Dict:\n try:\n schema = generateSchema(fileSchema)\n logger.info(\"Loading data from input file\")\n df = (\n spark.read.format(\"csv\")\n .option(\"header\", True)\n .schema(schema)\n .load(filePath)\n )\n count = df.count()\n windowBy = Window.partitionBy(f.col(pkey)).orderBy(f.col(definingCol))\n logger.info(\"Generating the required Audit Columns\")\n df = (\n df.withColumn(\n \"hashKey\",\n f.sha2(\n f.concat_ws(\n \"|\", *map(lambda key_cols: f.col(key_cols), hashKeyCols)\n ),\n 256,\n ),\n )\n .withColumn(\n \"hashData\",\n f.sha2(\n f.concat_ws(\n \"|\", *map(lambda key_cols: f.col(key_cols), hashDataCols)\n ),\n 256,\n ),\n )\n .withColumn(\"startDate\", f.col(definingCol))\n .withColumn(\"endDate\", f.lead(f.col(definingCol)).over(windowBy))\n .withColumn(\n str(partitionCol), f.lit(datetime.datetime.now().strftime(\"%Y-%m-%d\"))\n )\n )\n if not DeltaTable.isDeltaTable(spark, path):\n logger.info(\"Performing the initial load\")\n status = performFirstLoad(df, path, partitionCol)\n else:\n logger.info(\"Performing the incremental load\")\n status = performDeltaLoad(df, path, pkey)\n return {**status, **{\"count\": count}}\n except Exception as e:\n logger.error(\n \"Issue while processing the {0} error : {1}\".format(filePath, str(e)[:100])\n )\n return {\"status\": \"Failed\", \"message\": str(e)[:100], \"count\": 0}\n # raise DLoaderException(\"Failed while processing the data :{0}\".format(e))","def process_song_data(spark, input_data, output_data):\n # get filepath to song data file\n song_data = input_data + \"song_data/*/*/*/*.json\"\n \n # read song data file\n df = spark.read.json(song_data)\n\n # extract columns to create songs table\n songs_table = df.filter(df.song_id != '') \\\n .select(\"song_id\", \"title\", \"artist_id\", \"year\", \"duration\") \\\n .dropDuplicates()\n \n # output filepath to songs table file\n songs_table_path = output_data + \"songs_table.parquet\"\n \n # write songs table to parquet files partitioned by year and artist\n songs_table.write.partitionBy(\"year\", \"artist_id\").mode(\"overwrite\") \\\n .parquet(songs_table_path)\n\n # extract columns to create artists table\n artists_table = df.filter(df.artist_id != '').select(\"artist_id\",\n \"artist_name\", \"artist_location\", \"artist_latitude\", \"artist_longitude\") \\\n .dropDuplicates()\n \n # output filepath to artists table file\n artists_table_path = output_data + \"artists_table.parquet\"\n \n # write artists table to parquet files\n artists_table.write.mode(\"overwrite\") \\\n .parquet(artists_table_path)","def process_log_file(cur, filepath):\r\n\r\n # open log file\r\n df = pd.read_json(filepath, lines=True)\r\n df2 = pd.read_json(filepath, lines=True)\r\n\r\n # filter by NextSong action for missing data\r\n df2 = df2[df2['page']=='NextSong']\r\n\r\n\r\n\r\n # insert missing records into Song and Artist Table\r\n for i, row in df2.iterrows():\r\n cur.execute(artist_table_insert, (row.artist + str(i), row.artist, row.location, 0, 0))\r\n for i, row in df2.iterrows():\r\n cur.execute(song_table_insert, (row.song + str(i), row.song, row.artist + str(i), 0, row.length))\r\n\r\n # filter by NextSong action\r\n df = df[df['page']=='NextSong']\r\n\r\n # convert timestamp column to datetime\r\n t = pd.to_datetime(df['ts'], unit='ms')\r\n\r\n # extract time data from timestamp\r\n time_data = {'start_time': t,'hour': pd.Series(t).dt.hour, 'day':pd.Series(t).dt.day,\r\n 'month': pd.Series(t).dt.month, 'year': pd.Series(t).dt.year,\r\n 'weekday': pd.Series(t).dt.dayofweek}\r\n #column_labels = []\r\n # insert time data records\r\n time_df = pd.DataFrame(time_data)\r\n\r\n for i, row in time_df.iterrows():\r\n cur.execute(time_table_insert, list(row))\r\n\r\n # load user table\r\n user_df = df[['userId', 'firstName','lastName','gender','level']]\r\n user_df.drop_duplicates(subset='userId',keep ='first',inplace = True)\r\n\r\n # insert user records\r\n for i, row in user_df.iterrows():\r\n cur.execute(user_table_insert, row)\r\n\r\n # insert songplay records\r\n for index, row in df.iterrows():\r\n\r\n # get songid and artistid from song and artist tables\r\n print(cur.mogrify(song_select, (row.song, row.artist, row.length)))\r\n cur.execute(song_select, (row.song, row.artist, row.length))\r\n results = cur.fetchone()\r\n\r\n if results:\r\n songid, artistid = results[0],results[1]\r\n else:\r\n songid, artistid = \"None\" + str(index), \"None\" + str(index)\r\n\r\n # insert songplay record\r\n songplay_data = (df[['ts', 'userId', 'level', 'sessionId','location','userAgent' ]])\r\n songplay_data['ts'] = pd.to_datetime(df['ts'], unit='ms')\r\n cur.execute(songplay_table_insert, (index, row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent))\r\n #conn.commit()\r","def process_song_data(spark, input_data, output_data, mode=\"overwrite\"):\n # get filepath to song data file\n song_data = input_data + \"song_data/*/*/*/*.json\"\n\n # read song data file\n print(\"reading song logs from {}\".format(song_data))\n df = spark.read.json(song_data)\n\n # extract columns to create songs table\n song_fields = ['song_id', 'title', 'artist_id', 'year', 'duration']\n songs_table = df.select(song_fields)\n songs_table = songs_table.withColumn('year', F.col('year').cast(IntegerType()))\n songs_table = songs_table.withColumn('duration', F.col('duration').cast(DoubleType()))\n\n # write songs table to parquet files partitioned by year and artist\n song_path = output_data + 'star_schema/song_table/'\n print(\"Writing Song Table to {}\".format(song_path))\n songs_table.write \\\n .mode(mode) \\\n .partitionBy('year', 'artist_id') \\\n .parquet(song_path)\n\n # extract columns to create artists table\n artist_fields = [\n 'artist_id', 'artist_name',\n 'artist_location', 'artist_latitude', 'artist_longitude'\n ]\n artists_table = df.select(artist_fields)\n artists_table = artists_table.withColumnRenamed(\n 'artist_name', 'name'\n )\n artists_table = artists_table.withColumnRenamed(\n 'artist_location', 'location'\n )\n artists_table = artists_table.withColumn(\n 'latitude',\n F.col('artist_latitude').cast(DoubleType())\n )\n artists_table = artists_table.withColumn(\n 'longitude',\n F.col('artist_longitude').cast(DoubleType())\n )\n artist_col_names = [\n 'artist_id', 'name', 'location', 'latitude', 'longitude'\n ]\n artists_table = artists_table.select(artist_col_names)\n\n # write artists table to parquet files\n artists_path = output_data + 'star_schema/artist_table'\n print(\"Writing Artist Table to {}\".format(artists_path))\n artists_table.write \\\n .mode(mode) \\\n .partitionBy('artist_id') \\\n .parquet(artists_path)","def process_song_data(spark, input_data, output_data):\n # get filepath to song data file\n song_data = os.path.join(input_data, 'song_data', '*', '*', '*')\n \n # read song data file\n df = spark.read.json(song_data)\n print(f\"Loaded song_data from {input_data}\")\n df.createOrReplaceTempView(\"song_data\")\n \n # extract columns to create songs table\n songs_table = spark.sql(\"\"\"\n SELECT song_id, title, artist_id, year, duration\n FROM song_data\n \"\"\")\n \n # write songs table to parquet files partitioned by year and artist\n songs_table_path = os.path.join(output_data, \"songs_table.parquet\")\n (songs_table.\n write.\n mode(\"overwrite\").\n partitionBy(\"year\", \"artist_id\").\n parquet(songs_table_path))\n print(f\"Stored song table on {songs_table_path}\")\n # extract columns to create artists table\n artists_table = spark.sql(\"\"\"\n SELECT \n DISTINCT(artist_id) AS artist_id, \n artist_name AS name, \n artist_location AS location, \n artist_latitude AS latitude, \n artist_longitude AS longitude\n FROM song_data\n \"\"\")\n \n # write artists table to parquet files\n artists_table_path = os.path.join(output_data, \"artists_table.parquet\")\n (artists_table.\n write.\n mode(\"overwrite\").\n parquet(artists_table_path))\n print(f\"Stored artists table at {artists_table_path}\")","def process_song_data(spark, input_data, output_data):\n # get filepath to song data file\n song_data = os.path.join(input_data, \"song-data/*/*/*/*.json\")\n\n # read song data file\n df = spark.read.json(song_data)\n\n # extract columns to create songs table\n songs_table = df.select('song_id', 'title', 'artist_id', 'year', 'duration')\n\n # write songs table to parquet files partitioned by year and artist_id\n songs_table.write.partitionBy('year', 'artist_id').parquet(output_data + 'songs', mode='overwrite')\n\n # extract columns to create artists table\n artists_table = df.select('artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude')\n\n # write artists table to parquet files\n artists_table.write.parquet(output_data + 'artists', mode='overwrite')","def process_input_data(input_data_path):\n if os.path.isdir(input_data_path):\n input_data_glob = glob.glob(input_data_path + \"/*.csv\")\n else:\n if is_gcs_path(input_data_path):\n # Download the input to a local\n with tempfile.NamedTemporaryFile() as hf:\n input_data = hf.name\n\n logging.info(\"Copying %s to %s\", input_data_path, input_data)\n input_data_gcs_bucket, input_data_gcs_path = split_gcs_uri(\n input_data_path)\n\n logging.info(\"Download bucket %s object %s.\", input_data_gcs_bucket,\n input_data_gcs_path)\n bucket = storage.Bucket(storage.Client(), input_data_gcs_bucket)\n storage.Blob(input_data_gcs_path, bucket).download_to_filename(\n input_data)\n else:\n input_data = input_data_path\n\n ext = os.path.splitext(input_data)[-1]\n if ext.lower() == '.zip':\n zip_ref = zipfile.ZipFile(input_data, 'r')\n zip_ref.extractall('.')\n zip_ref.close()\n # TODO: Hardcoding the file in the Archive to use is brittle.\n # We should probably just require the input to be a CSV file.:\n csv_file = 'stackoverflow-questions.csv'\n else:\n csv_file = input_data\n\n input_data_glob = glob.glob(csv_file)\n\n return input_data_glob","def process_song_data(spark, input_data, output_data):\n # get filepath to song data file\n song_data = input_data + 'song_data/*/*/*/*.json'\n \n # read song data file\n df = spark.read.json(song_data)\n \n # create view for songs table\n df.createOrReplaceTempView(\"songs\") \n \n \n # extract columns to create songs table. Adding Distinct and Not null to song_id as it is the primary key\n songs_table = spark.sql(\"\"\"\n SELECT DISTINCT song_id, \n title,\n artist_id,\n year,\n duration\n FROM songs\n WHERE song_id IS NOT NULL\n \"\"\")\n \n # write songs table to parquet files partitioned by year and artist\n songs_table.write.mode('overwrite').partitionBy(\"year\", \"artist_id\").parquet(output_data+'songs_table/')\n\n # create view for artists table\n df.createOrReplaceTempView(\"artists\") \n \n # extract columns to create artists table, Adding Distinct and Not null to artist_id as it is the primary key\n artists_table = spark.sql(\"\"\"\n SELECT DISTINCT artist_id, \n artist_name,\n artist_location,\n artist_latitude,\n artist_longitude\n FROM artists\n WHERE artist_id IS NOT NULL\n \"\"\")\n \n # write artists table to parquet files\n artists_table.write.mode('overwrite').parquet(output_data+'artists_table/')","def process_song_data(spark, song_input_data, output_data):\n # get filepath to song data file\n song_data = song_input_data\n \n # read song data file\n print(\"Processing JSON song data...\")\n df = spark.read.json(song_data)\n\n # extract columns to create songs table\n print(\"Extracting columns for song table...\")\n df.createOrReplaceTempView(\"songs_table\")\n songs_table = spark.sql(\"\"\"\n SELECT song_id, title, artist_id, year, duration\n FROM songs_table\n ORDER BY song_id\n \"\"\") \n \n print(\"Song table sample:\")\n songs_table.show(5, truncate=False)\n \n # write songs table to parquet files partitioned by year and artist\n print(\"Writing songs table to parquet files...\")\n songs_table.write.mode(\"overwrite\").partitionBy(\"year\", \"artist_id\")\\\n .parquet(output_data + \"songs_table.parquet\")\n \n # extract columns to create artists table\n print(\"Extracting columns for artists table...\")\n df.createOrReplaceTempView(\"artists_table\")\n artists_table = spark.sql(\"\"\"\n SELECT artist_id,\n artist_name AS name,\n artist_location AS location,\n artist_latitude AS latitude,\n artist_longitude AS longitude\n FROM artists_table\n ORDER BY artist_id DESC\n \"\"\") \n\n print(\"Artists table sample:\")\n artists_table.show(5, truncate=False)\n \n # write artists table to parquet files\n print(\"Writing artists table to parquet files...\")\n songs_table.write.mode(\"overwrite\").parquet(output_data + \"artists_table.parquet\")","def _process_task_log(self):\n directory = self._executor.log_dir\n if os.path.exists(directory):\n for root, _dirs, files in os.walk(directory):\n for name in files:\n filepath = os.path.join(root, name)\n object_name = str(self._task.project_id) + \"/\" + self._task.node_id + \"/log/\" + name\n if not self._s3.client.upload_file(self._s3.bucket, object_name, filepath):\n log.error(\"Error uploading file to S3\")","def process_song_data(spark, input_data, output_data):\n \n # get filepath to song data file\n song_data = os.path.join( input_data, \"song_data/*/*/*/*.json\")\n \n # SONG TABLE\n # read song data file\n df = spark.read.json(song_data)\n \n # extract columns to create songs table\n songs_table = df.select('song_id', 'title', 'artist_id',\n 'year', 'duration').dropDuplicates(['song_id'])\n \n print( \"HERE songs_table sample:\\n\")\n songs_table.show(5)\n # write songs table to parquet files partitioned by year and artist\n songs_table.write.partitionBy('year', 'artist_id').parquet(os.path.join(output_data, 'songs/songs.parquet'), 'overwrite')\n \n # ARTISTS TABLE\n # extract columns to create artists table\n artists_table = df.select(\"artist_id\",\"artist_name\",\"artist_location\",\"artist_latitude\",\"artist_longitude\").dropDuplicates(['artist_id'])\n \n print( \"HERE artists_table sample:\\n\")\n artists_table.show(5)\n # write artists table to parquet files\n artists_table.write.parquet(output_data + \"artists/\", mode=\"overwrite\")","def process_song_data(spark, input_data, output_data):\n\n # get filepath to song data file\n input_data = input_data+\"/song-data\"\n print(input_data)\n \n \"\"\"\n for x in os.walk(input_data):\n for y in glob.glob(os.path.join(x[0], '*.json')):\n song_data.append(y)\n \"\"\"\n\n df = spark.read.json(input_data)\n df.createOrReplaceTempView(\"Staging_Song_Data\")\n song_Data_DF = spark.sql(\"select * from Staging_Song_Data\")\n\n # extract columns to create songs table\n songs_query = \" SELECT song_id, title, artist_id, year, duration \" \\\n \" FROM Staging_Song_Data\"\n songs_table = spark.sql(songs_query)\n\n # write songs table to parquet files partitioned by year and artist\n songs_table.write.mode('overwrite').partitionBy(\"year\",\"artist_id\").parquet(path=output_data+\"songs\")\n\n # extract columns to create artists table\n artists_query=\"select artist_id, artist_name as name, \" \\\n \" artist_location as location, \" \\\n \" artist_latitude as latitude, \" \\\n \" artist_longitude as longitude \" \\\n \"from Staging_Song_Data \"\n artists_table =spark.sql(artists_query)\n artists_table = artists_table.dropDuplicates(['artist_id'])\n\n # write artists table to parquet files\n artists_table.write.mode('overwrite').parquet(path=output_data+\"artists\")","def process_log_file(cur, filepath):\n # open log file\n df = pd.read_json(filepath, lines=True)\n\n # filter by NextSong action\n df = df[df['page']=='NextSong']\n\n # convert timestamp column to datetime\n t = pd.to_datetime(df['ts'], unit='ms')\n \n # insert time data records\n #timestamp, hour, day, week of year, month, year, and weekday\n hour = t.dt.hour\n day = t.dt.day\n weekofyear = t.dt.weekofyear\n month = t.dt.month\n year = t.dt.year\n weekday = t.dt.weekday\n\n time_data = [df['ts'], hour, day, weekofyear, month, year, weekday]\n column_labels = ['timestamp', 'hour', 'day', 'week of year', 'month', 'year', 'weekday']\n time_df = pd.DataFrame.from_dict(dict(zip(column_labels, time_data)))\n\n for i, row in time_df.iterrows():\n try:\n cur.execute(time_table_insert, list(row))\n except psycopg2.Error as e:\n print(\"Error: Unable to insert record in time table in row number : {}\".format(i))\n print(e)\n\n # load user table\n user_df = df[['userId', 'firstName', 'lastName', 'gender', 'level']]\n\n # insert user records\n for i, row in user_df.iterrows():\n try:\n cur.execute(user_table_insert, row)\n except psycopg2.Error as e:\n print(\"Error: Unable to insert record in users table in row number : {}\".format(i))\n print(e)\n\n # insert songplay records\n for index, row in df.iterrows():\n \n # get songid and artistid from song and artist tables\n try:\n cur.execute(song_select, (row.song, row.artist, row.length))\n except psycopg2.Error as e:\n print(\"Error: Unable to execute song_select query to join songs and artists table in row number : {}\".format(index))\n print(e)\n results = cur.fetchone()\n \n if results:\n songid, artistid = results\n else:\n songid, artistid = None, None\n\n # insert songplay record\n #timestamp, user ID, level, song ID, artist ID, session ID, location, and user agent\n songplay_data = (row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent)\n try:\n cur.execute(songplay_table_insert, songplay_data)\n except psycopg2.Error as e:\n print(\"Error: Unable to insert record in songplays table in row number : {}\".format(i))\n print(e)","def process_song_data(spark, input_data, output_data):\n # get filepath to song data file\n song_data = os.path.join(input_data, 'song_data/*/*/*/*.json')\n \n #specify schema for increased performance and control\n song_schema = StructType([\n StructField(\"artist_id\", StringType()),\n StructField(\"artist_latitude\", DoubleType()),\n StructField(\"artist_location\", StringType()),\n StructField(\"artist_longitude\", StringType()),\n StructField(\"artist_name\", StringType()),\n StructField(\"duration\", DoubleType()),\n StructField(\"num_songs\", IntegerType()),\n StructField(\"song_id\", StringType()),\n StructField(\"title\", StringType()),\n StructField(\"year\", IntegerType()),\n ])\n \n # read song data file\n dfs = spark.read.json(song_data, schema=song_schema)\n \n # create temporary view of table in order to run SQL queries\n dfs.createOrReplaceTempView(\"song_table\")\n\n # extract columns to create songs table\n dim_songs = spark.sql(\"\"\"\n SELECT song_id,\n title,\n artist_id,\n year,\n duration\n FROM song_table\n WHERE song_id IS NOT NULL\n \"\"\")\n \n # write songs table to parquet files partitioned by year and artist\n dim_songs.write.mode('overwrite').partitionBy(\"year\", \"artist_id\").parquet(output_data+\"songs\")\n\n # extract columns to create artists table\n dim_artists = spark.sql(\"\"\"\n SELECT DISTINCT artist_id,\n artist_name AS name,\n artist_location AS location,\n artist_latitude AS latitude,\n artist_longitude AS longitude\n FROM song_table\n WHERE artist_id IS NOT NULL\n \"\"\")\n \n # write artists table to parquet files\n dim_artists.write.mode('overwrite').parquet(output_data+\"artists\")","def _create_input_data(self):\n SCHEMA = parse_table_schema_from_json(\n '{\"fields\": [{\"name\": \"data\", \"type\": \"BYTES\"}]}')\n\n def format_record(record):\n # Since Synthetic Source returns data as a dictionary, we should skip one\n # of the part\n import base64\n return {'data': base64.b64encode(record[1])}\n\n with TestPipeline() as p:\n ( # pylint: disable=expression-not-assigned\n p\n | 'Produce rows' >> Read(\n SyntheticSource(self.parse_synthetic_source_options()))\n | 'Format' >> Map(format_record)\n | 'Write to BigQuery' >> WriteToBigQuery(\n dataset=self.input_dataset,\n table=self.input_table,\n schema=SCHEMA,\n create_disposition=BigQueryDisposition.CREATE_IF_NEEDED,\n write_disposition=BigQueryDisposition.WRITE_EMPTY))","def main():\n import sys\n n = len(sys.argv)\n if n != 3:\n raise ValueError(\"Please specify an input s3 bin and output s3 bin\")\n spark = create_spark_session()\n input_data = sys.argv[1]\n output_data = sys.argv[2]\n \n process_song_data(spark, input_data, output_data) \n process_log_data(spark, input_data, output_data)","def lambda_handler(event, context):\n \n filename = None\n fobj = None\n\n try:\n \n filename = 'dlq' + '-' + datetime.datetime.now().strftime(\"%s\")\n fobj = open('/tmp/'+filename, 'w')\n logger.debug('S3 client set up.')\n\n for record in event['Records']:\n fobj.write(json.dumps(record['body']))\n fobj.write(\"\\n\")\n \n except Exception as ex:\n logger.error('Exception in executing ingestion to S3: {}'.format(ex))\n send_sns_alert(str(ex))\n raise\n\n else:\n \n #Saves file to S3\n fobj.close()\n load_data_s3(filename)\n\n return {\n 'statusCode': 200,\n 'body': json.dumps('Success!')\n }\n\n finally:\n\n # S3 - close temp object\n fobj.close()","def process_song_data(spark, input_data, output_data):\n # get filepath to song data file\n song_data = \"{}/song_data/*/*/*/*\".format(input_data)\n \n # define schema used to import song json data into our data frame\n songSchema = R([\n Fld(\"num_songs\", Int()),\n Fld(\"artist_id\", Str()),\n Fld(\"artist_latitude\", Dbl()),\n Fld(\"artist_longitude\", Dbl()),\n Fld(\"artist_location\", Str()),\n Fld(\"artist_name\", Str()),\n Fld(\"song_id\", Str()),\n Fld(\"title\", Str()),\n Fld(\"duration\", Dbl()),\n Fld(\"year\", Int())\n\n ])\n \n # read song data file\n df = spark.read.format(\"json\").load(song_data, schema=songSchema)\n\n # register the temp view from our dataframe df_song\n df.createOrReplaceTempView(\"df_song\")\n \n # extract columns to create songs table\n songs_table = spark.sql(\"\"\"\n SELECT DISTINCT song_id, \n title,\n artist_id, \n artist_name,\n year, \n duration FROM df_song\n \"\"\")\n \n # write songs table to parquet files partitioned by year and artist\n songs_table.write.partitionBy('year', 'artist_id').parquet('{}/dim_song.pq'.format(output_data))\n\n # extract columns to create artists table\n artists_table = spark.sql(\"\"\"\n SELECT DISTINCT artist_id,\n artist_name,\n artist_location,\n artist_latitude,\n artist_longitude\n FROM df_song\n \"\"\")\n \n # write artists table to parquet files\n artists_table.write.parquet('{}/dim_artist.pq'.format(output_data))","def process_city_data(spark, input_data, output_data):\n\n # get filepath to city data file\n city_data = os.path.join(input_data, 'city_data/*.csv')\n\n # read city data files\n df = spark.read.csv(city_data, header=True, sep=';')\n df = df.drop_duplicates(subset=['City', 'State'])\n print('city_count = ', df.count())\n\n # extract columns to create city table\n city_table = df.select(\n F.monotonically_increasing_id().alias('city_id'),\n F.col('City').alias('city_name'),\n F.col('State Code').alias('state'),\n F.col('State Code').alias('state_code'),\n F.col('Total Population').alias('total_population')\n )\n\n city_table.write.parquet(os.path.join(output_data, 'cities'), 'overwrite')","def process_log_file(cur, filepath):\n # open log file\n data_frame = pd.read_json(filepath, lines=True)\n\n # filter by NextSong action\n data_frame = data_frame[data_frame.page == 'NextSong']\n\n # convert timestamp column to datetime\n time_value = pd.to_datetime(data_frame['ts'])\n\n # insert time data records\n time_data = (time_value, time_value.dt.year, time_value.dt.month,\n time_value.dt.isocalendar().week, time_value.dt.dayofweek,\n time_value.dt.day, time_value.dt.hour)\n\n column_labels = ('timestamp', 'year', 'month', 'week', 'weekday', 'day', 'hour')\n\n time_df = pd.DataFrame.from_dict(dict(zip(column_labels, time_data)))\n\n for i, row in time_df.iterrows():\n cur.execute(time_table_insert, list(row))\n\n # load user table\n user_df = data_frame[['userId', 'firstName', 'lastName', 'gender', 'level']]\n\n # insert user records\n for i, row in user_df.iterrows():\n cur.execute(user_table_insert, row)\n\n # insert songplay records\n for index, row in data_frame.iterrows():\n\n # get songid and artistid from song and artist tables\n cur.execute(song_select, (row.song, row.artist, row.length))\n results = cur.fetchone()\n\n if results:\n songid, artistid = results\n else:\n songid, artistid = None, None\n\n # insert songplay record\n songplay_data = row[['ts', 'userId', 'level', 'sessionId', 'location', 'userAgent']]. \\\n append(pd.Series([songid,\n artistid],\n index=[\n 'songid',\n 'artistid']))\n songplay_data['ts'] = pd.to_datetime(songplay_data['ts'])\n\n cur.execute(songplay_table_insert, songplay_data)","def process_log_file(cur, filepath):\n df = pd.read_json(filepath, lines=True)\n df = df.loc[df.page == 'NextSong', :]\n\n # insert time data records\n df['ts'] = pd.to_datetime(df.ts, unit='ms')\n t = df['ts']\n time_data = {\n 'start_time': t,\n 'hour': t.dt.hour,\n 'day': t.dt.day,\n 'week': t.dt.week,\n 'month': t.dt.month,\n 'year': t.dt.year,\n 'weekday': t.dt.weekday\n }\n time_df = pd.DataFrame(data=time_data)\n for i, row in time_df.iterrows():\n cur.execute(time_table_insert, list(row))\n\n # insert user records\n user_df = df.loc[:, ['userId', 'firstName', 'lastName', 'gender', 'level']]\n for i, row in user_df.iterrows():\n cur.execute(user_table_insert, row)\n\n # insert songplay records\n for index, row in df.iterrows():\n cur.execute(song_select, (row.song, row.artist, row.length))\n results = cur.fetchone()\n\n if results:\n songid, artistid = results\n else:\n songid, artistid = None, None\n\n songplay_data = {\n 'start_time': row.ts,\n 'user_id': row.userId,\n 'level': row.level,\n 'song_id': songid,\n 'artist_id': artistid,\n 'session_id': row.sessionId,\n 'location': row.location,\n 'user_agent': row.userAgent\n }\n cur.execute(songplay_table_insert, list(songplay_data.values()))","def process_log_file(cursor, filepath):\n\n def get_timestamp_data(df):\n # convert timestamp column to datetime\n timestamp = pd.to_datetime(df['ts'], unit='ms')\n\n return (df['ts'].values,\n timestamp.dt.hour.values,\n timestamp.dt.day.values,\n timestamp.dt.week.values,\n timestamp.dt.month.values,\n timestamp.dt.year.values,\n timestamp.dt.weekday.values)\n\n # open log file\n df = pd.read_json(filepath, lines=True)\n\n # filter by NextSong action\n df = df[df['page'] == 'NextSong']\n\n # insert time data records\n time_data = get_timestamp_data(df)\n column_labels = ('timestamp', 'hour', 'day', 'week', 'month', 'year', 'weekday')\n time_df = pd.DataFrame(data=dict(zip(column_labels, time_data)))\n\n for i, row in time_df.iterrows():\n cursor.execute(time_table_insert, list(row))\n\n # load user table\n user_columns = ['userId', 'firstName', 'lastName', 'gender', 'level']\n user_df = df[user_columns]\n\n # insert user records\n for i, row in user_df.iterrows():\n cursor.execute(user_table_insert, row)\n\n # insert songplay records\n for index, row in df.iterrows():\n\n # get song_id and artist_id from song and artist tables\n cursor.execute(song_select, (row.song, row.artist, row.length))\n results = cursor.fetchone()\n\n if results:\n song_id, artist_id = results\n else:\n song_id, artist_id = None, None\n\n # insert songplay record\n songplay_data = (\n row['ts'], row['userId'], row['level'], song_id, artist_id, row['sessionId'], row['location'],\n row['userAgent'])\n cursor.execute(songplay_table_insert, songplay_data)","def s3_process(self, payload, classifier):\n s3_file_lines = StreamPreParsers.pre_parse_s3(payload.raw_record)\n for line in s3_file_lines:\n data = line.rstrip()\n payload.refresh_record(data)\n self.process_alerts(classifier, payload, data)","def main():\n spark = create_spark_session()\n\n input_data = \"s3a://udacitydenanodegree2020/\"\n output_data = \"s3a://udacitydenanodegree2020/output/\"\n\n process_song_data(spark, input_data, output_data) \n process_log_data(spark, input_data, output_data)","def process_log_file(cur, filepath: str) -> None:\n # open log file\n df = pd.read_json(filepath, lines=True)\n\n # filter by NextSong action\n df = df[df.page == \"NextSong\"].copy()\n\n # convert timestamp column to datetime\n df[\"ts\"] = pd.to_datetime(df[\"ts\"], unit=\"ms\")\n\n # insert time data records\n column_labels = [\"hour\", \"day\", \"week\", \"month\", \"year\", \"weekday\"]\n\n for column_label in column_labels:\n if column_label == \"week\":\n # FutureWarning: Series.dt.weekofyear and Series.dt.week have been\n # deprecated. Please use Series.dt.isocalendar().week instead.\n df[column_label] = df[\"ts\"].dt.isocalendar().week\n else:\n df[column_label] = getattr(df[\"ts\"].dt, column_label)\n\n time_df = pd.DataFrame()\n time_df[\"start_time\"] = df[\"ts\"]\n time_df = pd.concat([time_df, df[column_labels]], axis=1)\n time_df.head()\n\n for i, row in time_df.iterrows():\n cur.execute(sql_queries.time_table_insert, list(row))\n\n # load user table\n user_df = df[[\"userId\", \"firstName\", \"lastName\", \"gender\", \"level\"]]\n\n # insert user records\n for i, row in user_df.iterrows():\n cur.execute(sql_queries.user_table_insert, row)\n\n # insert songplay records\n for _, row in df.iterrows():\n\n # get songid and artistid from song and artist tables\n cur.execute(sql_queries.song_select, (row.song, row.artist, row.length))\n results = cur.fetchone()\n\n if results:\n songid, artistid = results\n else:\n songid, artistid = None, None\n\n # insert songplay record\n songplay_data = (\n row.ts,\n row.userId,\n row.level,\n songid,\n artistid,\n row.sessionId,\n row.location,\n row.userAgent,\n )\n cur.execute(sql_queries.songplay_table_insert, songplay_data)","def load_raw_to_bq(event, context):\n\n import os\n\n\n print(f\"Processing .....\")\n\n file = event\n project = os.environ.get('ENV_PROJECT')\n dataset = os.environ.get('ENV_DATASET')\n bucket = file.get(\"bucket\")\n tableCsv = file.get(\"name\")\n tableDestList = tableCsv.split(\".\")\n tableDest = tableDestList[0]\n table_id = f'{project}.{dataset}.{tableDest}'\n\n from Configuration import Configuration\n\n Configuration(tableCsv,bucket,table_id)\n\n\n print(f\"End Process.\")","def _ProcessLog(self, log_processor, logfile): # pylint: disable=R0201\n for line in open(os.path.join(self.data_directory, logfile)):\n log_processor.ProcessLine(line)","def get_data(self):\n s3 = boto3.resource('s3')\n for obj in s3.Bucket(self.bucket_name).objects.all():\n output=str(obj.get()['Body'].read())\n ip=re.findall( r'[0-9]+(?:\\.[0-9]+){3}', output)[0] \n date=output.split(' [')[-1].split(':')[0] \n date=datetime.datetime.strptime(date, \"%d/%b/%Y\")\n if int(self.check_table(ip, date)) == 0: \n self.write_to_table(ip, date)","def main():\n spark = create_spark_session()\n input_data = \"s3a://udacity-dend/\"\n output_data = \"s3a://dend-bucket-cpm/\"\n\n process_song_data(spark, input_data, output_data)\n process_log_data(spark, input_data, output_data)","def process_log_file(cur, filepath):\n df = pd.read_json(filepath, lines=True)\n\n df = df[df['page'] == 'NextSong'].astype({'ts':'datetime64[ms]'})\n\n t = pd.Series(df['ts'], index=df.index)\n\n time_data = [[d, d.hour, d.day, d.week, d.month, d.year, d.weekday()] for d in t]\n column_labels= ['ts', 'hour', 'day', 'week', 'month', 'year', 'weekday']\n time_df = pd.DataFrame(data=time_data, columns=column_labels)\n\n for i, row in time_df.iterrows():\n cur.execute(time_table_insert, list(row))\n\n columns = ['userId', 'firstName', 'lastName', 'gender', 'level']\n user_df = df[[*columns]]\n user_df = user_df[user_df.firstName.notnull()]\n\n for i, row in user_df.iterrows():\n cur.execute(user_table_insert, row)\n\n for index, row in df.iterrows():\n cur.execute(song_select, (row.song, row.artist, row.length))\n results = cur.fetchone()\n\n if results:\n songid, artistid = results\n else:\n songid, artistid = None, None\n\n songplay_data = (row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent)\n cur.execute(songplay_table_insert, songplay_data)","def main(event, context):\n r = requests.get(yql_url)\n\n if r.status_code == 200:\n content = r.content\n t = datetime.now()\n filename = 'iran_' + t.strftime('%Y-%m-%dT%H-%M-%S') + '.json'\n put_data_in_s3(content, filename)\n\n data_dict = json.loads(content)\n data = data_dict.get('list')\n\n # start inserting data into timeseries database\n write_wind_data_to_csv(data)\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\n user=USERNAME, password=PASS)\n cur = conn.cursor()\n f = open('/tmp/wind_data.csv', 'r')\n cur.copy_from(f, 'windts', sep=',', columns=['speed', 'degree',\n 'utc_time', 'latitude', 'longitude'])\n conn.commit()\n try:\n os.remove('/tmp/wind_data.csv')\n except OSError:\n pass\n cur.close()\n\n write_temperature_data_to_csv(data)\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\n user=USERNAME, password=PASS)\n cur = conn.cursor()\n f = open('/tmp/temperature_data.csv', 'r')\n cur.copy_from(f, 'temperaturets', sep=',', columns=['temperature'\n ,'utc_time', 'latitude', 'longitude'])\n conn.commit()\n try:\n os.remove('/tmp/temperature_data.csv')\n except OSError:\n pass\n cur.close()\n\n write_pressure_data_to_csv(data)\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\n user=USERNAME, password=PASS)\n cur = conn.cursor()\n f = open('/tmp/pressure_data.csv', 'r')\n cur.copy_from(f, 'pressurets', sep=',', columns=['pressure'\n ,'utc_time', 'latitude', 'longitude'])\n conn.commit()\n try:\n os.remove('/tmp/pressure_data.csv')\n except OSError:\n pass\n cur.close()\n\n write_humidity_data_to_csv(data)\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\n user=USERNAME, password=PASS)\n cur = conn.cursor()\n f = open('/tmp/humidity_data.csv', 'r')\n cur.copy_from(f, 'humidityts', sep=',', columns=['humidity'\n ,'utc_time', 'latitude', 'longitude'])\n conn.commit()\n try:\n os.remove('/tmp/humidity_data.csv')\n except OSError:\n pass\n cur.close()\n\n write_condition_data_to_csv(data)\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\n user=USERNAME, password=PASS)\n cur = conn.cursor()\n f = open('/tmp/condition_data.csv', 'r')\n cur.copy_from(f, 'conditionts', sep=',', columns=['condition'\n ,'utc_time', 'latitude', 'longitude'])\n conn.commit()\n try:\n os.remove('/tmp/condition_data.csv')\n except OSError:\n pass\n cur.close()","def main():\n spark = create_spark_session()\n input_data = \"s3a://udacity-dend\"\n output_data = \"s3a://vivek1bucket\"\n \n process_song_data(spark, input_data, output_data) \n process_log_data(spark, input_data, output_data)","def process_log_file(cur, filepath):\r\n df=pd.read_json(filepath,lines=True)\r\n df2=df\r\n df=df[df['page']=='NextSong']\r\n ser=pd.to_datetime(df['ts'],unit='ms')\r\n times=[]\r\n for i in ser:\r\n times.append([i,i.hour,i.day,i.week,i.month,i.year,i.day_name()])\r\n for i in times:\r\n cur.execute(time_table_insert,i)\r\n df=df[['userId','firstName','lastName','gender','level']]\r\n for i,row in df.iterrows():\r\n cur.execute(users_table_insert,list(row))\r\n for i, row in df2.iterrows():\r\n cur.execute(song_select, (row.song, row.artist, row.length))\r\n res = cur.fetchone()\r\n if res:\r\n song_id, artist_id = res\r\n else:\r\n song_id, artist_id = None, None\r\n\r\n songplay_data = (\r\n i, pd.to_datetime(row.ts, unit='ms'),int(row.userId), row.level, song_id, artist_id, row.sessionId,\r\n row.location, row.userAgent)\r\n cur.execute(songplays_table_insert, songplay_data)","def main(input_filepath, output_filepath):\n productsDict = dataToDict(input_filepath)\n productsList = dictToCSV(productsDict)\n toCSV(productsList, output_filepath)\n\n logger = logging.getLogger(__name__)\n logger.info('making final data set from raw data')","def process_log_file(cur, filepath):\n\n df = pd.read_json(filepath, lines=True)\n\n df = df[df[\"page\"] == \"NextSong\"]\n\n t = df['ts'] = pd.to_datetime(df['ts'], unit='ms')\n\n accessor = t.dt\n time_data = (t, accessor.hour, accessor.day, accessor.week,\n accessor.month, accessor.year, accessor.weekday)\n\n time_df = pd.DataFrame.from_dict({\n \"timestamp\": t,\n \"hour\": accessor.hour,\n \"day\": accessor.day,\n \"week\": accessor.week,\n \"month\": accessor.month,\n \"year\": accessor.year,\n \"weekday\": accessor.weekday\n })\n\n for i, row in time_df.iterrows():\n cur.execute(time_table_insert, list(row))\n\n user_df = df[['userId', 'firstName', 'lastName', 'gender', 'level']]\n\n for i, row in user_df.iterrows():\n cur.execute(user_table_insert, row)\n\n for index, row in df.iterrows():\n\n cur.execute(song_select, (row.song, row.artist, row.length))\n results = cur.fetchone()\n\n if results:\n songid, artistid = results\n else:\n songid, artistid = None, None\n\n start_time = row[\"ts\"]\n user_id = row[\"userId\"]\n level = row[\"level\"]\n song_id = songid\n artist_id = artistid\n session_id = row['sessionId']\n location = row['location']\n user_agent = row['userAgent']\n\n songplay_data = (start_time, user_id, level, song_id, artist_id, session_id,\n location, user_agent)\n cur.execute(songplay_table_insert, songplay_data)","def handle_event(event, context):\n\n try:\n print(\"Received event: \" + json.dumps(event, indent=2))\n\n # grab resources section of event, get task execution ids\n task_execution_arns = event['resources']\n\n # now fetch the input filter info from each task_detail, fire off jobs\n new_files_to_process = []\n for task_execution_arn in task_execution_arns:\n # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/datasync.html#DataSync.Client.describe_task_execution\n response = datasync_client.describe_task_execution(TaskExecutionArn=task_execution_arn)\n print(\"Task execution details: \" + str(response))\n # this will be the location of the data in configured s3 bucket:\n # 'Includes': [\n # {\n # 'FilterType': 'SIMPLE_PATTERN',\n # 'Value': 'string'\n # },\n # ]\n if len(response['Includes']) > 0:\n file = response['Includes'][0]['Value']\n # files typically start with leading '/', strip that leading '/'\n print(\"Got filename:\" + file)\n if file.startswith('/', 0):\n new_files_to_process.append(file.lstrip('/'))\n else:\n new_files_to_process.append(file)\n else:\n print(\"Response didn't contain Includes files...\")\n\n if len(new_files_to_process) == 0:\n print('No files were parsed from input...exiting')\n return\n\n for new_file_to_process in new_files_to_process:\n state_machine_arn = os.environ['STATE_MACHINE_ARN']\n payload = {\"ObjectName\": new_file_to_process}\n json_payload = json.dumps(payload)\n print('Starting bcl2fastq with payload %s' % json_payload)\n #\n response = step_client.start_execution(stateMachineArn=state_machine_arn, input=json_payload)\n print(response)\n\n except Exception as e:\n print(e)\n print('Error handling event. %s' % e)\n raise e","def lambda_handler(event, context): # pylint: disable=too-many-locals,too-many-branches,too-many-statements\r\n try: # pylint: disable=too-many-nested-blocks\r\n print(\"Execution started!\")\r\n #print(\"Event: \",event)\r\n # Bucket name and Full path for file - where file will be uploded\r\n source_bucket_name = event[\"detail\"][\"requestParameters\"][\"bucketName\"]\r\n source_key = urllib.parse.unquote_plus(\r\n event[\"detail\"][\"requestParameters\"][\"key\"], encoding='utf-8')\r\n \r\n print(\"file_path: \",source_key)\r\n #Loading master config\r\n print(\"Loading master_config\")\r\n audit_config = {}\r\n config_path = \"./config/\" + \\\r\n os.environ['CCM_ENV'] + \"/master_config.json\"\r\n config_content = open(config_path).read()\r\n config_json = json.loads(config_content)\r\n audit_config = config_json[\"audit_config\"]\r\n snow_params = config_json[\"ERROR_NOTIFICATION_SNOW_PARAMS\"]\r\n athena_query_param = config_json[\"ATHENA_QUERY_PARAMS\"]\r\n athena_table_params = config_json[\"ATHENA_TABLE_PARAMS\"]\r\n\r\n # Audit Parameters Based on the Invoking lambda and its operation involved\r\n audit_config[\"component_type_code\"] = \"ETL\"\r\n audit_config[\"component_name\"] = \"PCP Appflow\"\r\n audit_config[\"source_name\"] = \"Patient Connections Platform\"\r\n audit_config[\"target_name\"] = \"Consumer Consent Management\"\r\n audit_config[\"full_file_path\"] = \"s3://\" + \\\r\n source_bucket_name + \"/\" + source_key\r\n audit_config[\"file_version_id\"] = \"\"\r\n\r\n # Creates Job Entry in ABC Framework\r\n print(\"audit config::\", audit_config)\r\n process_execution_id = audit_helper.\\\r\n invoke_edb_abc_log_process_status_event_job_entry(audit_config)\r\n audit_config[\"process_execution_id\"] = process_execution_id\r\n print(\"process_execution_id ::\", process_execution_id)\r\n #print(\"source_key: \",source_key)\r\n s3_write = boto3.client('s3')\r\n record_dict = {}\r\n file_name = \"\"\r\n final_json = \"\"\r\n # prefix = \"\"\r\n # file_list = []\r\n # client = boto3.client(\"s3\")\r\n # result = client.list_objects(Bucket=source_bucket_name, Prefix=source_key, Delimiter='/')\r\n # #print(result)\r\n # for obj in result.get('CommonPrefixes'):\r\n # prefix = obj.get('Prefix')\r\n # #print(prefix)\r\n # file_list = list_files(client,source_bucket_name,prefix)\r\n # for file in file_list:\r\n # #print(file)\r\n json_read = read_s3_file(source_bucket_name, source_key)\r\n data = json.loads(json_read)\r\n #print(data)\r\n if data != '':\r\n record_dict = {k.lower(): v for k, v in data.items()}\r\n print(\"Record_Dict::\",record_dict)\r\n event_type_param = {}\r\n event_type_list = athena_table_params.keys()\r\n print(\"event_type_list\",event_type_list)\r\n for key in event_type_list:\r\n print(\"key\",key)\r\n if key in source_key:\r\n print(\"key\",key)\r\n event_type_param = athena_table_params[key]\r\n print(event_type_param)\r\n if \"changeeventheader\" in record_dict:\r\n if record_dict[\"changeeventheader\"][\"changeType\"] == \"CREATE\":\r\n #and record_dict[\"dtpc_affiliate__c\"] == 'US':\r\n recordid_create = record_dict[\"changeeventheader\"][\"recordIds\"][0]\r\n print(recordid_create)\r\n if recordid_create != '':\r\n last_modified_date = record_dict[\"lastmodifieddate\"].replace(\":\",\".\")\r\n create_json = json.dumps(record_dict)\r\n final_json = create_json\r\n file_name = recordid_create + \"-create-\" + str(last_modified_date)\r\n print(\"file_name: \",file_name)\r\n outbound_path = event_type_param[\"folder_path\"]\r\n final_source_key = outbound_path + '/' + file_name+\".json\"\r\n print(\"final_source_key :\", final_source_key)\r\n s3_write.put_object(\r\n Body=final_json, Bucket=source_bucket_name, Key=final_source_key)\r\n else:\r\n raise Exception(\"RecordId is missing: \", record_dict)\r\n elif record_dict[\"changeeventheader\"][\"changeType\"] == \"UPDATE\":\r\n record_ids_list = record_dict[\"changeeventheader\"][\"recordIds\"]\r\n if len(record_ids_list) != 0:\r\n for ele in record_ids_list:\r\n print(ele)\r\n element = \"'\" + ele + \"'\"\r\n payload_condition = event_type_param[\"recordid_condition\"]\r\n query = 'SELECT * FROM '+event_type_param[\"athena_create_table\"]+\\\r\n ' WHERE lastmodifieddate IN(SELECT max(lastmodifieddate) from '\\\r\n +event_type_param[\"athena_create_table\"]+\\\r\n ', UNNEST(\"'+payload_condition[0]+'\".\"'+payload_condition[1]+\\\r\n '\") AS ln(jsondata) WHERE jsondata IN ('+element+'));'\r\n print(query)\r\n athena_query_param['athena_query'] = query\r\n query_result_record_id = athena_helper.perform_athena_search\\\r\n (athena_query_param)\r\n print(\"Athena Query Result for Create Path:::\", query_result_record_id)\r\n update_json = create_complete_payload(data,query_result_record_id)\r\n print(\"update_json: \",update_json)\r\n if len(update_json) != 0:\r\n last_modified_date = record_dict[\"lastmodifieddate\"].replace\\\r\n (\":\",\".\")\r\n final_json = json.dumps(update_json)\r\n file_name = ele + \"-update-\" + str(last_modified_date)\r\n print(\"file_name: \",file_name)\r\n outbound_path = event_type_param[\"folder_path\"]\r\n final_source_key = outbound_path + '/' + file_name+\".json\"\r\n print(\"final_source_key :\", final_source_key)\r\n s3_write.put_object(\r\n Body=final_json, Bucket=source_bucket_name, \\\r\n Key=final_source_key)\r\n else:\r\n print(ele,\" does not have a create payload\")\r\n else:\r\n raise Exception(\"RecordId is missing: \", record_dict)\r\n else:\r\n raise Exception(\"ChangeEventHeader is missing: \", record_dict)\r\n else:\r\n raise Exception(\"Invalid Payload: \", record_dict)\r\n\r\n except (Exception) as err: # pylint: disable=line-too-long,broad-except\r\n print(\"Error occured: {0}\".format(str(err)))\r\n audit_type = \"error\"\r\n error_msg = sys.exc_info()\r\n exc_type = error_msg\r\n exc_obj = error_msg\r\n snow_params[\"flag\"] = \"FAIL\"\r\n snow_params[\"error_message\"] = str(exc_obj)\r\n snow_params[\"error_type\"] = str(exc_type)\r\n audit_config[\"exception_message\"] = str(exc_obj)\r\n if audit_config != {}:\r\n logging.exception(sys.exc_info())\r\n audit_helper.invoke_edb_abc_log_process_status_event(\r\n audit_type, audit_config) # pylint: disable=line-too-long\r\n audit_helper.raise_snow_incident(snow_params)","def process_data(data):\n # Table Name from Json file\n table_name = data['table_name']\n\n # No of Column\n column_count = data['column_count']\n\n # No of Row\n row_count = data['row_count']\n\n # Table columns schema from Json file\n column_properties = data['column_properties']\n\n # Get the row row_properties\n row_properties = data['row_properties']\n return table_name, column_count, row_count, column_properties, row_properties","def copy_blobs_in_gcp_storage(source_bucket_name):\n\n # extract file and convert in dataframe\n extracted_df = extract()\n\n # transform the df\n transformed_df = transform (extracted_df)\n\n # the function loads clean csv content as csv file in clean-zone-bucket\n load(transformed_df)\n\n\n return \"Function executed sucessfully!\"","def main():\n spark = create_spark_session()\n input_data = \"s3a://udacity-dend/\"\n output_data = \"s3a://udacity-data-lake/output/\"\n\n process_song_data(spark, input_data, output_data)\n process_log_data(spark, input_data, output_data)","def main():\n spark = create_spark_session()\n input_data = \"s3a://udacity-dend/\"\n output_data = \"data/analytics\"\n \n process_song_data(spark, input_data, output_data) \n process_log_data(spark, input_data, output_data)","def process_log_data(log_data,\r\n seq_counts,\r\n mapping_file,\r\n fasta_files,\r\n qual_files,\r\n corrected_bc_count,\r\n keep_barcode=False,\r\n barcode_type=\"golay_12\",\r\n max_bc_errors=1.5,\r\n start_index=1,\r\n write_unassigned_reads=False,\r\n disable_bc_correction=False,\r\n added_demultiplex_field=None,\r\n save_barcode_frequencies=False):\r\n\r\n final_log_data = [\"demultiplex_fasta.py log data\\n\"]\r\n final_log_data.append(\"Metadata mapping file:\\t%s\" % mapping_file)\r\n final_log_data.append(\"Input FASTA file(s):\\t%s\" %\r\n \",\".join([curr_file.name for curr_file in fasta_files]))\r\n if qual_files:\r\n final_log_data.append(\"Input QUAL file(s):\\t%s\" %\r\n \",\".join([curr_file.name for curr_file in qual_files]))\r\n final_log_data.append(\"Total sequences in input files:\\t%d\" % seq_counts)\r\n final_log_data.append(\"Retain barcode:\\t%s\" % keep_barcode)\r\n final_log_data.append(\"Barcode type:\\t%s\" % barcode_type)\r\n final_log_data.append(\"Max barcode error/mismatches allowed:\\t%s\" %\r\n max_bc_errors)\r\n final_log_data.append(\"Starting sequence identifier:\\t%d\" % start_index)\r\n final_log_data.append(\r\n \"Write unassigned reads:\\t%s\" %\r\n write_unassigned_reads)\r\n final_log_data.append(\"Disable barcode correction:\\t%s\" %\r\n disable_bc_correction)\r\n final_log_data.append(\"Added demultiplex field:\\t%s\" %\r\n added_demultiplex_field)\r\n final_log_data.append(\"Save barcode frequencies:\\t%s\\n\" %\r\n save_barcode_frequencies)\r\n\r\n final_log_data.append(\"Barcodes corrected/not corrected:\\t%d/%d\" %\r\n (corrected_bc_count[0], corrected_bc_count[1]))\r\n\r\n # Make a list of SampleID/Counts/Barcodes/Added demultiplex for sorting\r\n id_counts_bcs = []\r\n counts_col = []\r\n for curr_key in log_data.keys():\r\n id_counts_bcs.append((curr_key.split(',')[-1], log_data[curr_key],\r\n ','.join(curr_key.split(',')[0:-1])))\r\n counts_col.append(int(log_data[curr_key]))\r\n\r\n counts_col = array(counts_col)\r\n\r\n final_log_data.append(\"Number of samples in mapping file:\\t%d\" %\r\n len(counts_col))\r\n final_log_data.append(\"Sample count min/max/mean:\\t%d / %d / %3.2f\" %\r\n (counts_col.min(), counts_col.max(), counts_col.mean()))\r\n\r\n id_counts_bcs = sorted(id_counts_bcs, key=itemgetter(1), reverse=True)\r\n\r\n final_log_data.append(\"Sample\\tSequence Count\\tBarcode/Added Demultiplex\")\r\n for curr_id in id_counts_bcs:\r\n final_log_data.append(\"%s\\t%s\\t%s\" %\r\n (curr_id[0], curr_id[1], curr_id[2]))\r\n\r\n final_log_data.append(\"Seqs written\\t%d\" % counts_col.sum())\r\n final_log_data.append(\"Percent of input seqs written\\t%3.2f\" %\r\n (counts_col.sum() / seq_counts))\r\n\r\n return final_log_data","def execute(self, context): \n aws_hook = AwsHook(self.aws_credentials)\n credentials = aws_hook.get_credentials()\n redshift = PostgresHook(self.redshift_conn_id)\n execution_date = context['execution_date']\n \n self.log.info(f\"Truncating {self.table}\")\n redshift.run(f\"TRUNCATE TABLE {self.table}\")\n \n \n self.log.info(f\"Inserting data into {self.table}\")\n s3_path = f\"s3://{self.s3_bucket}/{self.s3_key}\"\n\n if self.s3_key == \"log_data\":\n year = execution_date.year\n month = execution_date.month\n \n s3_path = '/'.join([s3_path, str(year), str(month)])\n \n formatted_sql = StageToRedshiftOperator.copy_sql.format(\n self.table,\n s3_path,\n credentials.access_key,\n credentials.secret_key,\n self.file_format,\n self.format_path\n )\n \n redshift.run(formatted_sql)","def runDataExtraction():\r\n config = CONFIG['steps']['DataExtraction']\r\n ci = config['inputs']\r\n co = config['outputs']\r\n columns = ci['columns']\r\n nrows = ci['nrows']\r\n input_bucket = ci['bucket']\r\n no_of_files = ci['no_of_files']\r\n\r\n output_bucket = co['bucket']\r\n csv_name_prefix = co['csv_name_prefix']\r\n\r\n minio_config = CONFIG['artifacts']['minio']\r\n minioClient = create_minio_client(minio_config[\"endpoint_url\"],\r\n access_key=minio_config[\"access_key\"],\r\n secret_key=minio_config[\"secret_key\"],\r\n secure=minio_config['secure'])\r\n\r\n boto_client = boto3.client(\"s3\",\r\n endpoint_url=minio_config[\"endpoint_url\"],\r\n aws_access_key_id=minio_config[\"access_key\"],\r\n aws_secret_access_key=minio_config[\"secret_key\"],\r\n region_name=minio_config[\"region_name\"])\r\n\r\n zip_files = get_files(input_bucket, boto_client, file_type='zip')\r\n\r\n no_of_files_to_process = no_of_files if no_of_files is not None else len(\r\n zip_files)\r\n for zip_file in tqdm(zip_files[:no_of_files_to_process], total=no_of_files_to_process):\r\n process_file(zip_file, input_bucket, output_bucket, minioClient, columns,\r\n nrows=nrows, output_csv_name_prefix=csv_name_prefix)","def BqTableDataFileProcessor(file_arg):\n data_insert_request_type = GetApiMessage('TableDataInsertAllRequest')\n insert_row_type = data_insert_request_type.RowsValueListEntry\n data_row_type = GetApiMessage('JsonObject')\n\n try:\n data_json = yaml.load(file_arg)\n\n if not data_json or not isinstance(data_json, list):\n raise TableDataFileError(\n 'Error parsing data file: no data records defined in file')\n\n rows = []\n for row in data_json:\n rows.append(insert_row_type(json=encoding.DictToMessage(\n row, data_row_type)))\n\n return rows\n except yaml.YAMLParseError as ype:\n raise TableDataFileError('Error parsing data file [{}]'.format(ype))","def process_log_file(cur, filepath):\n # open log file\n df = get_file_df(filepath)\n\n # filter by NextSong action\n df = df[df['page'] == 'NextSong']\n\n # convert timestamp column to datetime\n df['ts'] = df['ts'].apply(lambda x: datetime.datetime.fromtimestamp(x/1000)) \n t = df\n \n time_data = []\n for td in t['ts']:\n wd = True if td.weekday() <=6 else False\n time_data.append([str(td.time()), td.hour, td.day, td.week, td.month, td.year, wd])\n column_labels = ('start_time', 'hour', 'day', 'week', 'month', 'year', 'weekday')\n\n # insert time data records\n time_df = pd.DataFrame(time_data, columns=column_labels)\n\n for i, row in time_df.iterrows():\n cur.execute(time_table_insert, list(row))\n\n # load user table\n user_df = df[['userId', 'firstName', 'lastName', 'gender', 'level']].copy()\n\n # insert user records\n for i, row in user_df.iterrows():\n cur.execute(user_table_insert, row)\n\n # insert songplay records\n for index, row in df.iterrows():\n \n # get songid and artistid from song and artist tables\n cur.execute(song_select, (row.song, row.artist, row.length))\n results = cur.fetchone()\n \n if results:\n songid, artistid = results\n else:\n songid, artistid = None, None\n\n # insert songplay record\n #user_id, level, song_id, artist_id, session_id, location, user_agent\n songplay_data = [row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent]\n cur.execute(songplay_table_insert, songplay_data)","def process_log_event(event, context):\n\n with open('config.json') as fh:\n config = json.load(fh)\n serialized = event['awslogs'].pop('data')\n data = json.loads(zlib.decompress(\n base64.b64decode(serialized), 16+zlib.MAX_WBITS))\n message = [\n \"An error was detected\",\n \"\",\n \"Log Group: %s\" % data['logGroup'],\n \"Log Stream: %s\" % data['logStream'],\n \"Log Owner: %s\" % data['owner'],\n \"\",\n \"Log Contents\",\n \"\"]\n\n for evt in data['logEvents']:\n message.append(message_event(evt))\n message.append(\"\")\n\n params = dict(\n TopicArn=config['topic'],\n Subject=config['subject'],\n Message='\\n'.join(message))\n sns.publish(**params)","def convert_to_json(basepath, sendto):\n\n logger = logging.getLogger('WikiLog')\n\n k = bucket.new_key(basepath)\n\n filenames = []\n year = month = day = hrs = ''\n\n for key in bucket.list():\n thisfile = key.name.encode('utf-8')\n if 'projectviews' not in thisfile and 'sql' not in thisfile and '.gz' in thisfile and thisfile.startswith(basepath):\n # S3 key name is of the format kt-wiki/pageviews/2016/2016-06/pageviews-20160601-000000.gz\n # Split by / to get last element\n filenames.append(thisfile)\n logger.info(\"Processing file: {}\".format(thisfile))\n fname = thisfile.split('/')\n\n # Get content from filename and save to local\n # Split again to Grab year, month, day, hour value from filename\n key.get_contents_to_filename('/home/ubuntu/WikiView/data/' + fname[-1])\n fname1 = fname[-1]\n data_time = fname1[:-3].split('-')\n year, month, day, hrs = data_time[1][:4], data_time[1][4:6], data_time[1][-2:], data_time[-1]\n\n docname = 'pageviews-' + year + '-' + month + '-' + day + '-' + hrs + '.json'\n dictlist = []\n\n # save file from s3 to local, read, write to json, push json to s3\n with open(docname, 'w') as fp:\n #\n with gzip.open('/home/ubuntu/WikiView/data/'+fname[-1],'r') as fin:\n for line in fin:\n line = line.split(' ')\n doc = {}\n doc['ymdh'] = year + '-' + month + '-' + day + '-' + hrs\n try:\n # format: project, title, views, bytes ~ en Main_Page 242332 4737756101\n prj, title, vcount = line[0], line[1], line[2]\n doc['prj'] = prj\n doc['title'] = title\n doc['vcount'] = vcount\n json.dump(doc,fp)\n fp.write('\\n')\n except:\n logger.error('Error reading gzip file {} at line: {}'.format(thisfile, line))\n pass\n# sys.exc_clear()\n\n # Now, save the json file to \n key_name = 'pageviews-' + year + '-' + month + '-' + day + '-' + hrs + '.json'\n full_key_name = os.path.join(sendto, key_name)\n k = bucket.new_key(full_key_name)\n\n logger.info(\"Sending json file to S3: {}\".format(docname))\n k.set_contents_from_filename(key_name)\n\n # Remove temp file\n logger.info(\"Removing temp file: {} {}\".format('/home/ubuntu/WikiView/data/', fname[-1]))\n os.remove('/home/ubuntu/WikiView/data/'+fname[-1])\n logger.info(\"Removing temp file: {}\".format(key_name))\n os.remove(key_name)\n logger.info('Finished!!!')","def main(input_filepath, output_filepath):\n logger = logging.getLogger(__name__)\n logger.info('making final data set from raw data')\n\n conn = sqlite3.connect('../raw/td_V2.db')\n git_commits = pd.read_sql_query(\"SELECT * FROM GIT_COMMITS\",conn)\n szz_fault_inducing_commits = pd.read_sql_query(\"SELECT * FROM szz_fault_inducing_commits\",conn)\n refactoring_miner = pd.read_sql_query(\"SELECT * FROM refactoring_miner\",conn)\n refactoring_miner = refactoring_miner[refactoring_miner[\"COMMIT_HASH\"].isin(git_commits[\"COMMIT_HASH\"])]\n git_commits_changes = pd.read_sql_query(\"SELECT * FROM GIT_COMMITS_CHANGES\", conn)\n git_commits_changes = git_commits_changes[git_commits_changes[\"COMMIT_HASH\"].isin(refactoring_miner[\"COMMIT_HASH\"])]\n\n preprocess(git_commits, szz_fault_inducing_commits, refactoring_miner, git_commits_changes)","def get_raw_data(report, bucket, replay_path, query):\n\n logger = logging.getLogger(\"SimpleReplayLogger\")\n s3_client = boto3.client('s3')\n try:\n response = s3_client.get_object(Bucket=bucket.get('bucket_name'), Key=f\"{replay_path}/raw_data/{query}000\")\n except Exception as e:\n logger.error(f\"Unable to get raw data from S3. Results for {query} not found. {e}\")\n df = pd.read_csv(response.get(\"Body\")).fillna(0)\n logger.debug(f\"Parsing results from '{query}' query.\")\n if query == 'latency_distribution':\n report.feature_graph = df\n else:\n for t, vals in report.tables.items():\n if vals.get('sql') == query:\n vals['data'] = read_data(t, df, vals.get('columns'), report)","def load_dict_to_delta_table(spark, s3_data_bucket, table_schema, table_name, data, overwrite=False):\n table_to_col_names_dict = {}\n table_to_col_names_dict[\"transaction_fabs\"] = TRANSACTION_FABS_COLUMNS\n table_to_col_names_dict[\"transaction_fpds\"] = TRANSACTION_FPDS_COLUMNS\n table_to_col_names_dict[\"transaction_normalized\"] = list(TRANSACTION_NORMALIZED_COLUMNS)\n table_to_col_names_dict[\"awards\"] = list(AWARDS_COLUMNS)\n table_to_col_names_dict[\"financial_accounts_by_awards\"] = list(FINANCIAL_ACCOUNTS_BY_AWARDS_COLUMNS)\n\n table_to_col_info_dict = {}\n for tbl_name, col_info in zip(\n (\"transaction_fabs\", \"transaction_fpds\"), (TRANSACTION_FABS_COLUMN_INFO, TRANSACTION_FPDS_COLUMN_INFO)\n ):\n table_to_col_info_dict[tbl_name] = {}\n for col in col_info:\n table_to_col_info_dict[tbl_name][col.dest_name] = col\n\n # Make sure the table has been created first\n call_command(\n \"create_delta_table\",\n \"--destination-table\",\n table_name,\n \"--alt-db\",\n table_schema,\n \"--spark-s3-bucket\",\n s3_data_bucket,\n )\n\n if data:\n insert_sql = f\"INSERT {'OVERWRITE' if overwrite else 'INTO'} {table_schema}.{table_name} VALUES\\n\"\n row_strs = []\n for row in data:\n value_strs = []\n for col_name in table_to_col_names_dict[table_name]:\n value = row.get(col_name)\n if isinstance(value, (str, bytes)):\n # Quote strings for insertion into DB\n value_strs.append(f\"'{value}'\")\n elif isinstance(value, (date, datetime)):\n # Convert to string and quote\n value_strs.append(f\"\"\"'{value.isoformat()}'\"\"\")\n elif isinstance(value, bool):\n value_strs.append(str(value).upper())\n elif isinstance(value, (Sequence, Set)):\n # Assume \"sequences\" must be \"sequences\" of strings, so quote each item in the \"sequence\"\n value = [f\"'{item}'\" for item in value]\n value_strs.append(f\"ARRAY({', '.join(value)})\")\n elif value is None:\n col_info = table_to_col_info_dict.get(table_name)\n if (\n col_info\n and col_info[col_name].delta_type.upper() == \"BOOLEAN\"\n and not col_info[col_name].handling == \"leave_null\"\n ):\n # Convert None/NULL to false for boolean columns unless specified to leave the null\n value_strs.append(\"FALSE\")\n else:\n value_strs.append(\"NULL\")\n else:\n value_strs.append(str(value))\n\n row_strs.append(f\" ({', '.join(value_strs)})\")\n\n sql = \"\".join([insert_sql, \",\\n\".join(row_strs), \";\"])\n spark.sql(sql)","def format_data(df):\n\n if len(df) == 0:\n print('No logs found, please check your data')\n return None\n\n # Separate the fields in request and response\n print('Extracting request and response ...')\n df1 = pd.concat([df.drop(['request', 'response'], axis=1).reset_index(drop=True),\n df['request'].apply(pd.Series).add_prefix('request_').reset_index(drop=True),\n pd.DataFrame(df['response']\n .tolist()).add_prefix('response_')], axis=1) # type: pd.DataFrame\n df1['request_input'] = pd.json_normalize(df['request'])['input.text']\n\n # Add context and output fields\n print('Extracting context and output ...')\n df2 = pd.concat([df1.drop(['response_context', 'response_output'], axis=1),\n df1['response_context'].apply(pd.Series).add_prefix('response_context_'),\n pd.DataFrame(df1['response_output'].tolist()).add_prefix('response_')],\n axis=1) # type: pd.DataFrame\n # Add context_system fields\n df3 = pd.concat([df2.drop(['response_context_system'], axis=1),\n df2['response_context_system'].apply(pd.Series).add_prefix('response_')],\n axis=1) # type: pd.DataFrame\n\n if 'response_context_response_context_IntentStarted' in df3.columns \\\n and 'response_context_response_context_IntentCompleted' in df3.columns:\n cols = ['log_id', 'response_timestamp', 'response_context_conversation_id', 'request_input', 'response_text',\n 'response_intents', 'response_entities', 'response_nodes_visited', 'response_dialog_request_counter',\n 'response_dialog_stack', 'response_dialog_turn_counter',\n 'response_context_response_context_IntentStarted', 'response_context_response_context_IntentCompleted']\n else:\n cols = ['log_id', 'response_timestamp', 'response_context_conversation_id', 'request_input', 'response_text',\n 'response_intents', 'response_entities', 'response_nodes_visited', 'response_dialog_request_counter',\n 'response_dialog_stack', 'response_dialog_turn_counter']\n\n print('Extracting intents ...')\n # Select a few required columns\n df4 = df3[cols].copy(deep=True) # type: pd.DataFrame\n # Limit fetched intents to a maximum value of 3\n df4.loc[:, 'response_intents'] = df4['response_intents'].apply(lambda x: x[:3])\n # Separate intents into different fields\n df5 = pd.concat([df4.drop(['response_intents'], axis=1),\n pd.DataFrame(df4['response_intents'].values.tolist()).add_prefix(\n 'response_intent_')], axis=1) # type: pd.DataFrame\n # Check if at least 3 intents are identified\n if 'response_intent_2' in df5.columns:\n # Put the 3 intents and confidences into separate fields\n df6 = pd.concat([df5.drop(['response_intent_0', 'response_intent_1',\n 'response_intent_2'], axis=1),\n df5['response_intent_0'].apply(pd.Series).add_prefix('response.top_intent_'),\n df5['response_intent_1'].apply(pd.Series).add_prefix('Intent 2 '),\n df5['response_intent_2'].apply(pd.Series).add_prefix('Intent 3 ')],\n axis=1) # type: pd.DataFrame\n # Convert confidence to numeric type\n cols = ['response.top_intent_confidence', 'Intent 2 confidence', 'Intent 3 confidence']\n df6[cols] = df6[cols].apply(pd.to_numeric, errors='coerce', axis=1)\n # Add confidence gap column\n df6['Confidence gap (between 1 and 2)'] = df6['response.top_intent_confidence'] - df6['Intent 2 confidence']\n elif 'response_intent_1' in df5.columns:\n # Put the 3 intents and confidences into separate fields\n df6 = pd.concat([df5.drop(['response_intent_0', 'response_intent_1'], axis=1),\n df5['response_intent_0'].apply(pd.Series).add_prefix('response.top_intent_'),\n df5['response_intent_1'].apply(pd.Series).add_prefix('Intent 2 ')],\n axis=1) # type: pd.DataFrame\n # Convert confidence to numeric type\n cols = ['response.top_intent_confidence', 'Intent 2 confidence']\n df6[cols] = df6[cols].apply(pd.to_numeric, errors='coerce', axis=1)\n df6['Intent 3 intent'] = ''\n df6['Intent 3 confidence'] = ''\n # Add confidence gap column\n df6['Confidence gap (between 1 and 2)'] = df6['response.top_intent_confidence'] - df6['Intent 2 confidence']\n else:\n # Create the top intent and its confidence column\n df6 = pd.concat([df5.drop(['response_intent_0'], axis=1),\n df5['response_intent_0'].apply(pd.Series).add_prefix('response.top_intent_')],\n axis=1) # type: pd.DataFrame\n # df6['Confidence gap (between 1 and 2)'] = ''\n # df6['Intent 2 intent'] =''\n # df6['Intent 2 confidence'] = ''\n # df6['Intent 3 intent'] =''\n # df6['Intent 3 confidence'] = ''\n new_cols_list = ['Confidence gap (between 1 and 2)', 'Intent 2 intent', 'Intent 2 confidence',\n 'Intent 3 intent', 'Intent 3 confidence']\n\n df6.reindex(columns=[*df6.columns.tolist(), *new_cols_list], fill_value='')\n\n # Rename columns\n if 'response_context_response_context_IntentStarted' in df6.columns \\\n and 'response_context_response_context_IntentCompleted' in df6.columns:\n df6.rename(columns={'response_nodes_visited': 'response.output.nodes_visited_s',\n 'response_context_conversation_id': 'response.context.conversation_id',\n 'response_timestamp': 'response.timestamp',\n 'response_context_response_context_IntentStarted': 'response_context_IntentStarted',\n 'response_context_response_context_IntentCompleted': 'response_context_IntentCompleted'},\n inplace=True)\n else:\n df6.rename(columns={'response_nodes_visited': 'response.output.nodes_visited_s',\n 'response_context_conversation_id': 'response.context.conversation_id',\n 'response_timestamp': 'response.timestamp'},\n inplace=True)\n # Change format of numeric and date columns\n df6['response.top_intent_confidence'] = pd.to_numeric(df6['response.top_intent_confidence'])\n df6['response.timestamp'] = pd.to_datetime(df6['response.timestamp'])\n df6['Date'] = [datetime.datetime.date(d) for d in df6['response.timestamp']] # extracting date from timestamp\n df6['Customer ID (must retain for delete)'] = '' # Adding a column to retain customer id\n\n print('Completed!')\n return df6","def stream_to_s3(task_name,data,header,timestamp_suffix,**kwargs):\n if kwargs:\n file = '_'.join([task_name,timestamp_suffix,str(kwargs['batch_id'])])+'.csv'\n else:\n file = '_'.join([task_name,timestamp_suffix])+'.csv'\n\n f = io.StringIO()\n with smart_open.open('s3://{bucket_name}/{task_name}/{file}'.format(bucket_name=bucket_name,task_name=task_name,file=file), 'w') as fout:\n logger.info('Streaming file contents to S3')\n _writer = csv.writer(fout)\n _writer.writerow(header)\n fout.write(f.getvalue())\n \n for row in data:\n f.seek(0)\n f.truncate(0)\n _writer.writerow(row)\n fout.write(f.getvalue())\n \n f.close()\n logger.info('Complete')\n\n return file","def process_data(self, data):\n try:\n payload = self.extract(data)\n except (ValueError, InvalidToken) as doh:\n self.log.error('Error: {}, Data: {}'.format(doh, data))\n else:\n fields = {}\n tags = {}\n # writing strings to a field in Influx requires a double-quote\n tags['username'] = '\"{}\"'.format(payload['user'])\n # Dumbass Influx doesn't let you group by fields or aggregate tags...\n # I want to count the unique occurrences of a user over a period of time\n # to show current connected user counts, *and* be able to group by\n # those usernames over time to show specific user usage. Wish I\n # used TimescaleDB instead of InfluxDB\n fields['user'] = '\"{}\"'.format(payload.pop('user'))\n fields['source'] = '\"{}\"'.format(payload.pop('source'))\n fields['target'] = '\"{}\"'.format(payload.pop('target'))\n fields['packets'] = 1 # each event represents a single packet\n timestamp = payload.pop('time')\n self.influx.write(fields=fields, tags=tags, timestamp=timestamp)","def process_logs(logs):\n all_data = {}\n for log in logs:\n with open(log) as f:\n data = json.load(f)\n scenario = data[0].get(\"scenario\", None)\n if scenario is None:\n # No scenario name, no way to organize the data\n continue\n\n # Use the log's date as the run identifier\n # This assumes the format is SCENARIO-YYYY-MM-DD.json\n # NOTE: This may not match the GitHub Action run dates due to tests taking\n # a very long time.\n day = datetime.strptime(log[1+len(scenario):-5], \"%Y-%m-%d\").strftime(\"%Y%m%d\")\n if day not in all_data:\n all_data[day] = {}\n\n # Group them by scenario, assume each file is from one scenario per day\n all_data[day][scenario] = data\n return all_data","def dump_job_data(s3, bucket, key, ecosystem, package, version):\n data = s3.read_object(bucket, key)\n timestamp_str = datetime.datetime.utcnow().strftime(\"%Y-%m-%dT%H:%M:%S.%f\")\n filename = \"s3_data_{e}_{p}_{v}_{t}.json\".format(e=ecosystem,\n p=package,\n v=version,\n t=timestamp_str)\n with open(filename, 'w') as fout:\n json.dump(data, fout)","def main():\n conn = psycopg2.connect(\"host=127.0.0.1 dbname=sparkifydb user=student password=student\")\n cur = conn.cursor()\n\n process_data(cur, conn, filepath='data/song_data', func=process_song_file)\n print('song file processing is complete')\n process_data(cur, conn, filepath='data/log_data', func=process_log_file)\n print('log file processing is complete')\n conn.close()","def deduce_schema(self, input_data, *, schema_map=None):\n\n if self.input_format == 'csv':\n if self.csv_dialect:\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\n else:\n reader = csv.DictReader(input_data)\n elif self.input_format == 'json' or self.input_format is None:\n reader = json_reader(input_data)\n elif self.input_format == 'dict':\n reader = input_data\n else:\n raise Exception(f\"Unknown input_format '{self.input_format}'\")\n\n if schema_map is None:\n schema_map = OrderedDict()\n\n try:\n for json_object in reader:\n\n # Print a progress message periodically.\n self.line_number += 1\n if self.line_number % self.debugging_interval == 0:\n logging.info(f'Processing line {self.line_number}')\n\n # Deduce the schema from this given data record.\n if isinstance(json_object, dict):\n self.deduce_schema_for_record(\n json_object=json_object,\n schema_map=schema_map,\n )\n elif isinstance(json_object, Exception):\n self.log_error(\n f'Record could not be parsed: Exception: {json_object}'\n )\n if not self.ignore_invalid_lines:\n raise json_object\n else:\n self.log_error(\n 'Record should be a JSON Object '\n f'but was a {type(json_object)}'\n )\n if not self.ignore_invalid_lines:\n raise Exception(f'Record must be a JSON Object '\n f'but was a {type(json_object)}')\n finally:\n logging.info(f'Processed {self.line_number} lines')\n\n return schema_map, self.error_logs","def main(input_filepath, output_filepath):\n logger = logging.getLogger(__name__)\n logger.info('making final data set from raw data')\n\n # Get the data/raw/git-refactoring-commits-raw.csv file\n dataset = pd.read_csv(input_filepath, usecols=['Message', 'CommitSHA', 'IsRefactoring'])\n logger.info('Loaded data file ' + input_filepath + ' with ' + str(len(dataset)) + ' rows')\n\n logger.info('Applying pre-processing steps on the \"Message\" column...')\n dataset['Message'] = dataset['Message'].apply(preprocess)\n\n # Save the processed subset on data data/processed/git-refactoring-commits.csv\n logger.info('Saved processed results on ' + output_filepath + ' with ' + str(len(dataset)) + ' rows')\n dataset.to_csv(output_filepath, encoding='utf-8', index=False)","def create_dataset(input_file_path, output_file_path):\n col_index_map = {'user_id': 0, 'session_id': 1, 'timestamp': 2, 'step': 3, 'action_type': 4, 'reference': 5,\n 'platform': 6, 'city': 7, 'device': 8,\n 'current_filters': 9, 'impressions': 10, 'prices': 11}\n flat_dict = dict()\n with open(input_file_path, 'r') as csvFile:\n reader = csv.reader(csvFile)\n header = next(reader)\n col_names = [col_name for col_name in col_index_map.keys()]\n col_names.pop(0)\n index = 0\n for row in tqdm(reader):\n if len(flat_dict) > 40000:\n index += 1\n with open(output_file_path + \"_\" + str(index) + \".json\", \"w\") as file:\n json.dump(flat_dict, file)\n print(\" JSON : \", index)\n flat_dict = dict()\n col_values = [row[col_index_map[c_n]] for c_n in col_names]\n dict_for_each_row = dict(zip(col_names, col_values))\n to_list = dict_for_each_row['impressions']\n dict_for_each_row['impressions'] = to_list.split('|')\n to_list = dict_for_each_row['prices']\n dict_for_each_row['prices'] = to_list.split('|')\n user_id = row[col_index_map['user_id']]\n if user_id in flat_dict:\n flat_dict[user_id].append(dict_for_each_row)\n else:\n flat_dict[user_id] = [dict_for_each_row]\n\n print(\"Output is Saved\")","def main():\n spark = create_spark_session()\n input_data = \"s3a://udacity-dend/\"\n output_data = \"s3a://udacity-nanodegree-data-engineer/\"\n \n process_song_data(spark, input_data, output_data) \n process_log_data(spark, input_data, output_data)"],"string":"[\n \"def process_log_data(spark, input_data, output_data):\\n\\n # get filepath to log data file\\n log_data = input_data + \\\"log_data/2018/11/*.json\\\"\\n\\n # read log data file\\n log_data_schema = StructType([\\n StructField(\\\"artist\\\", StringType(), True),\\n StructField(\\\"auth\\\", StringType(), False),\\n StructField(\\\"firstName\\\", StringType(), True),\\n StructField(\\\"gender\\\", StringType(), True),\\n StructField(\\\"itemInSession\\\", IntegerType(), False),\\n StructField(\\\"lastName\\\", StringType(), True),\\n StructField(\\\"length\\\", DoubleType(), True),\\n StructField(\\\"level\\\", StringType(), False),\\n StructField(\\\"location\\\", StringType(), True),\\n StructField(\\\"method\\\", StringType(), False),\\n StructField(\\\"page\\\", StringType(), False),\\n StructField(\\\"registration\\\", DoubleType(), True),\\n StructField(\\\"sessionId\\\", IntegerType(), False),\\n StructField(\\\"song\\\", StringType(), True),\\n StructField(\\\"status\\\", IntegerType(), False),\\n StructField(\\\"ts\\\", DoubleType(), False),\\n StructField(\\\"userAgent\\\", StringType(), True),\\n StructField(\\\"userId\\\", StringType(), True)\\n ])\\n print(\\\"Start read s3 log data\\\") \\n df = spark.read.json(log_data, schema=log_data_schema)\\n \\n # filter by actions for song plays\\n print(\\\"Start filter for song plays\\\") \\n df = df.filter(col(\\\"page\\\") == \\\"NextSong\\\")\\n\\n # extract columns for users table\\n print(\\\"Start extract columns for users table\\\") \\n users_table = df.filter((col(\\\"userID\\\") != \\\"\\\") & (col(\\\"userID\\\").isNotNull())).select(\\n \\\"userID\\\", \\\"firstName\\\", \\\"lastName\\\", \\\"gender\\\", \\\"level\\\")\\n \\n # write users table to parquet files\\n print(\\\"Start write users table to parquet files\\\") \\n users_table.write.parquet(output_data + \\\"users_table.parquet\\\", mode=\\\"overwrite\\\")\\n\\n # create timestamp column from original timestamp column\\n print(\\\"Start create timestamp column from original timestamp column\\\") \\n get_timestamp = udf(\\n lambda x: x/1000,\\n DoubleType()\\n )\\n df = df.withColumn(\\\"start_timestamp\\\", get_timestamp(\\\"ts\\\")) \\n \\n # create datetime column from original timestamp column\\n print(\\\"Start create datetime column from original timestamp column\\\")\\n get_datetime = udf(\\n lambda x: datetime.fromtimestamp(x / 1000).replace(microsecond=0),\\n TimestampType()\\n )\\n df = df.withColumn(\\\"start_datetime\\\", get_datetime(\\\"ts\\\")) \\n \\n # extract columns to create time table\\n print(\\\"Start extract columns to create time table\\\")\\n time_table = df.withColumn(\\n \\\"hour\\\", hour(\\\"start_datetime\\\")).withColumn(\\n \\\"day\\\", dayofmonth(\\\"start_datetime\\\")).withColumn(\\n \\\"week\\\", weekofyear(\\\"start_datetime\\\")).withColumn(\\n \\\"month\\\", month(\\\"start_datetime\\\")).withColumn(\\n \\\"year\\\", year(\\\"start_datetime\\\")).withColumn(\\n \\\"weekday\\\", dayofweek(\\\"start_datetime\\\")).select(\\n \\\"start_datetime\\\", \\\"hour\\\", \\\"day\\\", \\\"week\\\", \\\"month\\\", \\\"year\\\", \\\"weekday\\\").distinct()\\n \\n # write time table to parquet files partitioned by year and month\\n print(\\\"Start write time table to parquet files partitioned by year and month\\\")\\n time_table.write.parquet(output_data + \\\"time_table.parquet\\\", mode=\\\"overwrite\\\", partitionBy=[\\\"year\\\", \\\"month\\\"])\\n\\n # read in song data to use for songplays table\\n print(\\\"Start read in song data to use for songplays table\\\")\\n song_df = spark.read.parquet(output_data + \\\"songs_table.parquet\\\")\\n\\n # extract columns from joined song and log datasets to create songplays table \\n print(\\\"Start extract columns from joined song and log datasets to create songplays table \\\")\\n artists_table = spark.read.parquet(output_data + \\\"artists_table.parquet\\\")\\n songs = song_df.join(artists_table, \\\"artist_id\\\", \\\"full\\\").select(\\n \\\"song_id\\\", \\\"title\\\", \\\"artist_id\\\", \\\"name\\\", \\\"duration\\\")\\n \\n songplays_table = df.join(songs, [df.song == songs.title, df.artist == songs.name, df.length == songs.duration], \\\"left\\\")\\n \\n songplays_table = songplays_table.join(time_table, \\\"start_datetime\\\", \\\"left\\\").select(\\n \\\"start_datetime\\\", \\\"userId\\\", \\\"level\\\", \\\"song_id\\\", \\\"artist_id\\\", \\\"sessionId\\\",\\n \\\"location\\\", \\\"userAgent\\\", \\\"year\\\", \\\"month\\\").withColumn(\\\"songplay_id\\\", monotonically_increasing_id())\\n \\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.parquet(output_data + \\\"songplays_table.parquet\\\", mode=\\\"overwrite\\\", partitionBy=[\\\"year\\\", \\\"month\\\"])\",\n \"def process_log_data(\\n spark: SparkSession,\\n input_data: str,\\n output_data: str\\n) -> None:\\n # get filepath to log data file\\n log_data = input_data + 'log-data/*'\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n\\n # filter by actions for song plays\\n actions_df = df.filter(df.page == 'NextSong') \\\\\\n .select('ts', 'userId', 'level', 'song', 'artist',\\n 'sessionId', 'location', 'userAgent')\\n\\n # extract columns for users table\\n users_table = df.select(\\n 'userId',\\n 'firstName',\\n 'lastName',\\n 'gender',\\n 'level'\\n ).dropDuplicates()\\n\\n users_table.createOrReplaceTempView('users')\\n # write users table to parquet files\\n users_table.write.parquet(\\n join(output_data, 'users/users.parquet'),\\n 'overwrite'\\n )\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = udf(lambda x: str(int(int(x) / 1000)))\\n actions_df = actions_df.withColumn(\\n 'timestamp',\\n get_timestamp(actions_df.ts)\\n )\\n\\n # create datetime column from original timestamp column\\n get_datetime = udf(lambda x: str(datetime.fromtimestamp(int(x) / 1000)))\\n actions_df = actions_df.withColumn('datetime', get_datetime(actions_df.ts))\\n\\n # extract columns to create time table\\n time_table = actions_df.select('datetime') \\\\\\n .withColumn('start_time', actions_df.datetime) \\\\\\n .withColumn('hour', hour('datetime')) \\\\\\n .withColumn('day', dayofmonth('datetime')) \\\\\\n .withColumn('week', weekofyear('datetime')) \\\\\\n .withColumn('month', month('datetime')) \\\\\\n .withColumn('year', year('datetime')) \\\\\\n .withColumn('weekday', dayofweek('datetime')).dropDuplicates()\\n\\n # write time table to parquet files partitioned by year and month\\n time_table.createOrReplaceTempView('time')\\n time_table.write.partitionBy(\\n 'year', 'month') \\\\\\n .parquet(join(output_data, 'time/time.parquet'), 'overwrite')\\n # read in song data to use for songplays table\\n song_df = spark.read.json(input_data + 'song_data/*/*/*/')\\n joined_df = actions_df.join(\\n song_df,\\n (actions_df.artist == song_df.artist_name),\\n 'inner'\\n )\\n # extract columns from joined\\n # song and log datasets to create songplays table\\n songplays_table = joined_df.select(\\n actions_df.datetime.alias('start_time'),\\n actions_df.userId.alias('user_id'),\\n actions_df.level.alias('level'),\\n song_df.song_id.alias('song_id'),\\n song_df.artist_id.alias('artist_id'),\\n actions_df.sessionId.alias('session_id'),\\n actions_df.location.alias('location'),\\n actions_df.userAgent.alias('user_agent'),\\n year(actions_df.datetime).alias('year'),\\n month(actions_df.datetime).alias('month')) \\\\\\n .withColumn('songplay_id', monotonically_increasing_id())\\n\\n songplays_table.createOrReplaceTempView('songplays')\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.\\\\\\n partitionBy('year', 'month').\\\\\\n parquet(join(output_data, 'songplays/songplays.parquet'), 'overwrite')\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = input_data + \\\"log_data/*/*/*.json\\\"\\n\\n # read log data file\\n df = df = spark.read.json(log_data)\\n \\n # filter by actions for song plays\\n df = df = df.filter(df.page == 'NextSong')\\n\\n # extract columns for users table \\n users_table = df.filter(df.userId != '').selectExpr(\\\"userId as user_id\\\",\\n \\\"firstName as first_name\\\", \\\"lastName as last_name\\\", \\\"gender\\\", \\\"level\\\") \\\\\\n .dropDuplicates()\\n \\n # output filepath to users table file\\n users_table_path = output_data + \\\"users_table.parquet\\\"\\n \\n # write users table to parquet files\\n users_table.write.mode(\\\"overwrite\\\") \\\\\\n .parquet(users_table_path)\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = udf(lambda x: datetime.fromtimestamp(x/1000).strftime('%Y-%m-%d %H:%M:%S'))\\n df = df.withColumn(\\\"start_time\\\", get_timestamp(df.ts))\\n \\n # create datetime column from original timestamp column\\n get_datetime = udf(lambda x: datetime.fromtimestamp(x/1000).strftime('%Y-%m-%d'))\\n df = df.withColumn(\\\"datetime\\\", get_datetime(df.ts))\\n \\n # extract columns to create time table\\n time_table = df.select(\\\"start_time\\\", hour(\\\"start_time\\\").alias(\\\"hour\\\"), dayofmonth(\\\"datetime\\\").alias(\\\"day\\\"),\\n weekofyear(\\\"datetime\\\").alias(\\\"week\\\"), month(\\\"datetime\\\").alias(\\\"month\\\"),\\n year(\\\"datetime\\\").alias(\\\"year\\\"), dayofweek(\\\"datetime\\\").alias(\\\"weekday\\\")).dropDuplicates()\\n \\n # output filepath to time table\\n time_table_path = output_data + \\\"time_table.parquet\\\"\\n \\n # write time table to parquet files partitioned by year and month\\n time_table.write.partitionBy(\\\"year\\\", \\\"month\\\").mode(\\\"overwrite\\\") \\\\\\n .parquet(time_table_path)\\n \\n # get filepath to song data file\\n song_data = input_data + \\\"song_data/*/*/*/*.json\\\"\\n\\n # read in song data to use for songplays table\\n song_df = spark.read.json(song_data)\\n\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = df.join(song_df, (df.song == song_df.title) & (df.length == song_df.duration) & \\n (df.artist == song_df.artist_name), how='left').dropDuplicates()\\n songplays_table = songplays_table.withColumn(\\\"id\\\", monotonically_increasing_id())\\n windowSpec = Window.orderBy(\\\"id\\\")\\n songplays_table.withColumn(\\\"songplay_id\\\", row_number().over(windowSpec))\\n songplays_table = songplays_table.selectExpr(\\\"songplay_id\\\", \\\"start_time\\\", \\n \\\"userId as user_id\\\", \\\"level\\\", \\\"song_id\\\", \\\"artist_id\\\", \\\"sessionId as session_id\\\",\\n \\\"location\\\", \\\"userAgent as user_agent\\\", \\\"year(start_time) as year\\\",\\n \\\"month(start_time) as month\\\")\\n\\n # output filepath to songplays table\\n songplays_table_path = output_data + \\\"songplays_table.parquet\\\"\\n \\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.partitionBy(\\\"year\\\", \\\"month\\\").mode(\\\"overwrite\\\") \\\\\\n .parquet(songplays_table_path)\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = input_data + \\\"log-data/*/*/*.json\\\"\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n \\n # filter by actions for song plays\\n # rename the columns as per requirements\\n df = df.filter(\\\"page='NextSong'\\\")\\\\\\n .withColumnRenamed(\\\"userId\\\", \\\"user_id\\\")\\\\\\n .withColumnRenamed(\\\"firstName\\\", \\\"first_name\\\")\\\\\\n .withColumnRenamed(\\\"lastName\\\", \\\"last_name\\\")\\\\\\n .withColumnRenamed(\\\"sessionId\\\", \\\"session_id\\\")\\\\\\n .withColumnRenamed(\\\"userAgent\\\", \\\"user_agent\\\")\\n\\n # extract columns for users table \\n users_table = df.select(\\\"user_id\\\", \\\"first_name\\\", \\\"last_name\\\", \\\"gender\\\", \\\"level\\\")\\n \\n # write users table to parquet files\\n file_name = output_data + \\\"users.parquet\\\"\\n users_table.write.parquet(file_name)\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = F.udf(lambda x: int(int(x)/1000))\\n df = df.withColumn(\\\"timestamp\\\", get_timestamp(df.ts))\\\\\\n .withColumn(\\\"datetime\\\", F.from_unixtime(\\\"timestamp\\\", \\\"MM-dd-yyyy HH:mm:ss\\\"))\\\\\\n .withColumn(\\\"start_time\\\", F.to_timestamp(\\\"datetime\\\", \\\"MM-dd-yyyy HH:mm:ss\\\"))\\\\\\n .withColumn(\\\"month\\\", F.month(\\\"start_time\\\"))\\\\\\n .withColumn(\\\"year\\\", F.year(\\\"start_time\\\"))\\\\\\n .withColumn(\\\"week\\\", F.weekofyear(\\\"start_time\\\"))\\\\\\n .withColumn(\\\"day\\\", F.dayofmonth(\\\"start_time\\\"))\\\\\\n .withColumn(\\\"weekday\\\", F.dayofweek(\\\"start_time\\\"))\\\\\\n .withColumn(\\\"hour\\\", F.hour(\\\"start_time\\\"))\\n \\n # extract columns to create time table\\n time_table = df.select(\\\"start_time\\\", \\\"month\\\", \\\"year\\\", \\\"week\\\", \\\"day\\\", \\\"weekday\\\", \\\"hour\\\")\\n \\n # write time table to parquet files partitioned by year and month\\n file_name = output_data + \\\"time.parquet\\\"\\n time_table.write.partitionBy([\\\"year\\\", \\\"month\\\"]).parquet(file_name)\\n\\n # read in song data to use for songplays table\\n file_name = output_data + \\\"songs.parquet\\\"\\n songs_df = spark.read.parquet(file_name)\\n\\n # Create views to perform sql query\\n songs_df.createOrReplaceTempView(\\\"songs_data\\\")\\n df.createOrReplaceTempView(\\\"logs_data\\\")\\n\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT start_time, user_id, level, song_id, artist_id,\\n session_id, location, user_agent, logs.year, month\\n FROM logs_data as logs\\n LEFT OUTER JOIN songs_data as songs\\n ON logs.song = songs.title\\n AND logs.length = songs.duration\\n \\\"\\\"\\\")\\n\\n # Create a column songplays_id and assign it values using monotonically_increasing_id method\\n songplays_table = songplays_table.withColumn(\\\"songplays_id\\\", F.monotonically_increasing_id())\\n\\n # write songplays table to parquet files partitioned by year and month\\n file_name = output_data + \\\"songplays.parquet\\\"\\n songplays_table.write.partitionBy([\\\"year\\\", \\\"month\\\"]).parquet(file_name)\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = f'{input_data}/log_data/*.json'\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n \\n # filter by actions for song plays\\n df = df.filter(df.page =='NextSong')\\n\\n # extract columns for users table \\n user_table = df.select([\\\"userId\\\", \\\"firstname\\\", \\\"lastname\\\", \\\"gender\\\", \\\"level\\\"]).where(df[\\\"userId\\\"].isNotNull())\\n \\n # write users table to parquet files\\n user_data_out = f'{output_data}/user_table/user_table.parquet'\\n user_table.write.mode('overwrite').parquet(user_data_out)\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = F.udf(lambda x: datetime.fromtimestamp( (x/1000.0) ), T.TimestampType()) \\n df = df.withColumn(\\\"timestamp\\\", get_timestamp(df.ts))\\n \\n # extract columns to create time table\\n time_table = df.select(['timestamp']).dropDuplicates()\\n time_table = time_table.withColumn(\\\"hour\\\", hour(time_table[\\\"timestamp\\\"]))\\n time_table = time_table.withColumn(\\\"day\\\", dayofyear(time_table[\\\"timestamp\\\"]))\\n time_table = time_table.withColumn(\\\"week\\\", weekofyear(time_table[\\\"timestamp\\\"]))\\n time_table = time_table.withColumn(\\\"month\\\", month(time_table[\\\"timestamp\\\"]))\\n time_table = time_table.withColumn(\\\"year\\\", year(time_table[\\\"timestamp\\\"]))\\n time_table = time_table.withColumn(\\\"weekday\\\", dayofweek(time_table[\\\"timestamp\\\"]))\\n\\n \\n # write time table to parquet files partitioned by year and month\\n time_data_out = f'{output_data}/time_table/time_table.parquet'\\n time_table.write.mode('overwrite').partitionBy('year','month').parquet(time_data_out)\\n\\n # read in song data to use for songplays table\\n song_data = f'{input_data}/song_data/*/*/*/*.json'\\n sdf = spark.read.json(song_data)\\n sdf.createOrReplaceTempView(\\\"song_df_table\\\")\\n \\n # Adding month and year column to log data read and preparing log data table\\n df = df.withColumn(\\\"month\\\", month(df[\\\"timestamp\\\"]))\\n df = df.withColumn(\\\"year\\\", year(df[\\\"timestamp\\\"]))\\n df.createOrReplaceTempView(\\\"log_df_table\\\")\\n \\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = spark.sql(\\\"\\\"\\\"\\n SELECT ldf.timestamp as start_time,\\n ldf.userid as user_id,\\n ldf.level,\\n sdf.song_id,\\n sdf.artist_id,\\n ldf.sessionid as session_id,\\n ldf.location,\\n ldf.useragent as user_agent,\\n ldf.month,\\n ldf.year\\n FROM log_df_table ldf\\n JOIN song_df_table sdf\\n ON (ldf.song = sdf.title) AND (ldf.artist = sdf.artist_name) AND (ldf.length = sdf.duration)\\n WHERE ldf.page = 'NextSong' and ldf.userid is not null\\n \\\"\\\"\\\")\\n \\n # adding the songplay_id column\\n window = Window.orderBy(F.col('start_time'))\\n songplays_table = songplays_table.withColumn('songplay_id', F.row_number().over(window))\\n songplays_table.select('songplay_id', 'start_time', 'user_id', 'level', 'song_id', 'artist_id', 'session_id', 'location', 'user_agent', 'month', 'year').show()\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_data_out = f'{output_data}/songplays_table/songplays_table.parquet'\\n songplays_table.write.mode('overwrite').partitionBy('year','month').parquet(songplays_data_out)\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = input_data + \\\"log_data/*.json\\\"\\n\\n # read log data file\\n df = spark.read.json(\\\"data/log_data/*.json\\\").dropDuplicates()\\n \\n # filter by NextSong actions for song plays\\n df = df.filter('page = \\\"NextSong\\\"')\\n\\n # extract columns for users table \\n artists_table = df.select(['userId', 'firstName', 'lastName', 'gender', 'level']) \\n \\n # write users table to parquet files\\n artists_table.write.parquet(output_data + \\\"UserTable.parquet\\\")\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = udf( lambda x: datetime.fromtimestamp(x / 1000).strftime('%Y-%m-%d %H:%M:%S'))\\n df = df.withColumn(\\\"time_stamp\\\", get_time_stamp(dfLog.ts))\\n \\n # extract columns to create time table\\n time_table = dfL.select('ts', hour('time_stamp').alias('hour'), dayofmonth('time_stamp').alias('day'), weekofyear('time_stamp').alias('week')\\n , month('time_stamp').alias('month'), year('time_stamp').alias('year'), date_format('time_stamp', 'EEEE').alias('weekday'))\\n \\n # write time table to parquet files partitioned by year and month\\n time_table.write.partitionBy(\\\"year\\\", \\\"month\\\").parquet(output_data + \\\"SongTable.parquet\\\")\\n\\n # read in song data to use for songplays table\\n song_df = songs_table\\n\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = song_df.join(dfLog).where((artist_and_song.title == dfLog.song) & \\n (artist_and_song.artist_name == dfLog.artist) & \\n (artist_and_song.duration == dfLog.length)).select('ts', 'userid', 'level', \\\\\\n 'song_id', 'artist_id','sessionid', \\\\\\n 'location', 'useragent')\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.join(time_table.select('ts', 'year', 'month')).where(songplays_table.ts == time_table.ts).write.partitionBy(\\\"year\\\", \\\"month\\\").parquet(output_data + \\\"songplaysTable.parquet\\\")\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = os.path.join(input_data, 'log_data', '*', '*', '*')\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n \\n # filter by actions for song plays\\n df = df.filter(col(\\\"page\\\") == \\\"NextSong\\\")\\n df.createOrReplaceTempView(\\\"songplays\\\")\\n\\n # extract columns for users table \\n users_table = spark.sql(\\\"\\\"\\\"\\n SELECT \\n DISTINCT(userId) AS user_id, \\n firstName AS first_name, \\n lastName AS last_name, \\n gender, \\n level\\n FROM songplays\\n \\\"\\\"\\\")\\n \\n # write users table to parquet files\\n users_table_path = os.path.join(output_data, \\\"users_table.parquet\\\")\\n (users_table.\\n write.\\n mode(\\\"overwrite\\\").\\n parquet(users_table_path))\\n print(f\\\"Stored users table at {users_table_path}\\\")\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = udf(lambda x: pd.Timestamp(x, unit = \\\"ms\\\"), TimestampType())\\n df = df.withColumn(\\\"timestamp\\\", get_timestamp(\\\"ts\\\"))\\n \\n # create datetime column from original timestamp column\\n get_datetime = udf(lambda x: pd.Timestamp(x, unit = \\\"ms\\\"), TimestampType())\\n df = df.withColumn(\\\"datetime\\\", get_datetime(\\\"ts\\\"))\\n df.createOrReplaceTempView(\\\"log_table\\\")\\n # extract columns to create time table\\n time_table = spark.sql(\\\"\\\"\\\"\\n SELECT \\n DISTINCT(timestamp) AS start_time, \\n HOUR(timestamp) AS hour,\\n day(timestamp) AS day,\\n weekofyear(timestamp) AS week,\\n month(timestamp) AS month,\\n year(timestamp) AS year,\\n dayofweek(timestamp) AS weekday\\n FROM log_table\\n \\\"\\\"\\\")\\n \\n # write time table to parquet files partitioned by year and month\\n time_table_path = os.path.join(output_data, \\\"time_table.parquet\\\")\\n (time_table.\\n write.\\n mode(\\\"overwrite\\\").\\n partitionBy(\\\"year\\\", \\\"month\\\").\\n parquet(time_table_path))\\n print(f\\\"Stored time table at {time_table_path}\\\")\\n\\n # read in song data to use for songplays table\\n song_df_path = os.path.join(input_data, \\\"song_data\\\", \\\"*\\\", \\\"*\\\", \\\"*\\\")\\n song_df = spark.read.json(song_df_path).alias(\\\"song_df\\\")\\n df = df.alias(\\\"df\\\")\\n \\n joined_df = df.join(\\n song_df, \\n col('df.artist') == col('song_df.artist_name'), \\n 'inner',\\n )\\n\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = joined_df.select(\\n col(\\\"timestamp\\\").alias(\\\"start_time\\\"),\\n col(\\\"userId\\\").alias(\\\"user_id\\\"),\\n col(\\\"level\\\").alias(\\\"level\\\"),\\n col(\\\"song_id\\\").alias(\\\"song_id\\\"),\\n col(\\\"artist_id\\\").alias(\\\"artist_id\\\"),\\n col(\\\"sessionId\\\").alias(\\\"session_id\\\"),\\n col(\\\"location\\\").alias(\\\"location\\\"),\\n col(\\\"userAgent\\\").alias(\\\"user_agent\\\")\\n ).withColumn('songplay_id', monotonically_increasing_id())\\n \\n # Add year and month to enable partitioning\\n songplays_table = (songplays_table.\\n withColumn('year', year(songplays_table.start_time)).\\n withColumn('month', month(songplays_table.start_time)))\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table_path= os.path.join(output_data, \\\"songplays_table.parquet\\\")\\n (songplays_table.\\n write.\\n mode(\\\"overwrite\\\").\\n partitionBy(\\\"year\\\", \\\"month\\\").\\n parquet(songplays_table_path))\\n print(f\\\"Stored songplays table at {songplays_table_path}\\\")\",\n \"def process_log_data(spark, input_data, output_data, mode=\\\"overwrite\\\"):\\n # get filepath to log data file\\n log_data = input_data + \\\"log_data/*.json\\\"\\n # read log data file\\n print(\\\"reading event logs from {}\\\".format(log_data))\\n df = spark.read.json(log_data)\\n\\n # filter by actions for song plays\\n df = df.filter(F.col('page') == 'NextSong')\\n df = df.withColumn(\\n 'userId', F.col('userId').cast(LongType())\\n )\\n df = df.withColumn(\\n 'registration',\\n (F.round(F.col('registration')/1000)).cast(TimestampType())\\n )\\n df = df.withColumn(\\n 'ts',\\n (F.round(F.col('ts')/1000)).cast(TimestampType())\\n )\\n\\n # extract columns for users table\\n users_table = df.selectExpr(\\n 'userId AS user_id',\\n 'firstName AS first_name',\\n 'lastName AS last_name',\\n 'gender AS gender') \\\\\\n .dropDuplicates(['user_id'])\\n\\n # write users table to parquet files\\n users_path = output_data + 'star_schema/user_table'\\n print(\\\"Writing Users Table to {}\\\".format(users_path))\\n users_table.write \\\\\\n .mode(mode) \\\\\\n .partitionBy('user_id') \\\\\\n .parquet(users_path)\\n\\n # extract columns to create time table\\n time_table = df.selectExpr('ts AS start_time') \\\\\\n .dropDuplicates() \\\\\\n .orderBy('start_time', ascending=True) \\\\\\n .withColumn('hour', F.hour('start_time')) \\\\\\n .withColumn('day', F.dayofmonth('start_time')) \\\\\\n .withColumn('week', F.weekofyear('start_time')) \\\\\\n .withColumn('month', F.month('start_time')) \\\\\\n .withColumn('year', F.year('start_time')) \\\\\\n .withColumn('weekday', F.dayofweek('start_time'))\\n\\n # write time table to parquet files partitioned by year and month\\n times_path = output_data + 'star_schema/time_table'\\n print(\\\"Writing Time Table to {}\\\".format(times_path))\\n time_table.write \\\\\\n .mode(mode) \\\\\\n .partitionBy('year', 'month', 'day') \\\\\\n .parquet(times_path)\\n\\n # read in song data to use for songplays table)\\n songs_path = output_data + 'star_schema/song_table'\\n print(\\\"Reading Songs table for join query from {}\\\".format(songs_path))\\n song_table = spark.read.parquet(songs_path)\\n\\n # extract columns from joined song and log datasets to create songplays table\\n songplays_table = df.selectExpr(\\n 'ts as start_time',\\n 'userId as user_id',\\n 'level',\\n 'song', # join to song_id from songs_df\\n # artist_id # join from songs df\\n 'sessionId as session_id',\\n 'location',\\n 'userAgent as user_agent'\\n )\\n songplays_table = songplays_table \\\\\\n .withColumn('songplay_id', F.monotonically_increasing_id()) \\\\\\n .withColumn('songplay_year', F.year('start_time')) \\\\\\n .withColumn('month', F.month('start_time'))\\n songplays_table = songplays_table.join(\\n song_table,\\n song_table.title == songplays_table.song, how='left'\\n ).select([\\n 'songplay_id', 'start_time', 'songplay_year', 'month',\\n 'user_id', 'level', 'song_id', 'artist_id',\\n 'session_id', 'location', 'user_agent'\\n ]).withColumnRenamed('songplay_year', 'year')\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_path = output_data + 'star_schema/songplay_table'\\n print(\\\"Writing Songplays Table to {}\\\".format(songplays_path))\\n songplays_table.write \\\\\\n .mode(mode) \\\\\\n .partitionBy('year', 'month') \\\\\\n .parquet(songplays_path)\",\n \"def process_log_data(spark, input_data, output_data):\\n # define json structure\\n logdata_schema = StructType([\\n StructField(\\\"artist\\\", StringType(), True),\\n StructField(\\\"auth\\\", StringType(), True),\\n StructField(\\\"firstName\\\", StringType(), True),\\n StructField(\\\"gender\\\", StringType(), True),\\n StructField(\\\"itemInSession\\\", LongType(), True),\\n StructField(\\\"lastName\\\", StringType(), True),\\n StructField(\\\"length\\\", DoubleType(), True),\\n StructField(\\\"level\\\", StringType(), True),\\n StructField(\\\"location\\\", StringType(), True),\\n StructField(\\\"method\\\", StringType(), True),\\n StructField(\\\"page\\\", StringType(), True),\\n StructField(\\\"registration\\\", DoubleType(), True),\\n StructField(\\\"sessionId\\\", LongType(), True),\\n StructField(\\\"song\\\", StringType(), True),\\n StructField(\\\"status\\\", LongType(), True),\\n StructField(\\\"ts\\\", LongType(), True),\\n StructField(\\\"userAgent\\\", StringType(), True),\\n StructField(\\\"userId\\\", StringType(), True),\\n ])\\n # get filepath to log data file\\n log_data = os.path.join(input_data, 'log_data/*/*/*.json')\\n\\n # read log data file\\n df = spark.read.json(log_data, schema=logdata_schema)\\n\\n # filter by actions for song plays\\n df = df.filter(col(\\\"page\\\") == 'NextSong')\\n\\n # extract columns for users table \\n users_table = df.select(col(\\\"userId\\\").alias(\\\"user_id\\\"),col(\\\"firstName\\\").alias(\\\"first_name\\\"),\\n col(\\\"lastName\\\").alias(\\\"last_name\\\"),\\\"gender\\\",\\\"level\\\")\\n \\n # write users table to parquet files\\n users_table.write.parquet(output_data + \\\"users\\\")\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = udf(lambda x: datetime.fromtimestamp((x/1000)), TimestampType())\\n df = df.withColumn(\\\"timestamp\\\", get_timestamp(df.ts))\\n \\n # create datetime column from original timestamp column\\n get_datetime = udf(lambda x: datetime.fromtimestamp(x/1000).strftime('%Y-%m-%d %H:%M:%S'))\\n df = df.withColumn(\\\"datetime\\\", get_datetime(df.ts))\\n \\n # extract columns to create time table\\n time_table = df.select(col(\\\"timestamp\\\").alias(\\\"start_time\\\"),\\n hour(col(\\\"timestamp\\\")).alias(\\\"hour\\\"),\\n dayofmonth(col(\\\"timestamp\\\")).alias(\\\"day\\\"), \\n weekofyear(col(\\\"timestamp\\\")).alias(\\\"week\\\"), \\n month(col(\\\"timestamp\\\")).alias(\\\"month\\\"),\\n year(col(\\\"timestamp\\\")).alias(\\\"year\\\"))\\n \\n # write time table to parquet files partitioned by year and month\\n time_table.write.partitionBy(\\\"year\\\", \\\"month\\\").parquet(output_data + \\\"time\\\")\\n\\n # read in song data to use for songplays table\\n song_data = os.path.join(input_data, \\\"song_data/A/A/A/TRAAAAK128F9318786.json\\\")\\n song_df = spark.read.json(song_data)\\n\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = song_df.join(df, \\n song_df.artist_name==df.artist).withColumn(\\\"songplay_id\\\", \\n monotonically_increasing_id()).withColumn(\\\"start_time\\\", get_datetime(df.ts)).select(\\\"songplay_id\\\",\\n \\\"start_time\\\", \\n col(\\\"userId\\\").alias(\\\"user_id\\\"),\\n \\\"level\\\",\\n \\\"song_id\\\",\\n \\\"artist_id\\\",\\n col(\\\"sessionId\\\").alias(\\\"session_id\\\"),\\n col(\\\"artist_location\\\").alias(\\\"location\\\"),\\n \\\"userAgent\\\",\\n month(col(\\\"start_time\\\")).alias(\\\"month\\\"),\\n year(col(\\\"start_time\\\")).alias(\\\"year\\\"))\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.partitionBy(\\\"year\\\", \\\"month\\\").parquet(output_data + \\\"songplays\\\")\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n # For working in the workspace: log_data = os.path.join(input_data, \\\"log-data/*.json\\\")\\n log_data = os.path.join(input_data, \\\"log-data/*/*/*.json\\\")\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n\\n # filter by actions for song plays\\n df = df.filter(df.page == 'NextSong')\\n\\n # rename the columns in df\\n df = (df.withColumnRenamed('userId', 'user_id')\\n .withColumnRenamed('firstName', 'first_name')\\n .withColumnRenamed('lastName', 'last_name')\\n .withColumnRenamed('itemInSession', 'item_in_session')\\n .withColumnRenamed('sessionId', 'session_id')\\n .withColumnRenamed('userAgent', 'user_agent'))\\n\\n # extract columns for users table\\n users_table = df.select('user_id', 'first_name', 'last_name', 'gender', 'level').distinct()\\n\\n # write users table to parquet files\\n users_table.write.parquet(output_data + 'users', mode='overwrite')\\n\\n # create timestamp column from original timestamp column\\n # default type is string for UDFs, so we need to switch that by specifying the correct type\\n get_timestamp = udf(lambda x: datetime.fromtimestamp(x/1000.0), T.TimestampType())\\n df = df.withColumn('start_time', get_timestamp(df.ts))\\n\\n # extract columns to create time table\\n time_table = df.select('start_time',\\n hour(col('start_time')).alias('hour'),\\n dayofmonth(col('start_time')).alias('day'),\\n weekofyear(col('start_time')).alias('week'),\\n month(col('start_time')).alias('month'),\\n year(col('start_time')).alias('year'),\\n date_format(col('start_time'), 'EEEE').alias('weekday'))\\n\\n # write time table to parquet files partitioned by year and month\\n time_table.write.partitionBy('year', 'month').parquet(output_data + 'time', mode='overwrite')\\n\\n # read in song data to use for songplays table\\n song_df = spark.read.parquet(output_data + 'songs/year=*/artist_id=*/*.parquet')\\n artist_df = spark.read.parquet(output_data + 'artists/*.parquet')\\n\\n # extract columns from joined song and log datasets to create songplays table\\n songplays_table = df.join(song_df, (df.song == song_df.title) & (df.length == song_df.duration)).join(artist_df, df.artist == artist_df.artist_name).join(time_table, ['start_time'])\\n\\n # create the songplay_id column\\n songplays_table = songplays_table.withColumn('songplay_id', monotonically_increasing_id())\\n\\n # select the columns of interest\\n songplays_table = songplays_table.select('songplay_id', 'start_time', 'user_id', 'level', 'song_id', 'artist_id', 'session_id', 'location', 'user_agent', 'year', 'month')\\n\\n # write songplays table to parquet files partitioned by year and month (I think this is a copy paste error because year and month aren't listed as required cols)\\n songplays_table.write.partitionBy('year', 'month').parquet(output_data + 'songplays', mode='overwrite')\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = input_data + 'log_data/*/*/*.json'\\n\\n # read log data file\\n df = df = spark.read.json(log_data)\\n\\n # filter by actions for song plays\\n df = df[df.page == 'NextSong']\\n\\n # extract columns for users table\\n users_table = df.select('userId', 'firstName', 'lastName', 'gender', 'level').drop_duplicates()\\n\\n # write users table to parquet files\\n users_table.write.format(\\\"parquet\\\").mode(\\\"overwrite\\\").save(output_data + 'users/user_data.parquet')\\n\\n # create timestamp column from original timestamp column\\n df = df.withColumn('timestamp', F.to_timestamp(df.ts / 1000))\\n\\n # create datetime column from original timestamp column\\n df = df.withColumn('datetime', F.to_date(df.timestamp))\\n\\n # create uniqueId column for log_data\\n df = df.withColumn('uniqueId', monotonically_increasing_id())\\n\\n # write log data to temp view log_data_table\\n df.createOrReplaceTempView(\\\"log_data_table\\\")\\n\\n # extract columns to create time table\\n time_table = spark.sql(\\\"\\\"\\\"\\n select DISTINCT\\n timestamp\\n , datetime AS start_time\\n , hour(timestamp) AS hour\\n , day(timestamp) AS day\\n , weekofyear(timestamp) AS week\\n , month(timestamp) AS month\\n , year(timestamp) AS year\\n , weekday(timestamp) AS weekday\\n from log_data_table\\n \\\"\\\"\\\")\\n\\n # write time table to parquet files partitioned by year and month\\n time_table.write.partitionBy(\\\"year\\\", \\\"month\\\").format(\\\"parquet\\\").mode(\\\"overwrite\\\").save(\\n output_data + 'time/time_data.parquet')\\n\\n # extract columns from joined song and log datasets to create songplays table\\n songplays_table = songplay_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT\\n stg.uniqueId AS songplay_id,\\n stg.ts AS start_time,\\n month(stg.timestamp) AS month,\\n year(stg.timestamp) AS year,\\n stg.userId,\\n stg.level,\\n stg2.song_id,\\n stg2.artist_id,\\n stg.sessionId,\\n stg.location,\\n stg.userAgent\\n FROM log_data_table stg\\n LEFT JOIN song_data_table stg2\\n ON stg.artist = stg2.artist_name\\n AND stg.song = stg2.title\\n AND stg.length = stg2.duration\\n WHERE stg.userId IS NOT NULL\\n \\\"\\\"\\\")\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.partitionBy(\\\"year\\\", \\\"month\\\").format(\\\"parquet\\\").mode(\\\"overwrite\\\").save(\\n output_data + 'songplays/songplays_data.parquet')\",\n \"def process_log_data(spark, input_data, output_data):\\n\\n print(\\\"Read log data\\\")\\n # read log data file\\n df_log_data = spark.read.json(input_data + \\\"log-data/*/*/*.json\\\")\\n\\n # filter by actions for song plays\\n df_log_data = df_log_data[df_log_data['page']=='NextSong']\\n\\n # extract columns for users table \\n users_table = df_log_data[['userId', 'firstName', 'lastName', 'gender', 'level']].drop_duplicates()\\n\\n \\n print(\\\"Write...\\\")\\n # write users table to parquet files\\n users_table.write.save(path=output_data + 'users_table',\\n format='parquet',\\n mode='overwrite'\\n )\\n\\n df_log_data = df_log_data.withColumn('timestamp', F.from_unixtime(df_log_data['ts']/1000))\\\\\\n .withColumn('hour', F.hour(F.col('timestamp')))\\\\\\n .withColumn('day', F.dayofmonth(F.col('timestamp')))\\\\\\n .withColumn('month', F.month(F.col('timestamp')))\\\\\\n .withColumn('year', F.year(F.col('timestamp')))\\\\\\n .withColumn('weekofyear', F.weekofyear(F.col('timestamp')))\\\\\\n .withColumn('dayofweek', F.dayofweek(F.col('timestamp')))\\n\\n # extract columns to create time table\\n time_table = df_log_data[['timestamp','hour','day','month','year','weekofyear','dayofweek',]].drop_duplicates()\\n\\n print(\\\"Write...\\\")\\n # write time table to parquet files partitioned by year and month\\n time_table.write.save(path=output_data + 'time_table',\\n format='parquet',\\n mode='overwrite',\\n partitionBy=['year','month'] )\\n\\n # read in song data to use for songplays table\\n df_song = spark.read.json(input_data + \\\"song_data/*/*/*/*.json\\\", schema=build_song_schema())\\n\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = df_log_data.join(df_song, \\n on = (df_song['title'] == df_log_data['song']) & \\\\\\n (df_song['artist_name'] == df_log_data['artist']) & \\\\\\n (df_song['duration'] == df_log_data['length']) \\n )\\n\\n print(\\\"Write...\\\")\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.save(path=output_data + 'songplays_table',\\n format='parquet',\\n mode='overwrite',\\n partitionBy=['year','month'] )\",\n \"def process_log_data(spark, input_data, output_data):\\n \\n # get filepath to log data file\\n log_data = input_data + 'log_data/*.json'\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n \\n # filter by actions for song plays\\n df = df.filter(df.page == 'NextSong')\\n \\n # create view for users table\\n df.createOrReplaceTempView(\\\"users\\\") \\n\\n # extract columns for users table, Adding Distinct and Not null to user_id as it is the primary key\\n users_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT userId as user_id, \\n firstName as first_name,\\n lastName as last_name,\\n gender as gender,\\n level as level\\n FROM users\\n WHERE userId IS NOT NULL\\n \\\"\\\"\\\")\\n \\n # write users table to parquet files\\n users_table.write.mode('overwrite').parquet(output_data+'users_table/') \\n \\n # create view for time table\\n df.createOrReplaceTempView(\\\"time\\\") \\n \\n # extract columns to create time table, Adding Not null to ts as it is the primary key, its very unlikely that ts will be \\n # same for two rows as its time in miliseconds. Much easier and striaghtforward to extract day, hour, week etc. from timestamp\\n # through SQL then converting timestamp in Dataframe to datetime and then performing extraction \\n time_table = spark.sql(\\\"\\\"\\\"\\n SELECT \\n timestamp_data.start_time_prev as start_time,\\n hour(timestamp_data.start_time_prev) as hour,\\n dayofmonth(timestamp_data.start_time_prev) as day,\\n weekofyear(timestamp_data.start_time_prev) as week,\\n month(timestamp_data.start_time_prev) as month,\\n year(timestamp_data.start_time_prev) as year,\\n dayofweek(timestamp_data.start_time_prev) as weekday\\n FROM\\n (SELECT to_timestamp(ts/1000) as start_time_prev\\n FROM time\\n WHERE ts IS NOT NULL\\n ) timestamp_data\\n \\\"\\\"\\\")\\n \\n # write time table to parquet files partitioned by year and month\\n time_table.write.mode('overwrite').partitionBy(\\\"year\\\", \\\"month\\\").parquet(output_data+'time_table/') \\n \\n # get filepath to song data file\\n song_data = input_data + 'song_data/*/*/*/*.json'\\n \\n # read song data file\\n df = spark.read.json(song_data)\\n \\n # create view for song data\\n df.createOrReplaceTempView(\\\"song_data\\\")\\n \\n # create view for songplays table \\n df.createOrReplaceTempView(\\\"songplays\\\")\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = input_data + \\\"log_data/*/*/*.json\\\"\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n \\n # print out the schema in tree format\\n print(\\\"---------- Print out the schema of log dataset in tree format: ----------\\\")\\n df.printSchema()\\n \\n # filter by actions for song plays\\n df = df.filter(df.page == \\\"NextSong\\\")\\n\\n # extract columns for users table \\n # users attributes: user_id, first_name, last_name, gender, level\\n users_table = df.select(\\\"userId\\\", \\\"firstName\\\", \\\"lastName\\\", \\\"gender\\\", \\\"level\\\").distinct()\\n \\n # show first 10 rows in users table\\n print(\\\" ---------- Show first 10 rows of users table ----------\\\")\\n users_table.show(10)\\n \\n # write users table to parquet files\\n output_data_users = os.path.join(output_data_users, \\\"users_table.parquet\\\")\\n if path.exists(output_data_users):\\n users_table.write.parquet(path = output_data_users, \\n mode = \\\"overwrite\\\")\\n else:\\n users_table.write.parquet(path = output_data_users, \\n mode = \\\"append\\\")\\n \\n # read parquet file and check the first 10 rows of partitioned parquet dataframes\\n df_users_parquet = spark.read.parquet(\\\"users_table.parquet\\\")\\n print(\\\" ---------- Show first 10 rows of users table parquet file ----------\\\")\\n df_users_parquet.show(10)\\n\\n # create datetime column from original timestamp column\\n # divide timestamp by 1000 to convert from milliseconds to seconds\\n get_datetime = udf(lambda x: datetime.fromtimestamp(x / 1000), TimestampType())\\n df = df.withColumn(\\\"start_time\\\", get_datetime(df.ts))\\n \\n # time table attributes: start_time, hour, day, week, month, year, weekday\\n get_hour = udf(lambda x: x.hour) \\n df = df.withColumn(\\\"hour\\\", get_hour(df.start_time)) # create hour column\\n \\n get_day = udf(lambda x: x.day)\\n df = df.withColumn(\\\"day\\\", get_day(df.start_time)) # create day column\\n \\n get_week = udf(lambda x: x.isocalendar()[1])\\n df = df.withColumn(\\\"week\\\", get_week(df.start_time)) # create week number column\\n \\n get_month = udf(lambda x: x.month)\\n df = df.withColumn(\\\"month\\\", get_month(df.start_time)) # create month column\\n \\n get_year = udf(lambda x: x.year)\\n df = df.withColumn(\\\"year\\\", get_year(df.start_time)) # create year column\\n \\n get_weekday = udf(lambda x: x.weekday())\\n df = df.withColumn(\\\"weekday\\\", get_weekday(df.start_time)) # create weekday column\\n \\n # extract columns to create time table\\n time_table = df.select(df.columns[-7:])\\n \\n # show first 10 rows of time table \\n print(\\\" ---------- Show first 10 rows of time table ----------\\\")\\n time_table.show(10)\\n\\n # write time table to parquet files partitioned by year and month\\n out_path_time = os.path.join(output_data, \\\"time_table.parquet\\\")\\n if path.exists(out_path_time):\\n time_table.write.parquet(path = out_path_time, \\n partitionBy = (\\\"year\\\", \\\"month\\\"),\\n mode = \\\"overwrite\\\")\\n else:\\n time_table.write.parquet(path = out_path_time, \\n partitionBy = (\\\"year\\\", \\\"month\\\"),\\n mode = \\\"append\\\")\\n\\n # read parquet file and check the first 10 rows of partitioned parquet dataframes\\n df_time_parquet = spark.read.parquet(\\\"time_table.parquet\\\")\\n print(\\\" ---------- Show first 10 rows of time table parquet file ----------\\\")\\n df_time_parquet.show(10)\\n\\n # read in song data to use for songplays table\\n song_df = spark.read.parquet(\\\"songs_table.parquet\\\")\\n \\n # inner join df with song_df by song's name\\n cond = [df.song == song_df.title]\\n df_join = df.join(song_df, cond, \\\"inner\\\")\\n \\n # extract columns from joined song and log datasets to create songplays table \\n # songplays attributes: songplay_id, start_time, user_id, level, song_id, \\n # artist_id, session_id, location, user_agent\\n songplays_table = df_join.select(\\\"start_time\\\", \\\"userId\\\", \\\"level\\\", \\\"song_id\\\", \\n \\\"artist_id\\\", \\\"sessionId\\\", \\\"location\\\", \\n \\\"userAgent\\\").distinct()\\n \\n # create songplay_id column with auto_increment\\n songplays_table.withColumn(\\\"songplay_id\\\", monotonically_increasing_id())\\n \\n # show first 10 rows of songplays table \\n print(\\\" ---------- Show first 10 rows of songplays table ----------\\\")\\n songplays_table.show(10)\\n \\n # append year and month column into songplays_table\\n songplays_table = songplays_table.withColumn(\\\"year\\\", get_year(df.start_time))\\n songplays_table = songplays_table.withColumn(\\\"month\\\", get_month(df.start_time))\\n \\n # write songplays table to parquet files partitioned by year and month\\n out_path_songplays = os.path.join(output_data, \\\"songplays_table.parquet\\\")\\n if path.exists(out_path_songplays):\\n songplays_table.write.parquet(path = out_path_songplays, \\n partitionBy = (\\\"year\\\", \\\"month\\\"),\\n mode = \\\"overwrite\\\")\\n else:\\n songplays_table.write.parquet(path = out_path_songplays, \\n partitionBy = (\\\"year\\\", \\\"month\\\"),\\n mode = \\\"append\\\")\",\n \"def process_log_data(spark, input_data, output_data):\\n\\n # get filepath to log data file\\n input_data = input_data+\\\"/log-data\\\"\\n\\n \\\"\\\"\\\"\\n log_data=[]\\n for x in os.walk(input_data):\\n for y in glob.glob(os.path.join(x[0], '*.json')):\\n log_data.append(y)\\n \\\"\\\"\\\"\\n \\n # read log data file\\n df = spark.read.json(input_data)\\n\\n # filter by actions for song plays\\n df=df.filter(col(\\\"page\\\")=='NextSong').withColumn(\\\"new_ts\\\", df[\\\"ts\\\"].cast(IntegerType())).drop(\\\"ts\\\").withColumnRenamed(\\\"new_ts\\\", \\\"ts\\\")\\n df.createOrReplaceTempView(\\\"staging_log_data\\\")\\n\\n # extract columns for users table\\n user_query = \\\" SELECT userid, firstName, lastName, gender, level \\\" \\\\\\n \\\" FROM staging_log_data \\\"\\n users_table = spark.sql(user_query)\\n \\n # write users table to parquet files\\n users_table.write.mode('overwrite').parquet(path=output_data+\\\"users\\\")\\n\\n df=df.filter(df['ts'].isNotNull())\\n time_table= df.select(from_unixtime(df['ts']/1000).alias('start_time'))\\n time_table=time_table.select(time_table['start_time'], \\\\\\n hour(time_table['start_time']).alias(\\\"hour\\\"), \\\\\\n dayofmonth(time_table['start_time']).alias(\\\"day\\\"), \\\\\\n weekofyear(time_table['start_time']).alias(\\\"week\\\"), \\\\\\n month(time_table['start_time']).alias(\\\"month\\\"), \\\\\\n year(time_table['start_time']).alias(\\\"year\\\"), \\\\\\n date_format(time_table['start_time'],'E').alias(\\\"DOW\\\"))\\n\\n # write time table to parquet files partitioned by year and month\\n time_table.write.mode('overwrite').partitionBy('year','month').parquet(path=output_data + \\\"time\\\")\\n\\n # read in song data to use for songplays table\\n songplay_query=\\\" Select DISTINCT monotonically_increasing_id() as songplay_id, \\\" \\\\\\n \\\" from_unixtime(ld.ts/1000) as start_time , \\\" \\\\\\n \\\" ld.userid as user_id, \\\" \\\\\\n \\\" ld.level as level,\\\"\\\\\\n \\\" sd.song_id as song_id,\\\" \\\\\\n \\\" sd.artist_id as artist_id,\\\" \\\\\\n \\\" ld.sessionid as session_id, \\\" \\\\\\n \\\" ld.location as location, \\\" \\\\\\n \\\" ld.useragent as user_agent, \\\" \\\\\\n \\\" t.year as year, \\\" \\\\\\n \\\" t.month as month \\\" \\\\\\n \\\" from staging_log_data ld, Staging_Song_Data sd, time t\\\" \\\\\\n \\\" Where ld.artist = sd.artist_name\\\" \\\\\\n \\\" and ld.song = sd.title \\\" \\\\\\n \\\" and from_unixtime(ld.ts/1000) = t.start_time \\\" \\n\\n # extract columns from joined song and log datasets to create songplays table\\n songplays_table = spark.sql(songplay_query)\\n #songplays_table = spark.sql(songplay_query).drop_duplicates('start_time','user_id','level','song_id','artist_id','location','user_agent')\\n\\n songplays_table.show()\\n \\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.mode('overwrite').partitionBy('year','month').parquet(path=output_data + \\\"songplays\\\")\",\n \"def process_log_data(spark, song_input_data, log_input_data, output_data):\\n # get filepath to log data file\\n log_data = log_input_data\\n\\n # read log data file\\n print(\\\"Reading in the log data...\\\")\\n log_df = spark.read.json(log_data)\\n \\n # filter by actions for song plays\\n print(\\\"Filtering by actions for song plays...\\\")\\n log_df = log_df.filter(log_df.page == 'NextSong')\\n\\n # extract columns for users table \\n print(\\\"Extracting columns for users table...\\\")\\n log_df.createOrReplaceTempView(\\\"users_table\\\")\\n users_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT userId AS user_id,\\n firstName AS first_name,\\n lastName AS last_name,\\n gender,\\n level\\n FROM users_table\\n ORDER BY last_name\\n \\\"\\\"\\\")\\n \\n print(\\\"Users table sample:\\\")\\n users_table.show(5, truncate=False)\\n \\n # write users table to parquet files\\n print(\\\"Writing users table to parquet files...\\\")\\n users_table.write.mode(\\\"overwrite\\\").parquet(output_data + \\\"users_table.parquet\\\")\\n\\n # create timestamp column from original timestamp column\\n print(\\\"Creating timestamp column...\\\")\\n @udf(pt.TimestampType())\\n def get_timestamp (ts):\\n return datetime.fromtimestamp(ts / 1000.0)\\n\\n log_df = log_df.withColumn(\\\"timestamp\\\", get_timestamp(\\\"ts\\\"))\\n log_df.show(5)\\n \\n # create datetime column from original timestamp column\\n print(\\\"Creating datetime column...\\\")\\n @udf(pt.StringType())\\n def get_datetime(ts):\\n return datetime.fromtimestamp(ts / 1000.0).strftime('%Y-%m-%d %H:%M:%S')\\n\\n log_df = log_df.withColumn(\\\"datetime\\\", get_datetime(\\\"ts\\\"))\\n log_df.show(5)\\n \\n # extract columns to create time table\\n print(\\\"Extracting columns for time table...\\\")\\n log_df.createOrReplaceTempView(\\\"time_table\\\")\\n time_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT datetime AS start_time,\\n hour(timestamp) AS hour,\\n day(timestamp) AS day,\\n weekofyear(timestamp) AS week,\\n month(timestamp) AS month,\\n year(timestamp) AS year,\\n dayofweek(timestamp) AS weekday\\n FROM time_table\\n ORDER BY start_time\\n \\\"\\\"\\\")\\n \\n print(\\\"Users table sample:\\\")\\n time_table.show(5, truncate=False)\\n \\n # write time table to parquet files partitioned by year and month\\n print(\\\"Writing time table to parquet files...\\\")\\n time_table.write.mode(\\\"overwrite\\\").partitionBy(\\\"year\\\", \\\"month\\\")\\\\\\n .parquet(output_data + \\\"time_table.parquet\\\")\\n\\n # read in song data to use for songplays table\\n song_df = spark.read.json(song_input_data)\\n\\n print(\\\"Joining log_data and song_data...\\\")\\n joined_df = log_df.join(song_df, (log_df.artist == song_df.artist_name) & (log_df.song == song_df.title))\\n\\n # extract columns from joined song and log datasets to create songplays table \\n print(\\\"Extracting columns from joined DF...\\\")\\n joined_df = joined_df.withColumn(\\\"songplay_id\\\", monotonically_increasing_id())\\n joined_df.createOrReplaceTempView(\\\"songplays_table\\\")\\n songplays_table = spark.sql(\\\"\\\"\\\"\\n SELECT songplay_id,\\n timestamp AS start_time,\\n month(timestamp) AS month,\\n year(timestamp) AS year,\\n userId AS user_id,\\n level,\\n song_id,\\n artist_id,\\n sessionId AS session_id,\\n location,\\n userAgent AS user_agent\\n FROM songplays_table\\n ORDER BY (user_id, session_id)\\n \\\"\\\"\\\")\\n\\n print(\\\"Song plays table sample:\\\")\\n songplays_table.show(5, truncate=False)\\n \\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.mode(\\\"overwrite\\\").partitionBy(\\\"year\\\", \\\"month\\\") \\\\\\n .parquet(output_data + \\\"songplays_table.parquet\\\")\",\n \"def process_log_data(spark, input_data, output_data):\\n # get filepath to log data file\\n log_data = \\\"{}/log_data/*/*/*\\\".format(input_data)\\n\\n # read log data file\\n df = spark.read.format(\\\"json\\\").load(log_data)\\n \\n # create timestamp column from original timestamp column\\n get_timestamp = udf(lambda x: datetime.fromtimestamp( (x/1000.0) ), T.TimestampType()) \\n df = df.withColumn(\\\"listening_datetime\\\", get_timestamp(df.ts))\\n \\n # Using the same udf to convert epoch ts into timestamp already. \\n #get_datetime = udf()\\n #df = \\n \\n # filter by actions for song plays\\n df = df.where(\\\"page == 'NextSong'\\\")\\n \\n # register dataframe df_log into the temp view\\n df.createOrReplaceTempView(\\\"df_log\\\")\\n # extract columns for users table \\n users_table = spark.sql(\\\"\\\"\\\"\\n select DISTINCT userId,\\n firstName,\\n lastName,\\n gender,\\n level\\n FROM df_log as e\\n \\\"\\\"\\\")\\n\\n \\n # write users table to parquet files\\n users_table.write.parquet('{}/dim_user.pq'.format(output_data))\\n\\n \\n \\n \\n # extract columns to create time table\\n time_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT listening_datetime as t_start_time,\\n hour(listening_datetime) as t_hourofday,\\n day(listening_datetime) as t_daynuminmonth,\\n weekofyear(listening_datetime) as t_weeknuminyear,\\n month(listening_datetime) as t_monthnuminyear,\\n year(listening_datetime) as t_yearnuminyear,\\n dayofweek(listening_datetime) as t_daynuminweek\\n\\n\\n FROM df_log as s\\n \\\"\\\"\\\")\\n \\n # write time table to parquet files partitioned by year and month\\n time_table.write.partitionBy('t_yearnuminyear', 't_monthnuminyear').parquet('{}/dim_time.pq'.format(output_data))\\n\\n # read in song data to use for songplays table\\n song_df = spark.read.parquet('data/analytics/dim_song.pq')\\n \\n # registering temp view for dim_time and df_song in order to join in the songplay \\n song_df.createOrReplaceTempView(\\\"df_song\\\")\\n time_table.createOrReplaceTempView(\\\"dim_time\\\")\\n\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT e.listening_datetime AS t_start_time,\\n userId as u_user_id,\\n level as u_level,\\n song_id as s_song_id,\\n artist_id as a_artist_id,\\n sessionId as sp_session_id,\\n location as sp_location,\\n userAgent as sp_user_agent,\\n t.t_yearnuminyear,\\n t.t_monthnuminyear\\n FROM df_log as e\\n JOIN df_song s\\n ON (e.artist = s.artist_name)\\n JOIN dim_time t\\n on t.t_start_time = e.listening_datetime\\n \\n \\\"\\\"\\\")\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.partitionBy('t_yearnuminyear', 't_monthnuminyear').parquet('{}/songplays.pq'.format(output_data))\",\n \"def main(input_filepath, output_filepath, data_type):\\n a = jsonCSV(input_filepath, os.path.join(output_filepath, data_type+'.csv'))\\n column_names = a.get_superset_column_names()\\n a.read_write(column_names)\\n\\n logger = logging.getLogger(__name__)\\n logger.info('transform log files into csv')\",\n \"def process_log_data(spark, input_data, output_data):\\n\\n # get filepath to log data file\\n log_data = os.path.join( input_data, \\\"log-data/*/*/*.json\\\")\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n\\n # filter by actions for song plays\\n df = df.filter(df.page == \\\"NextSong\\\")\\n \\n # USERS TABLE\\n # extract columns for users table\\n users_table = df.select(\\\"userId\\\",\\\"firstName\\\",\\\"lastName\\\",\\\"gender\\\",\\\"level\\\").dropDuplicates(['userId'])\\n \\n print( \\\"HERE users_table sample:\\\\n\\\")\\n users_table.show(5)\\n # write users table to parquet files\\n users_table.write.parquet(os.path.join(output_data, \\\"users/\\\") , mode=\\\"overwrite\\\")\\n\\n # TIME TABLE\\n # create timestamp column from original timestamp column\\n get_start_time = udf(lambda x: datetime.fromtimestamp(x / 1000.0).strftime('%Y-%m-%d %H:%M:%S'))\\n get_hour = udf(lambda x: datetime.fromtimestamp(x / 1000.0).hour)\\n get_day = udf(lambda x: datetime.fromtimestamp(x / 1000.0).day)\\n get_week = udf(lambda x: datetime.fromtimestamp(x / 1000.0).strftime('%W'))\\n get_month = udf(lambda x: datetime.fromtimestamp(x / 1000.0).month)\\n get_year = udf(lambda x: datetime.fromtimestamp(x / 1000.0).year)\\n get_weekday = udf(lambda x: datetime.fromtimestamp(x / 1000.0).strftime('%A'))\\n\\n df = df.withColumn('start_time', get_start_time(df['ts']))\\n df = df.withColumn('hour', get_hour(df['ts']))\\n df = df.withColumn('day', get_day(df['ts']))\\n df = df.withColumn('week', get_week(df['ts']))\\n df = df.withColumn('month', get_month(df['ts']))\\n df = df.withColumn('year', get_year(df['ts']))\\n df = df.withColumn('week_day', get_weekday(df['ts'])).dropDuplicates(['start_time'])\\n\\n df.createOrReplaceTempView(\\\"time_table\\\")\\n \\n time_columns = ['start_time', 'hour', 'day', 'week', 'month', 'year', 'week_day']\\n\\n # extract columns to create time table\\n time_table = spark.sql(\\\"\\\"\\\"\\n SELECT start_time, hour, day, week, month, year, week_day\\n FROM time_table\\n \\\"\\\"\\\").toDF(*time_columns)\\n \\n print( \\\"HERE time_table sample:\\\\n\\\")\\n time_table.show(5)\\n # write time table to parquet files partitioned by year and month\\n time_table.write.parquet(os.path.join(output_data, \\\"time_table/\\\"), mode='overwrite', partitionBy=[\\\"year\\\",\\\"month\\\"])\\n\\n # SONGPLAYS TABLE\\n # add monotonically increasing id column\\n df = df.withColumn('songplay_id', functions.monotonically_increasing_id())\\n df.createOrReplaceTempView(\\\"songplays_table\\\")\\n\\n # song df\\n song_data = os.path.join( input_data, \\\"song_data/*/*/*/*.json\\\")\\n song_df = spark.read.json(song_data).dropDuplicates()\\n song_df.createOrReplaceTempView(\\\"songs_table\\\")\\n\\n song_columns = ['songplay_id', 'start_time', 'userId', 'level', 'sessionId', 'location', 'userAgent', 'year', 'month',\\n 'length', 'song_id', 'artist_id', 'title', 'artist_name', 'duration']\\n\\n # extract columns to create time table\\n songplays_table = spark.sql(\\n \\\"\\\"\\\"\\n SELECT sp.songplay_id, sp.start_time, sp.userId, sp.level, sp.sessionId, sp.location, sp.userAgent, sp.year, \\n sp.month, sp.length, s.song_id, s.artist_id, s.title, s.artist_name, s.duration\\n FROM songplays_table AS sp \\n JOIN songs_table AS s ON sp.song = s.title AND sp.artist = s.artist_name AND sp.length = s.duration\\n \\\"\\\"\\\").toDF(*song_columns)\\n \\n print( \\\"HERE songplays_table sample:\\\\n\\\")\\n songplays_table.show(5)\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table.write.parquet(os.path.join(output_data, \\\"songplays/\\\"), mode=\\\"overwrite\\\", partitionBy=[\\\"year\\\",\\\"month\\\"])\",\n \"def process_log_data(spark, input_data, output_data):\\n \\n # get filepath to log data file\\n log_data = os.path.join(input_data,\\\"log_data/*/*/*.json\\\")\\n\\n\\n # read log data file\\n df = spark.read.json(log_data)\\n \\n # filter by actions for song plays\\n #df = \\n\\n # extract columns for users table \\n users_table = df['userId', 'firstName', 'lastName', 'gender', 'level'].dropDuplicates()\\n \\n # write users table to parquet files\\n users_table.write.parquet(os.path.join(output_data, 'users.parquet'), 'overwrite')\\n print(\\\"--- users.parquet completed ---\\\")\\n\\n # create timestamp column from original timestamp column\\n get_timestamp = udf(lambda x: datetime.fromtimestamp( (x/1000.0) ), T.TimestampType())\\n # create datetime column from original timestamp column\\n get_datetime = udf(lambda x: datetime.fromtimestamp(int(int(x)/1000)))\\n get_hour = udf(lambda x: x.hour, T.IntegerType()) \\n get_day = udf(lambda x: x.day, T.IntegerType()) \\n get_week = udf(lambda x: x.isocalendar()[1], T.IntegerType()) \\n get_month = udf(lambda x: x.month, T.IntegerType()) \\n get_year = udf(lambda x: x.year, T.IntegerType()) \\n get_weekday = udf(lambda x: x.weekday(), T.IntegerType()) \\n\\n df = df.withColumn(\\\"timestamp\\\", get_timestamp(df.ts))\\n df = df.withColumn('start_time', get_datetime(df.ts))\\n df = df.withColumn(\\\"hour\\\", get_hour(df.timestamp))\\n df = df.withColumn(\\\"day\\\", get_day(df.timestamp))\\n df = df.withColumn(\\\"week\\\", get_week(df.timestamp))\\n df = df.withColumn(\\\"month\\\", get_month(df.timestamp))\\n df = df.withColumn(\\\"year\\\", get_year(df.timestamp))\\n df = df.withColumn(\\\"weekday\\\", get_weekday(df.timestamp))\\n \\n \\n # extract columns to create time table\\n time_columns = ['start_time', 'hour', 'day', 'week', 'month', 'year', 'weekday'] \\n \\n # write time table to parquet files partitioned by year and month\\n time_table = df[time_columns]\\n \\n # write time table to parquet files partitioned by year and month\\n time_table.write.partitionBy('year', 'month').parquet(os.path.join(output_data, 'time.parquet'), 'overwrite')\\n print(\\\"--- time.parquet completed ---\\\")\\n \\n # read in song data to use for songplays table\\n df_songs = spark.read.parquet(os.path.join(output_data, 'songs.parquet'))\\n \\n df_songplays = df_songs.join(df, (df_songs.title == df.song)).where(df.page == 'NextSong').orderBy(df.timestamp)\\n # extract columns from joined song and log datasets to create songplays table \\n songplays_table = df_songplays['timestamp', 'userId', 'level', 'song_id', 'artist_id', 'sessionId', 'location', 'userAgent']\\n songplays_table.select(monotonically_increasing_id().alias('songplay_id')).collect()\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table\\\\\\n .withColumn(\\\"year\\\", get_year(songplays_table.timestamp))\\\\\\n .withColumn(\\\"month\\\", get_month(songplays_table.timestamp))\\\\\\n .write\\\\\\n .partitionBy('year', 'month')\\\\\\n .parquet(os.path.join(output_data, 'songplays.parquet'), 'overwrite')\\n \\n print(\\\"--- songplays.parquet completed ---\\\")\\n print(\\\"*** process_log_data completed ***\\\\n\\\\nEND\\\")\",\n \"def process_song_data(spark, input_data, output_data):\\n \\n # get filepath to all json file of song_data in S3 bucket\\n song_data = input_data + \\\"song_data/*/*/*/*.json\\\"\\n \\n # read song data file\\n df = spark.read.json(song_data)\\n \\n # print out the schema in tree format\\n print(\\\"---------- Print out the schema of song dataset in tree format: ----------\\\")\\n df.printSchema()\\n\\n # extract columns to create songs table\\n # songs table attributes: song_id, title, artist_id, year, duration\\n songs_table = df.select(\\\"song_id\\\", \\\"title\\\", \\\"artist_id\\\", \\\"year\\\", \\\"duration\\\")\\n # show first 10 rows in songs_table\\n print(\\\" ---------- Show first 10 rows of songs table ----------\\\")\\n songs_table.show(10)\\n \\n # write songs table to parquet files partitioned by year and artist\\n out_path_songs = os.path.join(output_data, \\\"songs_table.parquet\\\")\\n if path.exists(out_path_songs):\\n songs_table.write.parquet(path = out_path_songs, \\n partitionBy = (\\\"year\\\", \\\"artist_id\\\"),\\n mode = \\\"overwrite\\\")\\n else:\\n songs_table.write.parquet(path = out_path_songs, \\n partitionBy = (\\\"year\\\", \\\"artist_id\\\"),\\n mode = \\\"append\\\")\\n \\n # read parquet file and check the first 10 rows of partitioned parquet dataframes\\n df_songs_parquet = spark.read.parquet(\\\"songs_table.parquet\\\")\\n print(\\\" ---------- Show first 10 rows of songs table parquet file ----------\\\")\\n df_songs_parquet.show(10)\\n\\n # extract columns to create artists table\\n # artists table attributes: artist_id, name, location, lattitude, longitude\\n artists_table = df.select(\\\"artist_id\\\", \\\"artist_name\\\", \\\"artist_location\\\", \\n \\\"artist_latitude\\\", \\\"artist_longitude\\\")\\n # show first 10 rows in artists_table\\n print(\\\" ---------- Show first 10 rows of artists table ----------\\\")\\n artists_table.show(10)\\n \\n # write artists table to parquet files\\n out_path_artists = os.path.join(output_data, \\\"artists_table.parquet\\\")\\n if path.exists(out_path_artists):\\n artists_table.write.parquet(path = out_path_artists, \\n mode = \\\"overwrite\\\")\\n else:\\n artists_table.write.parquet(path = out_path_artists, \\n mode = \\\"append\\\")\\n \\n # read parquet file and check the first 10 rows of partitioned parquet dataframes\\n df_artists_parquet = spark.read.parquet(\\\"artists_table.parquet\\\")\\n print(\\\" ---------- Show first 10 rows of artists table parquet file ----------\\\")\\n df_artists_parquet.show(10)\",\n \"def process_data():\\n for message in get_messages_from_sqs():\\n try:\\n message_content = json.loads(message.body)\\n input_file = urllib.unquote_plus(message_content\\n ['Records'][0]['s3']['object']\\n ['key']).encode('utf-8')\\n s3.download_file(input_bucket_name, input_file, input_file)\\n output_file = os.path.join(output_dir, os.path.splitext(input_file)[0]+'.csv')\\n parse_patient_data(input_file, output_file)\\n upload_data(output_file)\\n cleanup_files(input_file, output_file)\\n except:\\n message.change_visibility(VisibilityTimeout=0)\\n continue\\n else:\\n message.delete()\",\n \"def process_song_data(spark, input_data, output_data):\\n\\n # get filepath to song data file\\n song_data = input_data + \\\"song_data/A/A/B/*.json\\\"\\n \\n # read song data file\\n song_data_schema = StructType([\\n StructField(\\\"artist_id\\\", StringType(), False),\\n StructField(\\\"artist_latitude\\\", StringType(), True),\\n StructField(\\\"artist_longitude\\\", StringType(), True),\\n StructField(\\\"artist_location\\\", StringType(), True),\\n StructField(\\\"artist_name\\\", StringType(), False),\\n StructField(\\\"song_id\\\", StringType(), False),\\n StructField(\\\"title\\\", StringType(), False),\\n StructField(\\\"duration\\\", DoubleType(), False),\\n StructField(\\\"year\\\", IntegerType(), False)\\n ])\\n \\n print(\\\"Start read s3 song data\\\") \\n df = spark.read.json(song_data, schema=song_data_schema)\\n \\n # extract columns to create songs table\\n print(\\\"Start create songs table\\\")\\n songs_table = df.select(\\\"song_id\\\", \\\"title\\\", \\\"artist_id\\\", \\\"year\\\", \\\"duration\\\")\\n \\n # write songs table to parquet files partitioned by year and artist\\n print(\\\"Start write songs table to parquet\\\")\\n songs_table.write.parquet(output_data + \\\"songs_table.parquet\\\", mode=\\\"overwrite\\\", partitionBy=[\\\"year\\\", \\\"artist_id\\\"])\\n\\n # extract columns to create artists table\\n # needs to distinct artist (can duplicate)\\n print(\\\"Start create artists table\\\")\\n artists_table = df.select(\\\"artist_id\\\", \\\"artist_name\\\", \\\"artist_location\\\", \\n \\\"artist_latitude\\\", \\\"artist_longitude\\\").distinct()\\n \\n # write artists table to parquet files\\n print(\\\"Start write artists table to parquet\\\")\\n artists_table.write.parquet(output_data + \\\"artists_table.parquet\\\", mode=\\\"overwrite\\\")\",\n \"def process_data() -> None:\\n yesterday_date = std.get_yesterday()\\n s3_working_bucket = \\\"stwit-working-bucket\\\"\\n s3_processed_bucket = \\\"stwit-processed-bucket\\\"\\n\\n df_tweets = process_tweets(s3_working_bucket, yesterday_date)\\n df_users = process_users(s3_working_bucket, yesterday_date)\\n df_stocks = process_stocks(s3_working_bucket, yesterday_date)\\n\\n logging.debug(\\\"Calling filter_tweets function.\\\")\\n df_tweets, df_users = stp.filter_tweets(df_tweets, df_users)\\n\\n logging.debug(\\\"Calling remove_duplicate_tweets function.\\\")\\n df_tweets, df_users = stp.remove_duplicate_tweets(df_tweets, df_users)\\n\\n logging.debug(\\\"Calling export_twitter_csv function with df_tweets data.\\\")\\n stdm.export_csv(df_tweets, s3_processed_bucket, yesterday_date, \\\"twitter\\\", \\\"tweets\\\")\\n\\n logging.debug(\\\"Calling export_twitter_csv function with df_users data.\\\")\\n stdm.export_csv(df_users, s3_processed_bucket, yesterday_date, \\\"twitter\\\", \\\"users\\\")\\n\\n logging.debug(\\\"Calling export_stocks_csv function.\\\")\\n stdm.export_csv(df_stocks, s3_processed_bucket, yesterday_date, \\\"stocks\\\")\",\n \"def process_song_data(spark, input_data, output_data):\\n \\n print(\\\"Read song data\\\")\\n df_song = spark.read.json(input_data+\\\"song_data/*/*/*/*.json\\\", schema=build_song_schema())\\n \\n # extract columns to create songs table\\n songs_table = df_song[['song_id', 'title', 'artist_id', 'year', 'duration']].drop_duplicates()\\n\\n \\n print(\\\"Write...\\\")\\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.save(path=output_data+'song_table',\\n format='parquet',\\n partitionBy=['year', 'artist_id'],\\n mode='overwrite' )\\n\\n # extract columns to create artists table\\n artists_table = df_song[['artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude']].drop_duplicates()\\n\\n print(\\\"Write...\\\")\\n # write artists table to parquet files\\n artists_table.write.save(path=output_data+'artists_table',\\n format='parquet',\\n mode='overwrite' )\",\n \"def process_log_file(cur, filepath):\\n # open log file\\n datalog = pd.read_json(filepath, lines=True)\\n\\n df = pd.DataFrame(data=datalog)\\n df.head()\\n\\n # convert timestamp column to datetime\\n t = pd.to_datetime(df['ts'], unit='ms')\\n \\n # insert time data records\\n time_log = []\\n column_labels = ('start time','hour','day','week of year','month','year','weekday')\\n index = 0\\n for timestamp in t:\\n time_data = (t[index],t.dt.hour[index],t.dt.day[index],t.dt.week[index],t.dt.month[index],t.dt.year[index],t.dt.weekday[index])\\n time_log.append(time_data)\\n index = index + 1\\n \\n time_df = pd.DataFrame.from_dict(time_log)\\n #print(time_df)\\n time_df.head()\\n\\n\\n for i, row in time_df.iterrows():\\n cur.execute(time_table_insert, list(row))\\n \\n\\n # load user table\\n user_df_data = df[['userId', 'firstName', 'lastName','gender','level']].values\\n user_df = pd.DataFrame.from_dict(user_df_data)\\n\\n # insert user records\\n for i, row in user_df.iterrows():\\n cur.execute(user_table_insert, row)\\n \\n # insert songplay records\\n for index, row in df.iterrows():\\n \\n # get songid and artistid from song and artist tables\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n \\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n # insert songplay record\\n songplay_data = (pd.to_datetime(row.ts, unit='ms'),row.userId,row.level,songid,artistid,row.sessionId,row.location,row.userAgent)\\n cur.execute(songplay_table_insert, songplay_data)\",\n \"def process_song_data(\\n spark: SparkSession,\\n input_data: str,\\n output_data: str\\n) -> None:\\n # get filepath to song data file\\n song_data = input_data + 'song_data/*/*/*/'\\n\\n songdata_schema = StructType([\\n StructField(\\\"song_id\\\", StringType(), True),\\n StructField(\\\"title\\\", StringType(), True),\\n StructField(\\\"year\\\", StringType(), True),\\n StructField(\\\"duration\\\", DoubleType(), True),\\n StructField(\\\"artist_id\\\", StringType(), True),\\n StructField(\\\"artist_name\\\", StringType(), True),\\n StructField(\\\"artist_location\\\", StringType(), True),\\n StructField(\\\"artist_latitude\\\", DoubleType(), True),\\n StructField(\\\"artist_longitude\\\", DoubleType(), True),\\n ])\\n # read song data file\\n df = spark.read.json(song_data, schema=songdata_schema)\\n\\n # extract columns to create songs table\\n songs_table = df.select(\\n 'song_id', 'title', 'artist_id', 'year', 'duration') \\\\\\n .dropDuplicates()\\n songs_table.createOrReplaceTempView('songs')\\n\\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.partitionBy('year', 'artist_id') \\\\\\n .parquet(join(output_data, 'songs/songs.parquet'), 'overwrite')\\n\\n # # extract columns to create artists table\\n artists_table = df.select(\\n 'artist_id',\\n 'artist_name',\\n 'artist_location',\\n 'artist_latitude',\\n 'artist_longitude',\\n ).withColumnRenamed('artist_name', 'name') \\\\\\n .withColumnRenamed('artist_location', 'location') \\\\\\n .withColumnRenamed('artist_latitude', 'latitude') \\\\\\n .withColumnRenamed('artist_longitude', 'longitude') \\\\\\n .dropDuplicates()\\n artists_table.createOrReplaceTempView('artists')\\n # # write artists table to parquet files\\n artists_table.write.parquet(\\n join(output_data, 'artists/artists.parquet'),\\n 'overwrite'\\n )\",\n \"def process_song_data(spark, input_data, output_data):\\n\\n # get filepath to song data file\\n song_data = input_data + 'song_data/A/A/A/*.json'\\n\\n # read song data file\\n df = spark.read.json(song_data)\\n\\n # write song data to temp view song_data_table\\n df.createOrReplaceTempView(\\\"song_data_table\\\")\\n\\n # extract columns to create songs table\\n songs_table = df.select('song_id', 'title', 'artist_id', 'year', 'duration').drop_duplicates()\\n\\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.partitionBy(\\\"year\\\", \\\"artist_id\\\").format(\\\"parquet\\\").mode(\\\"overwrite\\\").save(\\n output_data + 'songs/song_data.parquet')\\n\\n # extract columns to create artists table\\n artists_table = df.select('artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude') \\\\\\n .drop_duplicates()\\n\\n # write artists table to parquet files\\n artists_table.write.format(\\\"parquet\\\").mode(\\\"overwrite\\\").save(output_data + 'artists/artist_data.parquet')\",\n \"def process_song_data(spark, input_data, output_data):\\n # define json structure\\n songdata_schema = StructType([\\n StructField(\\\"song_id\\\", StringType(), True),\\n StructField(\\\"year\\\", StringType(), True),\\n StructField(\\\"duration\\\", DoubleType(), True),\\n StructField(\\\"artist_id\\\", StringType(), True),\\n StructField(\\\"artist_name\\\", StringType(), True),\\n StructField(\\\"artist_location\\\", StringType(), True),\\n StructField(\\\"artist_latitude\\\", DoubleType(), True),\\n StructField(\\\"artist_longitude\\\", DoubleType(), True),\\n ])\\n \\n # get filepath to song data file\\n song_data = os.path.join(input_data, \\\"song_data/*/*/*/*.json\\\")\\n \\n # read song data file\\n df = spark.read.json(song_data, schema=songdata_schema)\\n\\n # extract columns to create songs table\\n songs_table = df.select('song_id', 'artist_id', 'year', 'duration')\\n \\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.partitionBy('year', 'artist_id').parquet(output_data + \\\"songs\\\")\\n\\n # extract columns to create artists table\\n artists_table = df.select('artist_id', 'artist_name', 'artist_location', 'artist_latitude',\\n 'artist_longitude')\\n \\n # write artists table to parquet files\\n artists_table.write.parquet(output_data + \\\"artists\\\")\",\n \"def process_app_log(event, context):\\n pubsub_message = base64.b64decode(event[\\\"data\\\"]).decode(\\\"utf-8\\\")\\n\\n log_data = json.loads(pubsub_message)\\n print(log_data)\\n payload = None\\n try:\\n if \\\"protoPayload\\\" in log_data:\\n # If there is a protoPayload, we assume it's an entry from the audit log\\n protoPayload = log_data[\\\"protoPayload\\\"]\\n payload = protoPayload[\\\"operation\\\"].copy()\\n payload[\\\"methodName\\\"] = log_data[\\\"methodName\\\"]\\n payload[\\\"timestamp\\\"] = log_data[\\\"timestamp\\\"]\\n\\n elif \\\"jsonPayload\\\" in log_data:\\n # Assuming the log entry has the fields we need, we just pass it over\\n payload = log_data[\\\"jsonPayload\\\"]\\n\\n if payload:\\n time_difference = store_data(payload)\\n if time_difference:\\n send_metric(time_difference, payload[\\\"methodName\\\"])\\n except Exception as e:\\n print(e)\",\n \"def process_log_file(cur, filepath):\\n\\n # open log file\\n df = pd.read_json(filepath, lines=True)\\n\\n # filter by NextSong action\\n df = df[df['page'] == 'NextSong']\\n\\n # convert timestamp column to datetime\\n t = pd.to_datetime(df['ts'], unit='ms')\\n\\n # insert time data records\\n time_data = (t, t.dt.hour, t.dt.day,\\n t.dt.month, t.dt.year, t.dt.day_name())\\n column_labels = ('start_time', 'hour', 'day', 'month', 'year', 'weekday')\\n time_df = pd.DataFrame(dict(zip(column_labels, time_data)))\\n\\n # bulk insert time_df into Postgres\\n # create a csv like object\\n output = io.StringIO()\\n time_df.to_csv(output, sep='\\\\t', index=False, header=False)\\n # move the pointer to start of the file\\n output.seek(0)\\n # creating a temp table to handle conflict due to duplicate insert\\n # ref: https://stackoverflow.com/questions/48019381/how-postgresql-copy-to-stdin-with-csv-do-on-conflic-do-update\\n cur.execute(time_tmp_table)\\n # copy data from csv to temp table\\n cur.copy_from(output, 'tmp_table')\\n # merge temp table with main table\\n cur.execute(time_table_bulk_insert)\\n\\n # load user table\\n user_df = df[['userId', 'firstName', 'lastName', 'gender', 'level']]\\n\\n # insert user records\\n for i, row in user_df.iterrows():\\n cur.execute(user_table_insert, row)\\n\\n # insert songplay records\\n # create a csv like object\\n output = io.StringIO()\\n for index, row in df.iterrows():\\n\\n # get songid and artistid from song and artist tables\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n\\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n # insert songplay record\\n songplay_data = (t[index], row.userId, row.level, songid,\\n artistid, row.sessionId, row.location, row.userAgent)\\n # write to csv like object\\n output.write('\\\\t'.join(map(clean_csv_value, songplay_data)) + '\\\\n')\\n # move the pointer to start of the csv like object\\n output.seek(0)\\n # columns to insert (songplay_id is a serial insert)\\n columns = ['start_time', 'user_id', 'level', 'song_id',\\n 'artist_id', 'session_id', 'location', 'user_agent']\\n # copy data to songplays table\\n cur.copy_from(output, 'songplays', columns=columns)\",\n \"def analyze(sc, input_path, output_path):\\n context = LogsJobContext(sc)\\n # get filepath to log data file\\n log_data = \\\"{}/log_data/*/*/*.json\\\".format(input_path)\\n # read log data file\\n df = sc.read.json(log_data)\\n df.cache()\\n # filter by actions for song plays\\n df = df.filter(df.page == 'NextSong')\\n df.cache()\\n\\n # extract columns for users table\\n users = df.selectExpr('userId as user_id', 'firstName as first_name', 'lastName as last_name', 'gender',\\n 'level').dropDuplicates()\\n # write users table to parquet files\\n users.write.parquet(\\\"{}/users.parquet\\\".format(output_path), mode='overwrite')\\n\\n start_times_datetime = df.dropDuplicates().selectExpr(\\\"cast((from_unixtime(ts/1000.0)) as timestamp) as start_time\\\")\\n start_times_datetime.printSchema()\\n time = start_times_datetime.selectExpr([\\\"start_time\\\", \\\"hour(start_time) as hour\\\", \\\"day(start_time) as day\\\",\\n \\\"weekofyear(start_time) as week\\\", \\\"month(start_time) as month\\\",\\n \\\"year(start_time) as year\\\",\\n \\\"dayofweek(start_time) as weekday\\\"\\n ])\\n\\n # write time table to parquet files partitioned by year and month\\n time.write.partitionBy(['year', 'month']).parquet(\\\"{}/times.parquet\\\".format(output_path), mode=\\\"overwrite\\\")\\n\\n # read in song data to use for songplays table\\n song_df = sc.read.parquet(\\\"{}/songs.parquet\\\".format(output_path))\\n\\n # extract columns from joined song and log datasets to create songplays table\\n song_df.createOrReplaceTempView('songs')\\n df.createOrReplaceTempView('logs')\\n songplays_table = sc.sql('select \\\\\\n monotonically_increasing_id() as songplay_id, \\\\\\n from_unixtime(l.ts/1000) as start_time, \\\\\\n userId as user_id,\\\\\\n l.level,\\\\\\n s.song_id,\\\\\\n s.artist_id,\\\\\\n l.sessionId as session_id,\\\\\\n l.location,\\\\\\n l.userAgent as user_agent\\\\\\n from \\\\\\n logs l \\\\\\n left join songs s on l.song = s.title')\\n\\n songplays_table_for_partitioning = songplays_table\\\\\\n .withColumn('year', F.year(songplays_table.start_time))\\\\\\n .withColumn('month', F.month(songplays_table.start_time))\\n\\n # write songplays table to parquet files partitioned by year and month\\n songplays_table_for_partitioning.write.partitionBy(['year', 'month']) \\\\\\n .parquet(\\\"{}/songplays.parquet\\\".format(output_path), mode='overwrite')\",\n \"def process_song_data(spark, input_data, output_data):\\n \\n # get filepath to song data file\\n song_data = input_data + \\\"song_data/*/*/*/*.json\\\"\\n \\n # read song data file\\n df = spark.read.json(song_data).dropDuplicates()\\n\\n # extract columns to create songs table\\n global songs_table\\n songs_table = df.select(['song_id', 'title', 'artist_id', 'year', 'duration'])\\n \\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.partitionBy(\\\"year\\\", \\\"artist_id\\\").parquet(\\\"output_data + SongTable.parquet\\\")\\n\\n # extract columns to create artists table\\n artists_table = df.select(['artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude'])\\n \\n # write artists table to parquet files\\n artists_table.write.parquet(output_data + \\\"ArtistTable.parquet\\\")\",\n \"def lambda_handler(event, context):\\n\\n for record in event['Records']:\\n\\n bucket = record['s3']['bucket']['name']\\n key = unquote_plus(record['s3']['object']['key'])\\n\\n str_value = s3_utils.download_file_as_string(bucket, key)\\n data = json.loads(str_value)\\n\\n normalized_data = {\\n 'meta': {\\n 'table': 'parcels',\\n 'column_names': [\\n 'dataset',\\n 'as_of',\\n 'apn',\\n 'objectid',\\n 'city',\\n 'x_coordinate',\\n 'y_coordinate',\\n 'area',\\n 'length'\\n ]\\n }\\n }\\n\\n rows = []\\n\\n dataset = data['meta']['dataset']\\n as_of = data['meta']['datetime']\\n\\n for r in data['results']:\\n\\n attr = r['attributes']\\n\\n temp_dict = {\\n 'dataset': dataset,\\n 'as_of': as_of,\\n 'apn': attr.get('APN_SPACE'),\\n 'objectid': attr.get('OBJECTID'),\\n 'city': attr.get('CITY'),\\n 'x_coordinate': attr.get('X'),\\n 'y_coordinate': attr.get('Y'),\\n 'area': attr.get('Shape.STArea()'),\\n 'length': attr.get('Shape.STLength()')\\n }\\n\\n rows.append(temp_dict)\\n\\n normalized_data['rows'] = rows\\n \\n bucket = 'gis-data-normalized'\\n file_name = 'normalized_' + key\\n s3_utils.upload_json_as_file(normalized_data, bucket, file_name)\",\n \"def process_song_data(spark, input_data, output_data):\\n # get filepath to song data file\\n song_data = f'{input_data}/song_data/*/*/*/*.json'\\n \\n # read song data file\\n df = spark.read.json(song_data)\\n\\n # extract columns to create songs table\\n songs_table = df.select([\\\"song_id\\\", \\\"title\\\", \\\"artist_id\\\", \\\"year\\\", \\\"duration\\\"]).where(df[\\\"song_id\\\"].isNotNull())\\n \\n # write songs table to parquet files partitioned by year and artist\\n song_data_out = f'{output_data}/songs_table/songs_table.parquet'\\n songs_table.write.mode('overwrite').partitionBy('year','artist_id').parquet(song_data_out)\\n\\n # extract columns to create artists table\\n artists_table = df.select([\\\"artist_id\\\", \\\"artist_name\\\", \\\"artist_location\\\", \\\"artist_latitude\\\", \\\"artist_longitude\\\"]).where(df[\\\"artist_id\\\"].isNotNull())\\n \\n # write artists table to parquet files\\n artists_data_out = f'{output_data}/artists_table/artists_table.parquet'\\n artists_table.write.mode('overwrite').parquet(artists_data_out)\",\n \"def process_song_data(spark, input_data, output_data):\\n\\n # get filepath to song data file\\n song_data = input_data + \\\"song-data/*/*/*/*.json\\\"\\n\\n # read song data file\\n df = spark.read.json(song_data)\\n\\n # extract columns to create songs table\\n songs_table = df.select(\\\"song_id\\\", \\\"title\\\", \\\"artist_id\\\", \\\"year\\\", \\\"duration\\\")\\n \\n # write songs table to parquet files partitioned by year and artist\\n file_name = output_data + \\\"songs.parquet\\\"\\n songs_table.write.partitionBy([\\\"year\\\", \\\"artist_id\\\"]).parquet(file_name)\\n\\n # extract columns to create artists table\\n artists_table = df.select(\\\"artist_id\\\", \\\"artist_name\\\", \\\"artist_longitude\\\", \\\"artist_latitude\\\", \\\"artist_location\\\")\\n \\n # write artists table to parquet files\\n file_name = output_data + \\\"artists.parquet\\\"\\n artists_table.write.parquet(file_name)\",\n \"def process_log_file(cur, filepath):\\n \\n # open log file\\n df = pd.read_json(filepath,lines=True)\\n\\n # filter by NextSong action - i.e. get only listening music events from the logs\\n df = df[(df.page == \\\"NextSong\\\")]\\n\\n # insert time records\\n __insert_time_data(cur, df)\\n \\n # insert user records\\n __insert_user_data(cur, df)\\n \\n # insert songplay records\\n __insert_songplay_data(cur, df)\\n \\n # erase dataframe\\n df = df.iloc[0:0]\",\n \"def process_song_data(spark, input_data, output_data):\\n \\n # get filepath to song data file\\n song_data = input_data + \\\"/song_data/A/A/A/*.json\\\"\\n \\n # read song data file\\n df = spark.read.json(song_data)\\n #df.show(5)\\n \\n # extract columns to create songs table\\n songs_table = df.select(\\\"song_id\\\",\\\"title\\\", \\\"artist_id\\\",\\\"year\\\", \\\"duration\\\")\\n songs_table = songs_table.dropDuplicates()\\n songs_table.createOrReplaceTempView(\\\"temp_songs_table\\\")\\n # write songs table to parquet files partitioned by year and artist\\n songs_table = df.write.partitionBy(\\\"year\\\",\\\"artist_id\\\")\\\\\\n .mode(\\\"overwrite\\\").parquet(output_data + \\\"/songs_table\\\")\\n print(\\\"Songs Table Successfully created\\\")\\n \\n # extract columns to create artists table\\n artists_table = df.select(\\\"artist_id\\\",\\\"artist_name\\\", \\\\\\n \\\"artist_location\\\",\\\"artist_latitude\\\", \\\"artist_longitude\\\")\\n artists_table = artists_table.dropDuplicates()\\n artists_table.createOrReplaceTempView(\\\"temp_artists_table\\\")\\n \\n # write artists table to parquet files\\n artists_table = df.write.mode(\\\"overwrite\\\").parquet(output_data + \\\"/artists_table\\\")\\n print(\\\"Artists Table Successfully created\\\")\",\n \"def process_log_file(cur, filepath):\\n \\n # open log file\\n \\n df = pd.read_json(filepath, lines = True)\\n \\n # filter by NextSong action\\n df = df[df['page']=='NextSong']\\n # convert timestamp column to datetime\\n t = pd.to_datetime(df.ts, unit='ms')\\n df.ts = t\\n \\n # insert time data records\\n time_data = [t, t.dt.hour, t.dt.day, t.dt.weekofyear,\\n t.dt.month, t.dt.year, t.dt.weekday]\\n \\n # column_labels = ['timestamp','Hour', \\n # 'Day','Month','Year''Weekday']'\\n column_labels = ['timestamp','hour','day','weekofyear','month','year','weekday']\\n time_df = pd.DataFrame(dict(zip(column_labels, time_data)))\\n\\n for i, row in time_df.iterrows():\\n cur.execute(time_table_insert, list(row))\\n \\n # load user table\\n user_df = df[['userId','firstName', \\n 'lastName','gender','level']]\\n\\n # insert user records\\n for i, row in user_df.iterrows(): \\n cur.execute(user_table_insert, row)\\n \\n # insert songplay records\\n for index, row in df.iterrows():\\n \\n # get songid and artistid from song and artist tables\\n cur.execute(song_select, (row.song, row.artist,\\n row.length))\\n results = cur.fetchone()\\n \\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n # insert songplay record\\n songplay_data = (index, row.ts, row.userId, row.level,\\n songid, artistid, row.sessionId, \\n row.location, row.userAgent)\\n \\n \\n cur.execute(songplay_table_insert, songplay_data)\",\n \"def processData(\\n filePath: str,\\n path: str,\\n fileSchema: Dict,\\n pkey: str,\\n definingCol: str,\\n hashKeyCols: List[str],\\n hashDataCols: List[str],\\n partitionCol: str = \\\"date_loaded\\\",\\n) -> Dict:\\n try:\\n schema = generateSchema(fileSchema)\\n logger.info(\\\"Loading data from input file\\\")\\n df = (\\n spark.read.format(\\\"csv\\\")\\n .option(\\\"header\\\", True)\\n .schema(schema)\\n .load(filePath)\\n )\\n count = df.count()\\n windowBy = Window.partitionBy(f.col(pkey)).orderBy(f.col(definingCol))\\n logger.info(\\\"Generating the required Audit Columns\\\")\\n df = (\\n df.withColumn(\\n \\\"hashKey\\\",\\n f.sha2(\\n f.concat_ws(\\n \\\"|\\\", *map(lambda key_cols: f.col(key_cols), hashKeyCols)\\n ),\\n 256,\\n ),\\n )\\n .withColumn(\\n \\\"hashData\\\",\\n f.sha2(\\n f.concat_ws(\\n \\\"|\\\", *map(lambda key_cols: f.col(key_cols), hashDataCols)\\n ),\\n 256,\\n ),\\n )\\n .withColumn(\\\"startDate\\\", f.col(definingCol))\\n .withColumn(\\\"endDate\\\", f.lead(f.col(definingCol)).over(windowBy))\\n .withColumn(\\n str(partitionCol), f.lit(datetime.datetime.now().strftime(\\\"%Y-%m-%d\\\"))\\n )\\n )\\n if not DeltaTable.isDeltaTable(spark, path):\\n logger.info(\\\"Performing the initial load\\\")\\n status = performFirstLoad(df, path, partitionCol)\\n else:\\n logger.info(\\\"Performing the incremental load\\\")\\n status = performDeltaLoad(df, path, pkey)\\n return {**status, **{\\\"count\\\": count}}\\n except Exception as e:\\n logger.error(\\n \\\"Issue while processing the {0} error : {1}\\\".format(filePath, str(e)[:100])\\n )\\n return {\\\"status\\\": \\\"Failed\\\", \\\"message\\\": str(e)[:100], \\\"count\\\": 0}\\n # raise DLoaderException(\\\"Failed while processing the data :{0}\\\".format(e))\",\n \"def process_song_data(spark, input_data, output_data):\\n # get filepath to song data file\\n song_data = input_data + \\\"song_data/*/*/*/*.json\\\"\\n \\n # read song data file\\n df = spark.read.json(song_data)\\n\\n # extract columns to create songs table\\n songs_table = df.filter(df.song_id != '') \\\\\\n .select(\\\"song_id\\\", \\\"title\\\", \\\"artist_id\\\", \\\"year\\\", \\\"duration\\\") \\\\\\n .dropDuplicates()\\n \\n # output filepath to songs table file\\n songs_table_path = output_data + \\\"songs_table.parquet\\\"\\n \\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.partitionBy(\\\"year\\\", \\\"artist_id\\\").mode(\\\"overwrite\\\") \\\\\\n .parquet(songs_table_path)\\n\\n # extract columns to create artists table\\n artists_table = df.filter(df.artist_id != '').select(\\\"artist_id\\\",\\n \\\"artist_name\\\", \\\"artist_location\\\", \\\"artist_latitude\\\", \\\"artist_longitude\\\") \\\\\\n .dropDuplicates()\\n \\n # output filepath to artists table file\\n artists_table_path = output_data + \\\"artists_table.parquet\\\"\\n \\n # write artists table to parquet files\\n artists_table.write.mode(\\\"overwrite\\\") \\\\\\n .parquet(artists_table_path)\",\n \"def process_log_file(cur, filepath):\\r\\n\\r\\n # open log file\\r\\n df = pd.read_json(filepath, lines=True)\\r\\n df2 = pd.read_json(filepath, lines=True)\\r\\n\\r\\n # filter by NextSong action for missing data\\r\\n df2 = df2[df2['page']=='NextSong']\\r\\n\\r\\n\\r\\n\\r\\n # insert missing records into Song and Artist Table\\r\\n for i, row in df2.iterrows():\\r\\n cur.execute(artist_table_insert, (row.artist + str(i), row.artist, row.location, 0, 0))\\r\\n for i, row in df2.iterrows():\\r\\n cur.execute(song_table_insert, (row.song + str(i), row.song, row.artist + str(i), 0, row.length))\\r\\n\\r\\n # filter by NextSong action\\r\\n df = df[df['page']=='NextSong']\\r\\n\\r\\n # convert timestamp column to datetime\\r\\n t = pd.to_datetime(df['ts'], unit='ms')\\r\\n\\r\\n # extract time data from timestamp\\r\\n time_data = {'start_time': t,'hour': pd.Series(t).dt.hour, 'day':pd.Series(t).dt.day,\\r\\n 'month': pd.Series(t).dt.month, 'year': pd.Series(t).dt.year,\\r\\n 'weekday': pd.Series(t).dt.dayofweek}\\r\\n #column_labels = []\\r\\n # insert time data records\\r\\n time_df = pd.DataFrame(time_data)\\r\\n\\r\\n for i, row in time_df.iterrows():\\r\\n cur.execute(time_table_insert, list(row))\\r\\n\\r\\n # load user table\\r\\n user_df = df[['userId', 'firstName','lastName','gender','level']]\\r\\n user_df.drop_duplicates(subset='userId',keep ='first',inplace = True)\\r\\n\\r\\n # insert user records\\r\\n for i, row in user_df.iterrows():\\r\\n cur.execute(user_table_insert, row)\\r\\n\\r\\n # insert songplay records\\r\\n for index, row in df.iterrows():\\r\\n\\r\\n # get songid and artistid from song and artist tables\\r\\n print(cur.mogrify(song_select, (row.song, row.artist, row.length)))\\r\\n cur.execute(song_select, (row.song, row.artist, row.length))\\r\\n results = cur.fetchone()\\r\\n\\r\\n if results:\\r\\n songid, artistid = results[0],results[1]\\r\\n else:\\r\\n songid, artistid = \\\"None\\\" + str(index), \\\"None\\\" + str(index)\\r\\n\\r\\n # insert songplay record\\r\\n songplay_data = (df[['ts', 'userId', 'level', 'sessionId','location','userAgent' ]])\\r\\n songplay_data['ts'] = pd.to_datetime(df['ts'], unit='ms')\\r\\n cur.execute(songplay_table_insert, (index, row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent))\\r\\n #conn.commit()\\r\",\n \"def process_song_data(spark, input_data, output_data, mode=\\\"overwrite\\\"):\\n # get filepath to song data file\\n song_data = input_data + \\\"song_data/*/*/*/*.json\\\"\\n\\n # read song data file\\n print(\\\"reading song logs from {}\\\".format(song_data))\\n df = spark.read.json(song_data)\\n\\n # extract columns to create songs table\\n song_fields = ['song_id', 'title', 'artist_id', 'year', 'duration']\\n songs_table = df.select(song_fields)\\n songs_table = songs_table.withColumn('year', F.col('year').cast(IntegerType()))\\n songs_table = songs_table.withColumn('duration', F.col('duration').cast(DoubleType()))\\n\\n # write songs table to parquet files partitioned by year and artist\\n song_path = output_data + 'star_schema/song_table/'\\n print(\\\"Writing Song Table to {}\\\".format(song_path))\\n songs_table.write \\\\\\n .mode(mode) \\\\\\n .partitionBy('year', 'artist_id') \\\\\\n .parquet(song_path)\\n\\n # extract columns to create artists table\\n artist_fields = [\\n 'artist_id', 'artist_name',\\n 'artist_location', 'artist_latitude', 'artist_longitude'\\n ]\\n artists_table = df.select(artist_fields)\\n artists_table = artists_table.withColumnRenamed(\\n 'artist_name', 'name'\\n )\\n artists_table = artists_table.withColumnRenamed(\\n 'artist_location', 'location'\\n )\\n artists_table = artists_table.withColumn(\\n 'latitude',\\n F.col('artist_latitude').cast(DoubleType())\\n )\\n artists_table = artists_table.withColumn(\\n 'longitude',\\n F.col('artist_longitude').cast(DoubleType())\\n )\\n artist_col_names = [\\n 'artist_id', 'name', 'location', 'latitude', 'longitude'\\n ]\\n artists_table = artists_table.select(artist_col_names)\\n\\n # write artists table to parquet files\\n artists_path = output_data + 'star_schema/artist_table'\\n print(\\\"Writing Artist Table to {}\\\".format(artists_path))\\n artists_table.write \\\\\\n .mode(mode) \\\\\\n .partitionBy('artist_id') \\\\\\n .parquet(artists_path)\",\n \"def process_song_data(spark, input_data, output_data):\\n # get filepath to song data file\\n song_data = os.path.join(input_data, 'song_data', '*', '*', '*')\\n \\n # read song data file\\n df = spark.read.json(song_data)\\n print(f\\\"Loaded song_data from {input_data}\\\")\\n df.createOrReplaceTempView(\\\"song_data\\\")\\n \\n # extract columns to create songs table\\n songs_table = spark.sql(\\\"\\\"\\\"\\n SELECT song_id, title, artist_id, year, duration\\n FROM song_data\\n \\\"\\\"\\\")\\n \\n # write songs table to parquet files partitioned by year and artist\\n songs_table_path = os.path.join(output_data, \\\"songs_table.parquet\\\")\\n (songs_table.\\n write.\\n mode(\\\"overwrite\\\").\\n partitionBy(\\\"year\\\", \\\"artist_id\\\").\\n parquet(songs_table_path))\\n print(f\\\"Stored song table on {songs_table_path}\\\")\\n # extract columns to create artists table\\n artists_table = spark.sql(\\\"\\\"\\\"\\n SELECT \\n DISTINCT(artist_id) AS artist_id, \\n artist_name AS name, \\n artist_location AS location, \\n artist_latitude AS latitude, \\n artist_longitude AS longitude\\n FROM song_data\\n \\\"\\\"\\\")\\n \\n # write artists table to parquet files\\n artists_table_path = os.path.join(output_data, \\\"artists_table.parquet\\\")\\n (artists_table.\\n write.\\n mode(\\\"overwrite\\\").\\n parquet(artists_table_path))\\n print(f\\\"Stored artists table at {artists_table_path}\\\")\",\n \"def process_song_data(spark, input_data, output_data):\\n # get filepath to song data file\\n song_data = os.path.join(input_data, \\\"song-data/*/*/*/*.json\\\")\\n\\n # read song data file\\n df = spark.read.json(song_data)\\n\\n # extract columns to create songs table\\n songs_table = df.select('song_id', 'title', 'artist_id', 'year', 'duration')\\n\\n # write songs table to parquet files partitioned by year and artist_id\\n songs_table.write.partitionBy('year', 'artist_id').parquet(output_data + 'songs', mode='overwrite')\\n\\n # extract columns to create artists table\\n artists_table = df.select('artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude')\\n\\n # write artists table to parquet files\\n artists_table.write.parquet(output_data + 'artists', mode='overwrite')\",\n \"def process_input_data(input_data_path):\\n if os.path.isdir(input_data_path):\\n input_data_glob = glob.glob(input_data_path + \\\"/*.csv\\\")\\n else:\\n if is_gcs_path(input_data_path):\\n # Download the input to a local\\n with tempfile.NamedTemporaryFile() as hf:\\n input_data = hf.name\\n\\n logging.info(\\\"Copying %s to %s\\\", input_data_path, input_data)\\n input_data_gcs_bucket, input_data_gcs_path = split_gcs_uri(\\n input_data_path)\\n\\n logging.info(\\\"Download bucket %s object %s.\\\", input_data_gcs_bucket,\\n input_data_gcs_path)\\n bucket = storage.Bucket(storage.Client(), input_data_gcs_bucket)\\n storage.Blob(input_data_gcs_path, bucket).download_to_filename(\\n input_data)\\n else:\\n input_data = input_data_path\\n\\n ext = os.path.splitext(input_data)[-1]\\n if ext.lower() == '.zip':\\n zip_ref = zipfile.ZipFile(input_data, 'r')\\n zip_ref.extractall('.')\\n zip_ref.close()\\n # TODO: Hardcoding the file in the Archive to use is brittle.\\n # We should probably just require the input to be a CSV file.:\\n csv_file = 'stackoverflow-questions.csv'\\n else:\\n csv_file = input_data\\n\\n input_data_glob = glob.glob(csv_file)\\n\\n return input_data_glob\",\n \"def process_song_data(spark, input_data, output_data):\\n # get filepath to song data file\\n song_data = input_data + 'song_data/*/*/*/*.json'\\n \\n # read song data file\\n df = spark.read.json(song_data)\\n \\n # create view for songs table\\n df.createOrReplaceTempView(\\\"songs\\\") \\n \\n \\n # extract columns to create songs table. Adding Distinct and Not null to song_id as it is the primary key\\n songs_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT song_id, \\n title,\\n artist_id,\\n year,\\n duration\\n FROM songs\\n WHERE song_id IS NOT NULL\\n \\\"\\\"\\\")\\n \\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.mode('overwrite').partitionBy(\\\"year\\\", \\\"artist_id\\\").parquet(output_data+'songs_table/')\\n\\n # create view for artists table\\n df.createOrReplaceTempView(\\\"artists\\\") \\n \\n # extract columns to create artists table, Adding Distinct and Not null to artist_id as it is the primary key\\n artists_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT artist_id, \\n artist_name,\\n artist_location,\\n artist_latitude,\\n artist_longitude\\n FROM artists\\n WHERE artist_id IS NOT NULL\\n \\\"\\\"\\\")\\n \\n # write artists table to parquet files\\n artists_table.write.mode('overwrite').parquet(output_data+'artists_table/')\",\n \"def process_song_data(spark, song_input_data, output_data):\\n # get filepath to song data file\\n song_data = song_input_data\\n \\n # read song data file\\n print(\\\"Processing JSON song data...\\\")\\n df = spark.read.json(song_data)\\n\\n # extract columns to create songs table\\n print(\\\"Extracting columns for song table...\\\")\\n df.createOrReplaceTempView(\\\"songs_table\\\")\\n songs_table = spark.sql(\\\"\\\"\\\"\\n SELECT song_id, title, artist_id, year, duration\\n FROM songs_table\\n ORDER BY song_id\\n \\\"\\\"\\\") \\n \\n print(\\\"Song table sample:\\\")\\n songs_table.show(5, truncate=False)\\n \\n # write songs table to parquet files partitioned by year and artist\\n print(\\\"Writing songs table to parquet files...\\\")\\n songs_table.write.mode(\\\"overwrite\\\").partitionBy(\\\"year\\\", \\\"artist_id\\\")\\\\\\n .parquet(output_data + \\\"songs_table.parquet\\\")\\n \\n # extract columns to create artists table\\n print(\\\"Extracting columns for artists table...\\\")\\n df.createOrReplaceTempView(\\\"artists_table\\\")\\n artists_table = spark.sql(\\\"\\\"\\\"\\n SELECT artist_id,\\n artist_name AS name,\\n artist_location AS location,\\n artist_latitude AS latitude,\\n artist_longitude AS longitude\\n FROM artists_table\\n ORDER BY artist_id DESC\\n \\\"\\\"\\\") \\n\\n print(\\\"Artists table sample:\\\")\\n artists_table.show(5, truncate=False)\\n \\n # write artists table to parquet files\\n print(\\\"Writing artists table to parquet files...\\\")\\n songs_table.write.mode(\\\"overwrite\\\").parquet(output_data + \\\"artists_table.parquet\\\")\",\n \"def _process_task_log(self):\\n directory = self._executor.log_dir\\n if os.path.exists(directory):\\n for root, _dirs, files in os.walk(directory):\\n for name in files:\\n filepath = os.path.join(root, name)\\n object_name = str(self._task.project_id) + \\\"/\\\" + self._task.node_id + \\\"/log/\\\" + name\\n if not self._s3.client.upload_file(self._s3.bucket, object_name, filepath):\\n log.error(\\\"Error uploading file to S3\\\")\",\n \"def process_song_data(spark, input_data, output_data):\\n \\n # get filepath to song data file\\n song_data = os.path.join( input_data, \\\"song_data/*/*/*/*.json\\\")\\n \\n # SONG TABLE\\n # read song data file\\n df = spark.read.json(song_data)\\n \\n # extract columns to create songs table\\n songs_table = df.select('song_id', 'title', 'artist_id',\\n 'year', 'duration').dropDuplicates(['song_id'])\\n \\n print( \\\"HERE songs_table sample:\\\\n\\\")\\n songs_table.show(5)\\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.partitionBy('year', 'artist_id').parquet(os.path.join(output_data, 'songs/songs.parquet'), 'overwrite')\\n \\n # ARTISTS TABLE\\n # extract columns to create artists table\\n artists_table = df.select(\\\"artist_id\\\",\\\"artist_name\\\",\\\"artist_location\\\",\\\"artist_latitude\\\",\\\"artist_longitude\\\").dropDuplicates(['artist_id'])\\n \\n print( \\\"HERE artists_table sample:\\\\n\\\")\\n artists_table.show(5)\\n # write artists table to parquet files\\n artists_table.write.parquet(output_data + \\\"artists/\\\", mode=\\\"overwrite\\\")\",\n \"def process_song_data(spark, input_data, output_data):\\n\\n # get filepath to song data file\\n input_data = input_data+\\\"/song-data\\\"\\n print(input_data)\\n \\n \\\"\\\"\\\"\\n for x in os.walk(input_data):\\n for y in glob.glob(os.path.join(x[0], '*.json')):\\n song_data.append(y)\\n \\\"\\\"\\\"\\n\\n df = spark.read.json(input_data)\\n df.createOrReplaceTempView(\\\"Staging_Song_Data\\\")\\n song_Data_DF = spark.sql(\\\"select * from Staging_Song_Data\\\")\\n\\n # extract columns to create songs table\\n songs_query = \\\" SELECT song_id, title, artist_id, year, duration \\\" \\\\\\n \\\" FROM Staging_Song_Data\\\"\\n songs_table = spark.sql(songs_query)\\n\\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.mode('overwrite').partitionBy(\\\"year\\\",\\\"artist_id\\\").parquet(path=output_data+\\\"songs\\\")\\n\\n # extract columns to create artists table\\n artists_query=\\\"select artist_id, artist_name as name, \\\" \\\\\\n \\\" artist_location as location, \\\" \\\\\\n \\\" artist_latitude as latitude, \\\" \\\\\\n \\\" artist_longitude as longitude \\\" \\\\\\n \\\"from Staging_Song_Data \\\"\\n artists_table =spark.sql(artists_query)\\n artists_table = artists_table.dropDuplicates(['artist_id'])\\n\\n # write artists table to parquet files\\n artists_table.write.mode('overwrite').parquet(path=output_data+\\\"artists\\\")\",\n \"def process_log_file(cur, filepath):\\n # open log file\\n df = pd.read_json(filepath, lines=True)\\n\\n # filter by NextSong action\\n df = df[df['page']=='NextSong']\\n\\n # convert timestamp column to datetime\\n t = pd.to_datetime(df['ts'], unit='ms')\\n \\n # insert time data records\\n #timestamp, hour, day, week of year, month, year, and weekday\\n hour = t.dt.hour\\n day = t.dt.day\\n weekofyear = t.dt.weekofyear\\n month = t.dt.month\\n year = t.dt.year\\n weekday = t.dt.weekday\\n\\n time_data = [df['ts'], hour, day, weekofyear, month, year, weekday]\\n column_labels = ['timestamp', 'hour', 'day', 'week of year', 'month', 'year', 'weekday']\\n time_df = pd.DataFrame.from_dict(dict(zip(column_labels, time_data)))\\n\\n for i, row in time_df.iterrows():\\n try:\\n cur.execute(time_table_insert, list(row))\\n except psycopg2.Error as e:\\n print(\\\"Error: Unable to insert record in time table in row number : {}\\\".format(i))\\n print(e)\\n\\n # load user table\\n user_df = df[['userId', 'firstName', 'lastName', 'gender', 'level']]\\n\\n # insert user records\\n for i, row in user_df.iterrows():\\n try:\\n cur.execute(user_table_insert, row)\\n except psycopg2.Error as e:\\n print(\\\"Error: Unable to insert record in users table in row number : {}\\\".format(i))\\n print(e)\\n\\n # insert songplay records\\n for index, row in df.iterrows():\\n \\n # get songid and artistid from song and artist tables\\n try:\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n except psycopg2.Error as e:\\n print(\\\"Error: Unable to execute song_select query to join songs and artists table in row number : {}\\\".format(index))\\n print(e)\\n results = cur.fetchone()\\n \\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n # insert songplay record\\n #timestamp, user ID, level, song ID, artist ID, session ID, location, and user agent\\n songplay_data = (row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent)\\n try:\\n cur.execute(songplay_table_insert, songplay_data)\\n except psycopg2.Error as e:\\n print(\\\"Error: Unable to insert record in songplays table in row number : {}\\\".format(i))\\n print(e)\",\n \"def process_song_data(spark, input_data, output_data):\\n # get filepath to song data file\\n song_data = os.path.join(input_data, 'song_data/*/*/*/*.json')\\n \\n #specify schema for increased performance and control\\n song_schema = StructType([\\n StructField(\\\"artist_id\\\", StringType()),\\n StructField(\\\"artist_latitude\\\", DoubleType()),\\n StructField(\\\"artist_location\\\", StringType()),\\n StructField(\\\"artist_longitude\\\", StringType()),\\n StructField(\\\"artist_name\\\", StringType()),\\n StructField(\\\"duration\\\", DoubleType()),\\n StructField(\\\"num_songs\\\", IntegerType()),\\n StructField(\\\"song_id\\\", StringType()),\\n StructField(\\\"title\\\", StringType()),\\n StructField(\\\"year\\\", IntegerType()),\\n ])\\n \\n # read song data file\\n dfs = spark.read.json(song_data, schema=song_schema)\\n \\n # create temporary view of table in order to run SQL queries\\n dfs.createOrReplaceTempView(\\\"song_table\\\")\\n\\n # extract columns to create songs table\\n dim_songs = spark.sql(\\\"\\\"\\\"\\n SELECT song_id,\\n title,\\n artist_id,\\n year,\\n duration\\n FROM song_table\\n WHERE song_id IS NOT NULL\\n \\\"\\\"\\\")\\n \\n # write songs table to parquet files partitioned by year and artist\\n dim_songs.write.mode('overwrite').partitionBy(\\\"year\\\", \\\"artist_id\\\").parquet(output_data+\\\"songs\\\")\\n\\n # extract columns to create artists table\\n dim_artists = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT artist_id,\\n artist_name AS name,\\n artist_location AS location,\\n artist_latitude AS latitude,\\n artist_longitude AS longitude\\n FROM song_table\\n WHERE artist_id IS NOT NULL\\n \\\"\\\"\\\")\\n \\n # write artists table to parquet files\\n dim_artists.write.mode('overwrite').parquet(output_data+\\\"artists\\\")\",\n \"def _create_input_data(self):\\n SCHEMA = parse_table_schema_from_json(\\n '{\\\"fields\\\": [{\\\"name\\\": \\\"data\\\", \\\"type\\\": \\\"BYTES\\\"}]}')\\n\\n def format_record(record):\\n # Since Synthetic Source returns data as a dictionary, we should skip one\\n # of the part\\n import base64\\n return {'data': base64.b64encode(record[1])}\\n\\n with TestPipeline() as p:\\n ( # pylint: disable=expression-not-assigned\\n p\\n | 'Produce rows' >> Read(\\n SyntheticSource(self.parse_synthetic_source_options()))\\n | 'Format' >> Map(format_record)\\n | 'Write to BigQuery' >> WriteToBigQuery(\\n dataset=self.input_dataset,\\n table=self.input_table,\\n schema=SCHEMA,\\n create_disposition=BigQueryDisposition.CREATE_IF_NEEDED,\\n write_disposition=BigQueryDisposition.WRITE_EMPTY))\",\n \"def main():\\n import sys\\n n = len(sys.argv)\\n if n != 3:\\n raise ValueError(\\\"Please specify an input s3 bin and output s3 bin\\\")\\n spark = create_spark_session()\\n input_data = sys.argv[1]\\n output_data = sys.argv[2]\\n \\n process_song_data(spark, input_data, output_data) \\n process_log_data(spark, input_data, output_data)\",\n \"def lambda_handler(event, context):\\n \\n filename = None\\n fobj = None\\n\\n try:\\n \\n filename = 'dlq' + '-' + datetime.datetime.now().strftime(\\\"%s\\\")\\n fobj = open('/tmp/'+filename, 'w')\\n logger.debug('S3 client set up.')\\n\\n for record in event['Records']:\\n fobj.write(json.dumps(record['body']))\\n fobj.write(\\\"\\\\n\\\")\\n \\n except Exception as ex:\\n logger.error('Exception in executing ingestion to S3: {}'.format(ex))\\n send_sns_alert(str(ex))\\n raise\\n\\n else:\\n \\n #Saves file to S3\\n fobj.close()\\n load_data_s3(filename)\\n\\n return {\\n 'statusCode': 200,\\n 'body': json.dumps('Success!')\\n }\\n\\n finally:\\n\\n # S3 - close temp object\\n fobj.close()\",\n \"def process_song_data(spark, input_data, output_data):\\n # get filepath to song data file\\n song_data = \\\"{}/song_data/*/*/*/*\\\".format(input_data)\\n \\n # define schema used to import song json data into our data frame\\n songSchema = R([\\n Fld(\\\"num_songs\\\", Int()),\\n Fld(\\\"artist_id\\\", Str()),\\n Fld(\\\"artist_latitude\\\", Dbl()),\\n Fld(\\\"artist_longitude\\\", Dbl()),\\n Fld(\\\"artist_location\\\", Str()),\\n Fld(\\\"artist_name\\\", Str()),\\n Fld(\\\"song_id\\\", Str()),\\n Fld(\\\"title\\\", Str()),\\n Fld(\\\"duration\\\", Dbl()),\\n Fld(\\\"year\\\", Int())\\n\\n ])\\n \\n # read song data file\\n df = spark.read.format(\\\"json\\\").load(song_data, schema=songSchema)\\n\\n # register the temp view from our dataframe df_song\\n df.createOrReplaceTempView(\\\"df_song\\\")\\n \\n # extract columns to create songs table\\n songs_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT song_id, \\n title,\\n artist_id, \\n artist_name,\\n year, \\n duration FROM df_song\\n \\\"\\\"\\\")\\n \\n # write songs table to parquet files partitioned by year and artist\\n songs_table.write.partitionBy('year', 'artist_id').parquet('{}/dim_song.pq'.format(output_data))\\n\\n # extract columns to create artists table\\n artists_table = spark.sql(\\\"\\\"\\\"\\n SELECT DISTINCT artist_id,\\n artist_name,\\n artist_location,\\n artist_latitude,\\n artist_longitude\\n FROM df_song\\n \\\"\\\"\\\")\\n \\n # write artists table to parquet files\\n artists_table.write.parquet('{}/dim_artist.pq'.format(output_data))\",\n \"def process_city_data(spark, input_data, output_data):\\n\\n # get filepath to city data file\\n city_data = os.path.join(input_data, 'city_data/*.csv')\\n\\n # read city data files\\n df = spark.read.csv(city_data, header=True, sep=';')\\n df = df.drop_duplicates(subset=['City', 'State'])\\n print('city_count = ', df.count())\\n\\n # extract columns to create city table\\n city_table = df.select(\\n F.monotonically_increasing_id().alias('city_id'),\\n F.col('City').alias('city_name'),\\n F.col('State Code').alias('state'),\\n F.col('State Code').alias('state_code'),\\n F.col('Total Population').alias('total_population')\\n )\\n\\n city_table.write.parquet(os.path.join(output_data, 'cities'), 'overwrite')\",\n \"def process_log_file(cur, filepath):\\n # open log file\\n data_frame = pd.read_json(filepath, lines=True)\\n\\n # filter by NextSong action\\n data_frame = data_frame[data_frame.page == 'NextSong']\\n\\n # convert timestamp column to datetime\\n time_value = pd.to_datetime(data_frame['ts'])\\n\\n # insert time data records\\n time_data = (time_value, time_value.dt.year, time_value.dt.month,\\n time_value.dt.isocalendar().week, time_value.dt.dayofweek,\\n time_value.dt.day, time_value.dt.hour)\\n\\n column_labels = ('timestamp', 'year', 'month', 'week', 'weekday', 'day', 'hour')\\n\\n time_df = pd.DataFrame.from_dict(dict(zip(column_labels, time_data)))\\n\\n for i, row in time_df.iterrows():\\n cur.execute(time_table_insert, list(row))\\n\\n # load user table\\n user_df = data_frame[['userId', 'firstName', 'lastName', 'gender', 'level']]\\n\\n # insert user records\\n for i, row in user_df.iterrows():\\n cur.execute(user_table_insert, row)\\n\\n # insert songplay records\\n for index, row in data_frame.iterrows():\\n\\n # get songid and artistid from song and artist tables\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n\\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n # insert songplay record\\n songplay_data = row[['ts', 'userId', 'level', 'sessionId', 'location', 'userAgent']]. \\\\\\n append(pd.Series([songid,\\n artistid],\\n index=[\\n 'songid',\\n 'artistid']))\\n songplay_data['ts'] = pd.to_datetime(songplay_data['ts'])\\n\\n cur.execute(songplay_table_insert, songplay_data)\",\n \"def process_log_file(cur, filepath):\\n df = pd.read_json(filepath, lines=True)\\n df = df.loc[df.page == 'NextSong', :]\\n\\n # insert time data records\\n df['ts'] = pd.to_datetime(df.ts, unit='ms')\\n t = df['ts']\\n time_data = {\\n 'start_time': t,\\n 'hour': t.dt.hour,\\n 'day': t.dt.day,\\n 'week': t.dt.week,\\n 'month': t.dt.month,\\n 'year': t.dt.year,\\n 'weekday': t.dt.weekday\\n }\\n time_df = pd.DataFrame(data=time_data)\\n for i, row in time_df.iterrows():\\n cur.execute(time_table_insert, list(row))\\n\\n # insert user records\\n user_df = df.loc[:, ['userId', 'firstName', 'lastName', 'gender', 'level']]\\n for i, row in user_df.iterrows():\\n cur.execute(user_table_insert, row)\\n\\n # insert songplay records\\n for index, row in df.iterrows():\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n\\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n songplay_data = {\\n 'start_time': row.ts,\\n 'user_id': row.userId,\\n 'level': row.level,\\n 'song_id': songid,\\n 'artist_id': artistid,\\n 'session_id': row.sessionId,\\n 'location': row.location,\\n 'user_agent': row.userAgent\\n }\\n cur.execute(songplay_table_insert, list(songplay_data.values()))\",\n \"def process_log_file(cursor, filepath):\\n\\n def get_timestamp_data(df):\\n # convert timestamp column to datetime\\n timestamp = pd.to_datetime(df['ts'], unit='ms')\\n\\n return (df['ts'].values,\\n timestamp.dt.hour.values,\\n timestamp.dt.day.values,\\n timestamp.dt.week.values,\\n timestamp.dt.month.values,\\n timestamp.dt.year.values,\\n timestamp.dt.weekday.values)\\n\\n # open log file\\n df = pd.read_json(filepath, lines=True)\\n\\n # filter by NextSong action\\n df = df[df['page'] == 'NextSong']\\n\\n # insert time data records\\n time_data = get_timestamp_data(df)\\n column_labels = ('timestamp', 'hour', 'day', 'week', 'month', 'year', 'weekday')\\n time_df = pd.DataFrame(data=dict(zip(column_labels, time_data)))\\n\\n for i, row in time_df.iterrows():\\n cursor.execute(time_table_insert, list(row))\\n\\n # load user table\\n user_columns = ['userId', 'firstName', 'lastName', 'gender', 'level']\\n user_df = df[user_columns]\\n\\n # insert user records\\n for i, row in user_df.iterrows():\\n cursor.execute(user_table_insert, row)\\n\\n # insert songplay records\\n for index, row in df.iterrows():\\n\\n # get song_id and artist_id from song and artist tables\\n cursor.execute(song_select, (row.song, row.artist, row.length))\\n results = cursor.fetchone()\\n\\n if results:\\n song_id, artist_id = results\\n else:\\n song_id, artist_id = None, None\\n\\n # insert songplay record\\n songplay_data = (\\n row['ts'], row['userId'], row['level'], song_id, artist_id, row['sessionId'], row['location'],\\n row['userAgent'])\\n cursor.execute(songplay_table_insert, songplay_data)\",\n \"def s3_process(self, payload, classifier):\\n s3_file_lines = StreamPreParsers.pre_parse_s3(payload.raw_record)\\n for line in s3_file_lines:\\n data = line.rstrip()\\n payload.refresh_record(data)\\n self.process_alerts(classifier, payload, data)\",\n \"def main():\\n spark = create_spark_session()\\n\\n input_data = \\\"s3a://udacitydenanodegree2020/\\\"\\n output_data = \\\"s3a://udacitydenanodegree2020/output/\\\"\\n\\n process_song_data(spark, input_data, output_data) \\n process_log_data(spark, input_data, output_data)\",\n \"def process_log_file(cur, filepath: str) -> None:\\n # open log file\\n df = pd.read_json(filepath, lines=True)\\n\\n # filter by NextSong action\\n df = df[df.page == \\\"NextSong\\\"].copy()\\n\\n # convert timestamp column to datetime\\n df[\\\"ts\\\"] = pd.to_datetime(df[\\\"ts\\\"], unit=\\\"ms\\\")\\n\\n # insert time data records\\n column_labels = [\\\"hour\\\", \\\"day\\\", \\\"week\\\", \\\"month\\\", \\\"year\\\", \\\"weekday\\\"]\\n\\n for column_label in column_labels:\\n if column_label == \\\"week\\\":\\n # FutureWarning: Series.dt.weekofyear and Series.dt.week have been\\n # deprecated. Please use Series.dt.isocalendar().week instead.\\n df[column_label] = df[\\\"ts\\\"].dt.isocalendar().week\\n else:\\n df[column_label] = getattr(df[\\\"ts\\\"].dt, column_label)\\n\\n time_df = pd.DataFrame()\\n time_df[\\\"start_time\\\"] = df[\\\"ts\\\"]\\n time_df = pd.concat([time_df, df[column_labels]], axis=1)\\n time_df.head()\\n\\n for i, row in time_df.iterrows():\\n cur.execute(sql_queries.time_table_insert, list(row))\\n\\n # load user table\\n user_df = df[[\\\"userId\\\", \\\"firstName\\\", \\\"lastName\\\", \\\"gender\\\", \\\"level\\\"]]\\n\\n # insert user records\\n for i, row in user_df.iterrows():\\n cur.execute(sql_queries.user_table_insert, row)\\n\\n # insert songplay records\\n for _, row in df.iterrows():\\n\\n # get songid and artistid from song and artist tables\\n cur.execute(sql_queries.song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n\\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n # insert songplay record\\n songplay_data = (\\n row.ts,\\n row.userId,\\n row.level,\\n songid,\\n artistid,\\n row.sessionId,\\n row.location,\\n row.userAgent,\\n )\\n cur.execute(sql_queries.songplay_table_insert, songplay_data)\",\n \"def load_raw_to_bq(event, context):\\n\\n import os\\n\\n\\n print(f\\\"Processing .....\\\")\\n\\n file = event\\n project = os.environ.get('ENV_PROJECT')\\n dataset = os.environ.get('ENV_DATASET')\\n bucket = file.get(\\\"bucket\\\")\\n tableCsv = file.get(\\\"name\\\")\\n tableDestList = tableCsv.split(\\\".\\\")\\n tableDest = tableDestList[0]\\n table_id = f'{project}.{dataset}.{tableDest}'\\n\\n from Configuration import Configuration\\n\\n Configuration(tableCsv,bucket,table_id)\\n\\n\\n print(f\\\"End Process.\\\")\",\n \"def _ProcessLog(self, log_processor, logfile): # pylint: disable=R0201\\n for line in open(os.path.join(self.data_directory, logfile)):\\n log_processor.ProcessLine(line)\",\n \"def get_data(self):\\n s3 = boto3.resource('s3')\\n for obj in s3.Bucket(self.bucket_name).objects.all():\\n output=str(obj.get()['Body'].read())\\n ip=re.findall( r'[0-9]+(?:\\\\.[0-9]+){3}', output)[0] \\n date=output.split(' [')[-1].split(':')[0] \\n date=datetime.datetime.strptime(date, \\\"%d/%b/%Y\\\")\\n if int(self.check_table(ip, date)) == 0: \\n self.write_to_table(ip, date)\",\n \"def main():\\n spark = create_spark_session()\\n input_data = \\\"s3a://udacity-dend/\\\"\\n output_data = \\\"s3a://dend-bucket-cpm/\\\"\\n\\n process_song_data(spark, input_data, output_data)\\n process_log_data(spark, input_data, output_data)\",\n \"def process_log_file(cur, filepath):\\n df = pd.read_json(filepath, lines=True)\\n\\n df = df[df['page'] == 'NextSong'].astype({'ts':'datetime64[ms]'})\\n\\n t = pd.Series(df['ts'], index=df.index)\\n\\n time_data = [[d, d.hour, d.day, d.week, d.month, d.year, d.weekday()] for d in t]\\n column_labels= ['ts', 'hour', 'day', 'week', 'month', 'year', 'weekday']\\n time_df = pd.DataFrame(data=time_data, columns=column_labels)\\n\\n for i, row in time_df.iterrows():\\n cur.execute(time_table_insert, list(row))\\n\\n columns = ['userId', 'firstName', 'lastName', 'gender', 'level']\\n user_df = df[[*columns]]\\n user_df = user_df[user_df.firstName.notnull()]\\n\\n for i, row in user_df.iterrows():\\n cur.execute(user_table_insert, row)\\n\\n for index, row in df.iterrows():\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n\\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n songplay_data = (row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent)\\n cur.execute(songplay_table_insert, songplay_data)\",\n \"def main(event, context):\\n r = requests.get(yql_url)\\n\\n if r.status_code == 200:\\n content = r.content\\n t = datetime.now()\\n filename = 'iran_' + t.strftime('%Y-%m-%dT%H-%M-%S') + '.json'\\n put_data_in_s3(content, filename)\\n\\n data_dict = json.loads(content)\\n data = data_dict.get('list')\\n\\n # start inserting data into timeseries database\\n write_wind_data_to_csv(data)\\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\\n user=USERNAME, password=PASS)\\n cur = conn.cursor()\\n f = open('/tmp/wind_data.csv', 'r')\\n cur.copy_from(f, 'windts', sep=',', columns=['speed', 'degree',\\n 'utc_time', 'latitude', 'longitude'])\\n conn.commit()\\n try:\\n os.remove('/tmp/wind_data.csv')\\n except OSError:\\n pass\\n cur.close()\\n\\n write_temperature_data_to_csv(data)\\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\\n user=USERNAME, password=PASS)\\n cur = conn.cursor()\\n f = open('/tmp/temperature_data.csv', 'r')\\n cur.copy_from(f, 'temperaturets', sep=',', columns=['temperature'\\n ,'utc_time', 'latitude', 'longitude'])\\n conn.commit()\\n try:\\n os.remove('/tmp/temperature_data.csv')\\n except OSError:\\n pass\\n cur.close()\\n\\n write_pressure_data_to_csv(data)\\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\\n user=USERNAME, password=PASS)\\n cur = conn.cursor()\\n f = open('/tmp/pressure_data.csv', 'r')\\n cur.copy_from(f, 'pressurets', sep=',', columns=['pressure'\\n ,'utc_time', 'latitude', 'longitude'])\\n conn.commit()\\n try:\\n os.remove('/tmp/pressure_data.csv')\\n except OSError:\\n pass\\n cur.close()\\n\\n write_humidity_data_to_csv(data)\\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\\n user=USERNAME, password=PASS)\\n cur = conn.cursor()\\n f = open('/tmp/humidity_data.csv', 'r')\\n cur.copy_from(f, 'humidityts', sep=',', columns=['humidity'\\n ,'utc_time', 'latitude', 'longitude'])\\n conn.commit()\\n try:\\n os.remove('/tmp/humidity_data.csv')\\n except OSError:\\n pass\\n cur.close()\\n\\n write_condition_data_to_csv(data)\\n conn = psycopg2.connect(dbname='climateTSDB', host=DB_HOST_NAME,\\n user=USERNAME, password=PASS)\\n cur = conn.cursor()\\n f = open('/tmp/condition_data.csv', 'r')\\n cur.copy_from(f, 'conditionts', sep=',', columns=['condition'\\n ,'utc_time', 'latitude', 'longitude'])\\n conn.commit()\\n try:\\n os.remove('/tmp/condition_data.csv')\\n except OSError:\\n pass\\n cur.close()\",\n \"def main():\\n spark = create_spark_session()\\n input_data = \\\"s3a://udacity-dend\\\"\\n output_data = \\\"s3a://vivek1bucket\\\"\\n \\n process_song_data(spark, input_data, output_data) \\n process_log_data(spark, input_data, output_data)\",\n \"def process_log_file(cur, filepath):\\r\\n df=pd.read_json(filepath,lines=True)\\r\\n df2=df\\r\\n df=df[df['page']=='NextSong']\\r\\n ser=pd.to_datetime(df['ts'],unit='ms')\\r\\n times=[]\\r\\n for i in ser:\\r\\n times.append([i,i.hour,i.day,i.week,i.month,i.year,i.day_name()])\\r\\n for i in times:\\r\\n cur.execute(time_table_insert,i)\\r\\n df=df[['userId','firstName','lastName','gender','level']]\\r\\n for i,row in df.iterrows():\\r\\n cur.execute(users_table_insert,list(row))\\r\\n for i, row in df2.iterrows():\\r\\n cur.execute(song_select, (row.song, row.artist, row.length))\\r\\n res = cur.fetchone()\\r\\n if res:\\r\\n song_id, artist_id = res\\r\\n else:\\r\\n song_id, artist_id = None, None\\r\\n\\r\\n songplay_data = (\\r\\n i, pd.to_datetime(row.ts, unit='ms'),int(row.userId), row.level, song_id, artist_id, row.sessionId,\\r\\n row.location, row.userAgent)\\r\\n cur.execute(songplays_table_insert, songplay_data)\",\n \"def main(input_filepath, output_filepath):\\n productsDict = dataToDict(input_filepath)\\n productsList = dictToCSV(productsDict)\\n toCSV(productsList, output_filepath)\\n\\n logger = logging.getLogger(__name__)\\n logger.info('making final data set from raw data')\",\n \"def process_log_file(cur, filepath):\\n\\n df = pd.read_json(filepath, lines=True)\\n\\n df = df[df[\\\"page\\\"] == \\\"NextSong\\\"]\\n\\n t = df['ts'] = pd.to_datetime(df['ts'], unit='ms')\\n\\n accessor = t.dt\\n time_data = (t, accessor.hour, accessor.day, accessor.week,\\n accessor.month, accessor.year, accessor.weekday)\\n\\n time_df = pd.DataFrame.from_dict({\\n \\\"timestamp\\\": t,\\n \\\"hour\\\": accessor.hour,\\n \\\"day\\\": accessor.day,\\n \\\"week\\\": accessor.week,\\n \\\"month\\\": accessor.month,\\n \\\"year\\\": accessor.year,\\n \\\"weekday\\\": accessor.weekday\\n })\\n\\n for i, row in time_df.iterrows():\\n cur.execute(time_table_insert, list(row))\\n\\n user_df = df[['userId', 'firstName', 'lastName', 'gender', 'level']]\\n\\n for i, row in user_df.iterrows():\\n cur.execute(user_table_insert, row)\\n\\n for index, row in df.iterrows():\\n\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n\\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n start_time = row[\\\"ts\\\"]\\n user_id = row[\\\"userId\\\"]\\n level = row[\\\"level\\\"]\\n song_id = songid\\n artist_id = artistid\\n session_id = row['sessionId']\\n location = row['location']\\n user_agent = row['userAgent']\\n\\n songplay_data = (start_time, user_id, level, song_id, artist_id, session_id,\\n location, user_agent)\\n cur.execute(songplay_table_insert, songplay_data)\",\n \"def handle_event(event, context):\\n\\n try:\\n print(\\\"Received event: \\\" + json.dumps(event, indent=2))\\n\\n # grab resources section of event, get task execution ids\\n task_execution_arns = event['resources']\\n\\n # now fetch the input filter info from each task_detail, fire off jobs\\n new_files_to_process = []\\n for task_execution_arn in task_execution_arns:\\n # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/datasync.html#DataSync.Client.describe_task_execution\\n response = datasync_client.describe_task_execution(TaskExecutionArn=task_execution_arn)\\n print(\\\"Task execution details: \\\" + str(response))\\n # this will be the location of the data in configured s3 bucket:\\n # 'Includes': [\\n # {\\n # 'FilterType': 'SIMPLE_PATTERN',\\n # 'Value': 'string'\\n # },\\n # ]\\n if len(response['Includes']) > 0:\\n file = response['Includes'][0]['Value']\\n # files typically start with leading '/', strip that leading '/'\\n print(\\\"Got filename:\\\" + file)\\n if file.startswith('/', 0):\\n new_files_to_process.append(file.lstrip('/'))\\n else:\\n new_files_to_process.append(file)\\n else:\\n print(\\\"Response didn't contain Includes files...\\\")\\n\\n if len(new_files_to_process) == 0:\\n print('No files were parsed from input...exiting')\\n return\\n\\n for new_file_to_process in new_files_to_process:\\n state_machine_arn = os.environ['STATE_MACHINE_ARN']\\n payload = {\\\"ObjectName\\\": new_file_to_process}\\n json_payload = json.dumps(payload)\\n print('Starting bcl2fastq with payload %s' % json_payload)\\n #\\n response = step_client.start_execution(stateMachineArn=state_machine_arn, input=json_payload)\\n print(response)\\n\\n except Exception as e:\\n print(e)\\n print('Error handling event. %s' % e)\\n raise e\",\n \"def lambda_handler(event, context): # pylint: disable=too-many-locals,too-many-branches,too-many-statements\\r\\n try: # pylint: disable=too-many-nested-blocks\\r\\n print(\\\"Execution started!\\\")\\r\\n #print(\\\"Event: \\\",event)\\r\\n # Bucket name and Full path for file - where file will be uploded\\r\\n source_bucket_name = event[\\\"detail\\\"][\\\"requestParameters\\\"][\\\"bucketName\\\"]\\r\\n source_key = urllib.parse.unquote_plus(\\r\\n event[\\\"detail\\\"][\\\"requestParameters\\\"][\\\"key\\\"], encoding='utf-8')\\r\\n \\r\\n print(\\\"file_path: \\\",source_key)\\r\\n #Loading master config\\r\\n print(\\\"Loading master_config\\\")\\r\\n audit_config = {}\\r\\n config_path = \\\"./config/\\\" + \\\\\\r\\n os.environ['CCM_ENV'] + \\\"/master_config.json\\\"\\r\\n config_content = open(config_path).read()\\r\\n config_json = json.loads(config_content)\\r\\n audit_config = config_json[\\\"audit_config\\\"]\\r\\n snow_params = config_json[\\\"ERROR_NOTIFICATION_SNOW_PARAMS\\\"]\\r\\n athena_query_param = config_json[\\\"ATHENA_QUERY_PARAMS\\\"]\\r\\n athena_table_params = config_json[\\\"ATHENA_TABLE_PARAMS\\\"]\\r\\n\\r\\n # Audit Parameters Based on the Invoking lambda and its operation involved\\r\\n audit_config[\\\"component_type_code\\\"] = \\\"ETL\\\"\\r\\n audit_config[\\\"component_name\\\"] = \\\"PCP Appflow\\\"\\r\\n audit_config[\\\"source_name\\\"] = \\\"Patient Connections Platform\\\"\\r\\n audit_config[\\\"target_name\\\"] = \\\"Consumer Consent Management\\\"\\r\\n audit_config[\\\"full_file_path\\\"] = \\\"s3://\\\" + \\\\\\r\\n source_bucket_name + \\\"/\\\" + source_key\\r\\n audit_config[\\\"file_version_id\\\"] = \\\"\\\"\\r\\n\\r\\n # Creates Job Entry in ABC Framework\\r\\n print(\\\"audit config::\\\", audit_config)\\r\\n process_execution_id = audit_helper.\\\\\\r\\n invoke_edb_abc_log_process_status_event_job_entry(audit_config)\\r\\n audit_config[\\\"process_execution_id\\\"] = process_execution_id\\r\\n print(\\\"process_execution_id ::\\\", process_execution_id)\\r\\n #print(\\\"source_key: \\\",source_key)\\r\\n s3_write = boto3.client('s3')\\r\\n record_dict = {}\\r\\n file_name = \\\"\\\"\\r\\n final_json = \\\"\\\"\\r\\n # prefix = \\\"\\\"\\r\\n # file_list = []\\r\\n # client = boto3.client(\\\"s3\\\")\\r\\n # result = client.list_objects(Bucket=source_bucket_name, Prefix=source_key, Delimiter='/')\\r\\n # #print(result)\\r\\n # for obj in result.get('CommonPrefixes'):\\r\\n # prefix = obj.get('Prefix')\\r\\n # #print(prefix)\\r\\n # file_list = list_files(client,source_bucket_name,prefix)\\r\\n # for file in file_list:\\r\\n # #print(file)\\r\\n json_read = read_s3_file(source_bucket_name, source_key)\\r\\n data = json.loads(json_read)\\r\\n #print(data)\\r\\n if data != '':\\r\\n record_dict = {k.lower(): v for k, v in data.items()}\\r\\n print(\\\"Record_Dict::\\\",record_dict)\\r\\n event_type_param = {}\\r\\n event_type_list = athena_table_params.keys()\\r\\n print(\\\"event_type_list\\\",event_type_list)\\r\\n for key in event_type_list:\\r\\n print(\\\"key\\\",key)\\r\\n if key in source_key:\\r\\n print(\\\"key\\\",key)\\r\\n event_type_param = athena_table_params[key]\\r\\n print(event_type_param)\\r\\n if \\\"changeeventheader\\\" in record_dict:\\r\\n if record_dict[\\\"changeeventheader\\\"][\\\"changeType\\\"] == \\\"CREATE\\\":\\r\\n #and record_dict[\\\"dtpc_affiliate__c\\\"] == 'US':\\r\\n recordid_create = record_dict[\\\"changeeventheader\\\"][\\\"recordIds\\\"][0]\\r\\n print(recordid_create)\\r\\n if recordid_create != '':\\r\\n last_modified_date = record_dict[\\\"lastmodifieddate\\\"].replace(\\\":\\\",\\\".\\\")\\r\\n create_json = json.dumps(record_dict)\\r\\n final_json = create_json\\r\\n file_name = recordid_create + \\\"-create-\\\" + str(last_modified_date)\\r\\n print(\\\"file_name: \\\",file_name)\\r\\n outbound_path = event_type_param[\\\"folder_path\\\"]\\r\\n final_source_key = outbound_path + '/' + file_name+\\\".json\\\"\\r\\n print(\\\"final_source_key :\\\", final_source_key)\\r\\n s3_write.put_object(\\r\\n Body=final_json, Bucket=source_bucket_name, Key=final_source_key)\\r\\n else:\\r\\n raise Exception(\\\"RecordId is missing: \\\", record_dict)\\r\\n elif record_dict[\\\"changeeventheader\\\"][\\\"changeType\\\"] == \\\"UPDATE\\\":\\r\\n record_ids_list = record_dict[\\\"changeeventheader\\\"][\\\"recordIds\\\"]\\r\\n if len(record_ids_list) != 0:\\r\\n for ele in record_ids_list:\\r\\n print(ele)\\r\\n element = \\\"'\\\" + ele + \\\"'\\\"\\r\\n payload_condition = event_type_param[\\\"recordid_condition\\\"]\\r\\n query = 'SELECT * FROM '+event_type_param[\\\"athena_create_table\\\"]+\\\\\\r\\n ' WHERE lastmodifieddate IN(SELECT max(lastmodifieddate) from '\\\\\\r\\n +event_type_param[\\\"athena_create_table\\\"]+\\\\\\r\\n ', UNNEST(\\\"'+payload_condition[0]+'\\\".\\\"'+payload_condition[1]+\\\\\\r\\n '\\\") AS ln(jsondata) WHERE jsondata IN ('+element+'));'\\r\\n print(query)\\r\\n athena_query_param['athena_query'] = query\\r\\n query_result_record_id = athena_helper.perform_athena_search\\\\\\r\\n (athena_query_param)\\r\\n print(\\\"Athena Query Result for Create Path:::\\\", query_result_record_id)\\r\\n update_json = create_complete_payload(data,query_result_record_id)\\r\\n print(\\\"update_json: \\\",update_json)\\r\\n if len(update_json) != 0:\\r\\n last_modified_date = record_dict[\\\"lastmodifieddate\\\"].replace\\\\\\r\\n (\\\":\\\",\\\".\\\")\\r\\n final_json = json.dumps(update_json)\\r\\n file_name = ele + \\\"-update-\\\" + str(last_modified_date)\\r\\n print(\\\"file_name: \\\",file_name)\\r\\n outbound_path = event_type_param[\\\"folder_path\\\"]\\r\\n final_source_key = outbound_path + '/' + file_name+\\\".json\\\"\\r\\n print(\\\"final_source_key :\\\", final_source_key)\\r\\n s3_write.put_object(\\r\\n Body=final_json, Bucket=source_bucket_name, \\\\\\r\\n Key=final_source_key)\\r\\n else:\\r\\n print(ele,\\\" does not have a create payload\\\")\\r\\n else:\\r\\n raise Exception(\\\"RecordId is missing: \\\", record_dict)\\r\\n else:\\r\\n raise Exception(\\\"ChangeEventHeader is missing: \\\", record_dict)\\r\\n else:\\r\\n raise Exception(\\\"Invalid Payload: \\\", record_dict)\\r\\n\\r\\n except (Exception) as err: # pylint: disable=line-too-long,broad-except\\r\\n print(\\\"Error occured: {0}\\\".format(str(err)))\\r\\n audit_type = \\\"error\\\"\\r\\n error_msg = sys.exc_info()\\r\\n exc_type = error_msg\\r\\n exc_obj = error_msg\\r\\n snow_params[\\\"flag\\\"] = \\\"FAIL\\\"\\r\\n snow_params[\\\"error_message\\\"] = str(exc_obj)\\r\\n snow_params[\\\"error_type\\\"] = str(exc_type)\\r\\n audit_config[\\\"exception_message\\\"] = str(exc_obj)\\r\\n if audit_config != {}:\\r\\n logging.exception(sys.exc_info())\\r\\n audit_helper.invoke_edb_abc_log_process_status_event(\\r\\n audit_type, audit_config) # pylint: disable=line-too-long\\r\\n audit_helper.raise_snow_incident(snow_params)\",\n \"def process_data(data):\\n # Table Name from Json file\\n table_name = data['table_name']\\n\\n # No of Column\\n column_count = data['column_count']\\n\\n # No of Row\\n row_count = data['row_count']\\n\\n # Table columns schema from Json file\\n column_properties = data['column_properties']\\n\\n # Get the row row_properties\\n row_properties = data['row_properties']\\n return table_name, column_count, row_count, column_properties, row_properties\",\n \"def copy_blobs_in_gcp_storage(source_bucket_name):\\n\\n # extract file and convert in dataframe\\n extracted_df = extract()\\n\\n # transform the df\\n transformed_df = transform (extracted_df)\\n\\n # the function loads clean csv content as csv file in clean-zone-bucket\\n load(transformed_df)\\n\\n\\n return \\\"Function executed sucessfully!\\\"\",\n \"def main():\\n spark = create_spark_session()\\n input_data = \\\"s3a://udacity-dend/\\\"\\n output_data = \\\"s3a://udacity-data-lake/output/\\\"\\n\\n process_song_data(spark, input_data, output_data)\\n process_log_data(spark, input_data, output_data)\",\n \"def main():\\n spark = create_spark_session()\\n input_data = \\\"s3a://udacity-dend/\\\"\\n output_data = \\\"data/analytics\\\"\\n \\n process_song_data(spark, input_data, output_data) \\n process_log_data(spark, input_data, output_data)\",\n \"def process_log_data(log_data,\\r\\n seq_counts,\\r\\n mapping_file,\\r\\n fasta_files,\\r\\n qual_files,\\r\\n corrected_bc_count,\\r\\n keep_barcode=False,\\r\\n barcode_type=\\\"golay_12\\\",\\r\\n max_bc_errors=1.5,\\r\\n start_index=1,\\r\\n write_unassigned_reads=False,\\r\\n disable_bc_correction=False,\\r\\n added_demultiplex_field=None,\\r\\n save_barcode_frequencies=False):\\r\\n\\r\\n final_log_data = [\\\"demultiplex_fasta.py log data\\\\n\\\"]\\r\\n final_log_data.append(\\\"Metadata mapping file:\\\\t%s\\\" % mapping_file)\\r\\n final_log_data.append(\\\"Input FASTA file(s):\\\\t%s\\\" %\\r\\n \\\",\\\".join([curr_file.name for curr_file in fasta_files]))\\r\\n if qual_files:\\r\\n final_log_data.append(\\\"Input QUAL file(s):\\\\t%s\\\" %\\r\\n \\\",\\\".join([curr_file.name for curr_file in qual_files]))\\r\\n final_log_data.append(\\\"Total sequences in input files:\\\\t%d\\\" % seq_counts)\\r\\n final_log_data.append(\\\"Retain barcode:\\\\t%s\\\" % keep_barcode)\\r\\n final_log_data.append(\\\"Barcode type:\\\\t%s\\\" % barcode_type)\\r\\n final_log_data.append(\\\"Max barcode error/mismatches allowed:\\\\t%s\\\" %\\r\\n max_bc_errors)\\r\\n final_log_data.append(\\\"Starting sequence identifier:\\\\t%d\\\" % start_index)\\r\\n final_log_data.append(\\r\\n \\\"Write unassigned reads:\\\\t%s\\\" %\\r\\n write_unassigned_reads)\\r\\n final_log_data.append(\\\"Disable barcode correction:\\\\t%s\\\" %\\r\\n disable_bc_correction)\\r\\n final_log_data.append(\\\"Added demultiplex field:\\\\t%s\\\" %\\r\\n added_demultiplex_field)\\r\\n final_log_data.append(\\\"Save barcode frequencies:\\\\t%s\\\\n\\\" %\\r\\n save_barcode_frequencies)\\r\\n\\r\\n final_log_data.append(\\\"Barcodes corrected/not corrected:\\\\t%d/%d\\\" %\\r\\n (corrected_bc_count[0], corrected_bc_count[1]))\\r\\n\\r\\n # Make a list of SampleID/Counts/Barcodes/Added demultiplex for sorting\\r\\n id_counts_bcs = []\\r\\n counts_col = []\\r\\n for curr_key in log_data.keys():\\r\\n id_counts_bcs.append((curr_key.split(',')[-1], log_data[curr_key],\\r\\n ','.join(curr_key.split(',')[0:-1])))\\r\\n counts_col.append(int(log_data[curr_key]))\\r\\n\\r\\n counts_col = array(counts_col)\\r\\n\\r\\n final_log_data.append(\\\"Number of samples in mapping file:\\\\t%d\\\" %\\r\\n len(counts_col))\\r\\n final_log_data.append(\\\"Sample count min/max/mean:\\\\t%d / %d / %3.2f\\\" %\\r\\n (counts_col.min(), counts_col.max(), counts_col.mean()))\\r\\n\\r\\n id_counts_bcs = sorted(id_counts_bcs, key=itemgetter(1), reverse=True)\\r\\n\\r\\n final_log_data.append(\\\"Sample\\\\tSequence Count\\\\tBarcode/Added Demultiplex\\\")\\r\\n for curr_id in id_counts_bcs:\\r\\n final_log_data.append(\\\"%s\\\\t%s\\\\t%s\\\" %\\r\\n (curr_id[0], curr_id[1], curr_id[2]))\\r\\n\\r\\n final_log_data.append(\\\"Seqs written\\\\t%d\\\" % counts_col.sum())\\r\\n final_log_data.append(\\\"Percent of input seqs written\\\\t%3.2f\\\" %\\r\\n (counts_col.sum() / seq_counts))\\r\\n\\r\\n return final_log_data\",\n \"def execute(self, context): \\n aws_hook = AwsHook(self.aws_credentials)\\n credentials = aws_hook.get_credentials()\\n redshift = PostgresHook(self.redshift_conn_id)\\n execution_date = context['execution_date']\\n \\n self.log.info(f\\\"Truncating {self.table}\\\")\\n redshift.run(f\\\"TRUNCATE TABLE {self.table}\\\")\\n \\n \\n self.log.info(f\\\"Inserting data into {self.table}\\\")\\n s3_path = f\\\"s3://{self.s3_bucket}/{self.s3_key}\\\"\\n\\n if self.s3_key == \\\"log_data\\\":\\n year = execution_date.year\\n month = execution_date.month\\n \\n s3_path = '/'.join([s3_path, str(year), str(month)])\\n \\n formatted_sql = StageToRedshiftOperator.copy_sql.format(\\n self.table,\\n s3_path,\\n credentials.access_key,\\n credentials.secret_key,\\n self.file_format,\\n self.format_path\\n )\\n \\n redshift.run(formatted_sql)\",\n \"def runDataExtraction():\\r\\n config = CONFIG['steps']['DataExtraction']\\r\\n ci = config['inputs']\\r\\n co = config['outputs']\\r\\n columns = ci['columns']\\r\\n nrows = ci['nrows']\\r\\n input_bucket = ci['bucket']\\r\\n no_of_files = ci['no_of_files']\\r\\n\\r\\n output_bucket = co['bucket']\\r\\n csv_name_prefix = co['csv_name_prefix']\\r\\n\\r\\n minio_config = CONFIG['artifacts']['minio']\\r\\n minioClient = create_minio_client(minio_config[\\\"endpoint_url\\\"],\\r\\n access_key=minio_config[\\\"access_key\\\"],\\r\\n secret_key=minio_config[\\\"secret_key\\\"],\\r\\n secure=minio_config['secure'])\\r\\n\\r\\n boto_client = boto3.client(\\\"s3\\\",\\r\\n endpoint_url=minio_config[\\\"endpoint_url\\\"],\\r\\n aws_access_key_id=minio_config[\\\"access_key\\\"],\\r\\n aws_secret_access_key=minio_config[\\\"secret_key\\\"],\\r\\n region_name=minio_config[\\\"region_name\\\"])\\r\\n\\r\\n zip_files = get_files(input_bucket, boto_client, file_type='zip')\\r\\n\\r\\n no_of_files_to_process = no_of_files if no_of_files is not None else len(\\r\\n zip_files)\\r\\n for zip_file in tqdm(zip_files[:no_of_files_to_process], total=no_of_files_to_process):\\r\\n process_file(zip_file, input_bucket, output_bucket, minioClient, columns,\\r\\n nrows=nrows, output_csv_name_prefix=csv_name_prefix)\",\n \"def BqTableDataFileProcessor(file_arg):\\n data_insert_request_type = GetApiMessage('TableDataInsertAllRequest')\\n insert_row_type = data_insert_request_type.RowsValueListEntry\\n data_row_type = GetApiMessage('JsonObject')\\n\\n try:\\n data_json = yaml.load(file_arg)\\n\\n if not data_json or not isinstance(data_json, list):\\n raise TableDataFileError(\\n 'Error parsing data file: no data records defined in file')\\n\\n rows = []\\n for row in data_json:\\n rows.append(insert_row_type(json=encoding.DictToMessage(\\n row, data_row_type)))\\n\\n return rows\\n except yaml.YAMLParseError as ype:\\n raise TableDataFileError('Error parsing data file [{}]'.format(ype))\",\n \"def process_log_file(cur, filepath):\\n # open log file\\n df = get_file_df(filepath)\\n\\n # filter by NextSong action\\n df = df[df['page'] == 'NextSong']\\n\\n # convert timestamp column to datetime\\n df['ts'] = df['ts'].apply(lambda x: datetime.datetime.fromtimestamp(x/1000)) \\n t = df\\n \\n time_data = []\\n for td in t['ts']:\\n wd = True if td.weekday() <=6 else False\\n time_data.append([str(td.time()), td.hour, td.day, td.week, td.month, td.year, wd])\\n column_labels = ('start_time', 'hour', 'day', 'week', 'month', 'year', 'weekday')\\n\\n # insert time data records\\n time_df = pd.DataFrame(time_data, columns=column_labels)\\n\\n for i, row in time_df.iterrows():\\n cur.execute(time_table_insert, list(row))\\n\\n # load user table\\n user_df = df[['userId', 'firstName', 'lastName', 'gender', 'level']].copy()\\n\\n # insert user records\\n for i, row in user_df.iterrows():\\n cur.execute(user_table_insert, row)\\n\\n # insert songplay records\\n for index, row in df.iterrows():\\n \\n # get songid and artistid from song and artist tables\\n cur.execute(song_select, (row.song, row.artist, row.length))\\n results = cur.fetchone()\\n \\n if results:\\n songid, artistid = results\\n else:\\n songid, artistid = None, None\\n\\n # insert songplay record\\n #user_id, level, song_id, artist_id, session_id, location, user_agent\\n songplay_data = [row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent]\\n cur.execute(songplay_table_insert, songplay_data)\",\n \"def process_log_event(event, context):\\n\\n with open('config.json') as fh:\\n config = json.load(fh)\\n serialized = event['awslogs'].pop('data')\\n data = json.loads(zlib.decompress(\\n base64.b64decode(serialized), 16+zlib.MAX_WBITS))\\n message = [\\n \\\"An error was detected\\\",\\n \\\"\\\",\\n \\\"Log Group: %s\\\" % data['logGroup'],\\n \\\"Log Stream: %s\\\" % data['logStream'],\\n \\\"Log Owner: %s\\\" % data['owner'],\\n \\\"\\\",\\n \\\"Log Contents\\\",\\n \\\"\\\"]\\n\\n for evt in data['logEvents']:\\n message.append(message_event(evt))\\n message.append(\\\"\\\")\\n\\n params = dict(\\n TopicArn=config['topic'],\\n Subject=config['subject'],\\n Message='\\\\n'.join(message))\\n sns.publish(**params)\",\n \"def convert_to_json(basepath, sendto):\\n\\n logger = logging.getLogger('WikiLog')\\n\\n k = bucket.new_key(basepath)\\n\\n filenames = []\\n year = month = day = hrs = ''\\n\\n for key in bucket.list():\\n thisfile = key.name.encode('utf-8')\\n if 'projectviews' not in thisfile and 'sql' not in thisfile and '.gz' in thisfile and thisfile.startswith(basepath):\\n # S3 key name is of the format kt-wiki/pageviews/2016/2016-06/pageviews-20160601-000000.gz\\n # Split by / to get last element\\n filenames.append(thisfile)\\n logger.info(\\\"Processing file: {}\\\".format(thisfile))\\n fname = thisfile.split('/')\\n\\n # Get content from filename and save to local\\n # Split again to Grab year, month, day, hour value from filename\\n key.get_contents_to_filename('/home/ubuntu/WikiView/data/' + fname[-1])\\n fname1 = fname[-1]\\n data_time = fname1[:-3].split('-')\\n year, month, day, hrs = data_time[1][:4], data_time[1][4:6], data_time[1][-2:], data_time[-1]\\n\\n docname = 'pageviews-' + year + '-' + month + '-' + day + '-' + hrs + '.json'\\n dictlist = []\\n\\n # save file from s3 to local, read, write to json, push json to s3\\n with open(docname, 'w') as fp:\\n #\\n with gzip.open('/home/ubuntu/WikiView/data/'+fname[-1],'r') as fin:\\n for line in fin:\\n line = line.split(' ')\\n doc = {}\\n doc['ymdh'] = year + '-' + month + '-' + day + '-' + hrs\\n try:\\n # format: project, title, views, bytes ~ en Main_Page 242332 4737756101\\n prj, title, vcount = line[0], line[1], line[2]\\n doc['prj'] = prj\\n doc['title'] = title\\n doc['vcount'] = vcount\\n json.dump(doc,fp)\\n fp.write('\\\\n')\\n except:\\n logger.error('Error reading gzip file {} at line: {}'.format(thisfile, line))\\n pass\\n# sys.exc_clear()\\n\\n # Now, save the json file to \\n key_name = 'pageviews-' + year + '-' + month + '-' + day + '-' + hrs + '.json'\\n full_key_name = os.path.join(sendto, key_name)\\n k = bucket.new_key(full_key_name)\\n\\n logger.info(\\\"Sending json file to S3: {}\\\".format(docname))\\n k.set_contents_from_filename(key_name)\\n\\n # Remove temp file\\n logger.info(\\\"Removing temp file: {} {}\\\".format('/home/ubuntu/WikiView/data/', fname[-1]))\\n os.remove('/home/ubuntu/WikiView/data/'+fname[-1])\\n logger.info(\\\"Removing temp file: {}\\\".format(key_name))\\n os.remove(key_name)\\n logger.info('Finished!!!')\",\n \"def main(input_filepath, output_filepath):\\n logger = logging.getLogger(__name__)\\n logger.info('making final data set from raw data')\\n\\n conn = sqlite3.connect('../raw/td_V2.db')\\n git_commits = pd.read_sql_query(\\\"SELECT * FROM GIT_COMMITS\\\",conn)\\n szz_fault_inducing_commits = pd.read_sql_query(\\\"SELECT * FROM szz_fault_inducing_commits\\\",conn)\\n refactoring_miner = pd.read_sql_query(\\\"SELECT * FROM refactoring_miner\\\",conn)\\n refactoring_miner = refactoring_miner[refactoring_miner[\\\"COMMIT_HASH\\\"].isin(git_commits[\\\"COMMIT_HASH\\\"])]\\n git_commits_changes = pd.read_sql_query(\\\"SELECT * FROM GIT_COMMITS_CHANGES\\\", conn)\\n git_commits_changes = git_commits_changes[git_commits_changes[\\\"COMMIT_HASH\\\"].isin(refactoring_miner[\\\"COMMIT_HASH\\\"])]\\n\\n preprocess(git_commits, szz_fault_inducing_commits, refactoring_miner, git_commits_changes)\",\n \"def get_raw_data(report, bucket, replay_path, query):\\n\\n logger = logging.getLogger(\\\"SimpleReplayLogger\\\")\\n s3_client = boto3.client('s3')\\n try:\\n response = s3_client.get_object(Bucket=bucket.get('bucket_name'), Key=f\\\"{replay_path}/raw_data/{query}000\\\")\\n except Exception as e:\\n logger.error(f\\\"Unable to get raw data from S3. Results for {query} not found. {e}\\\")\\n df = pd.read_csv(response.get(\\\"Body\\\")).fillna(0)\\n logger.debug(f\\\"Parsing results from '{query}' query.\\\")\\n if query == 'latency_distribution':\\n report.feature_graph = df\\n else:\\n for t, vals in report.tables.items():\\n if vals.get('sql') == query:\\n vals['data'] = read_data(t, df, vals.get('columns'), report)\",\n \"def load_dict_to_delta_table(spark, s3_data_bucket, table_schema, table_name, data, overwrite=False):\\n table_to_col_names_dict = {}\\n table_to_col_names_dict[\\\"transaction_fabs\\\"] = TRANSACTION_FABS_COLUMNS\\n table_to_col_names_dict[\\\"transaction_fpds\\\"] = TRANSACTION_FPDS_COLUMNS\\n table_to_col_names_dict[\\\"transaction_normalized\\\"] = list(TRANSACTION_NORMALIZED_COLUMNS)\\n table_to_col_names_dict[\\\"awards\\\"] = list(AWARDS_COLUMNS)\\n table_to_col_names_dict[\\\"financial_accounts_by_awards\\\"] = list(FINANCIAL_ACCOUNTS_BY_AWARDS_COLUMNS)\\n\\n table_to_col_info_dict = {}\\n for tbl_name, col_info in zip(\\n (\\\"transaction_fabs\\\", \\\"transaction_fpds\\\"), (TRANSACTION_FABS_COLUMN_INFO, TRANSACTION_FPDS_COLUMN_INFO)\\n ):\\n table_to_col_info_dict[tbl_name] = {}\\n for col in col_info:\\n table_to_col_info_dict[tbl_name][col.dest_name] = col\\n\\n # Make sure the table has been created first\\n call_command(\\n \\\"create_delta_table\\\",\\n \\\"--destination-table\\\",\\n table_name,\\n \\\"--alt-db\\\",\\n table_schema,\\n \\\"--spark-s3-bucket\\\",\\n s3_data_bucket,\\n )\\n\\n if data:\\n insert_sql = f\\\"INSERT {'OVERWRITE' if overwrite else 'INTO'} {table_schema}.{table_name} VALUES\\\\n\\\"\\n row_strs = []\\n for row in data:\\n value_strs = []\\n for col_name in table_to_col_names_dict[table_name]:\\n value = row.get(col_name)\\n if isinstance(value, (str, bytes)):\\n # Quote strings for insertion into DB\\n value_strs.append(f\\\"'{value}'\\\")\\n elif isinstance(value, (date, datetime)):\\n # Convert to string and quote\\n value_strs.append(f\\\"\\\"\\\"'{value.isoformat()}'\\\"\\\"\\\")\\n elif isinstance(value, bool):\\n value_strs.append(str(value).upper())\\n elif isinstance(value, (Sequence, Set)):\\n # Assume \\\"sequences\\\" must be \\\"sequences\\\" of strings, so quote each item in the \\\"sequence\\\"\\n value = [f\\\"'{item}'\\\" for item in value]\\n value_strs.append(f\\\"ARRAY({', '.join(value)})\\\")\\n elif value is None:\\n col_info = table_to_col_info_dict.get(table_name)\\n if (\\n col_info\\n and col_info[col_name].delta_type.upper() == \\\"BOOLEAN\\\"\\n and not col_info[col_name].handling == \\\"leave_null\\\"\\n ):\\n # Convert None/NULL to false for boolean columns unless specified to leave the null\\n value_strs.append(\\\"FALSE\\\")\\n else:\\n value_strs.append(\\\"NULL\\\")\\n else:\\n value_strs.append(str(value))\\n\\n row_strs.append(f\\\" ({', '.join(value_strs)})\\\")\\n\\n sql = \\\"\\\".join([insert_sql, \\\",\\\\n\\\".join(row_strs), \\\";\\\"])\\n spark.sql(sql)\",\n \"def format_data(df):\\n\\n if len(df) == 0:\\n print('No logs found, please check your data')\\n return None\\n\\n # Separate the fields in request and response\\n print('Extracting request and response ...')\\n df1 = pd.concat([df.drop(['request', 'response'], axis=1).reset_index(drop=True),\\n df['request'].apply(pd.Series).add_prefix('request_').reset_index(drop=True),\\n pd.DataFrame(df['response']\\n .tolist()).add_prefix('response_')], axis=1) # type: pd.DataFrame\\n df1['request_input'] = pd.json_normalize(df['request'])['input.text']\\n\\n # Add context and output fields\\n print('Extracting context and output ...')\\n df2 = pd.concat([df1.drop(['response_context', 'response_output'], axis=1),\\n df1['response_context'].apply(pd.Series).add_prefix('response_context_'),\\n pd.DataFrame(df1['response_output'].tolist()).add_prefix('response_')],\\n axis=1) # type: pd.DataFrame\\n # Add context_system fields\\n df3 = pd.concat([df2.drop(['response_context_system'], axis=1),\\n df2['response_context_system'].apply(pd.Series).add_prefix('response_')],\\n axis=1) # type: pd.DataFrame\\n\\n if 'response_context_response_context_IntentStarted' in df3.columns \\\\\\n and 'response_context_response_context_IntentCompleted' in df3.columns:\\n cols = ['log_id', 'response_timestamp', 'response_context_conversation_id', 'request_input', 'response_text',\\n 'response_intents', 'response_entities', 'response_nodes_visited', 'response_dialog_request_counter',\\n 'response_dialog_stack', 'response_dialog_turn_counter',\\n 'response_context_response_context_IntentStarted', 'response_context_response_context_IntentCompleted']\\n else:\\n cols = ['log_id', 'response_timestamp', 'response_context_conversation_id', 'request_input', 'response_text',\\n 'response_intents', 'response_entities', 'response_nodes_visited', 'response_dialog_request_counter',\\n 'response_dialog_stack', 'response_dialog_turn_counter']\\n\\n print('Extracting intents ...')\\n # Select a few required columns\\n df4 = df3[cols].copy(deep=True) # type: pd.DataFrame\\n # Limit fetched intents to a maximum value of 3\\n df4.loc[:, 'response_intents'] = df4['response_intents'].apply(lambda x: x[:3])\\n # Separate intents into different fields\\n df5 = pd.concat([df4.drop(['response_intents'], axis=1),\\n pd.DataFrame(df4['response_intents'].values.tolist()).add_prefix(\\n 'response_intent_')], axis=1) # type: pd.DataFrame\\n # Check if at least 3 intents are identified\\n if 'response_intent_2' in df5.columns:\\n # Put the 3 intents and confidences into separate fields\\n df6 = pd.concat([df5.drop(['response_intent_0', 'response_intent_1',\\n 'response_intent_2'], axis=1),\\n df5['response_intent_0'].apply(pd.Series).add_prefix('response.top_intent_'),\\n df5['response_intent_1'].apply(pd.Series).add_prefix('Intent 2 '),\\n df5['response_intent_2'].apply(pd.Series).add_prefix('Intent 3 ')],\\n axis=1) # type: pd.DataFrame\\n # Convert confidence to numeric type\\n cols = ['response.top_intent_confidence', 'Intent 2 confidence', 'Intent 3 confidence']\\n df6[cols] = df6[cols].apply(pd.to_numeric, errors='coerce', axis=1)\\n # Add confidence gap column\\n df6['Confidence gap (between 1 and 2)'] = df6['response.top_intent_confidence'] - df6['Intent 2 confidence']\\n elif 'response_intent_1' in df5.columns:\\n # Put the 3 intents and confidences into separate fields\\n df6 = pd.concat([df5.drop(['response_intent_0', 'response_intent_1'], axis=1),\\n df5['response_intent_0'].apply(pd.Series).add_prefix('response.top_intent_'),\\n df5['response_intent_1'].apply(pd.Series).add_prefix('Intent 2 ')],\\n axis=1) # type: pd.DataFrame\\n # Convert confidence to numeric type\\n cols = ['response.top_intent_confidence', 'Intent 2 confidence']\\n df6[cols] = df6[cols].apply(pd.to_numeric, errors='coerce', axis=1)\\n df6['Intent 3 intent'] = ''\\n df6['Intent 3 confidence'] = ''\\n # Add confidence gap column\\n df6['Confidence gap (between 1 and 2)'] = df6['response.top_intent_confidence'] - df6['Intent 2 confidence']\\n else:\\n # Create the top intent and its confidence column\\n df6 = pd.concat([df5.drop(['response_intent_0'], axis=1),\\n df5['response_intent_0'].apply(pd.Series).add_prefix('response.top_intent_')],\\n axis=1) # type: pd.DataFrame\\n # df6['Confidence gap (between 1 and 2)'] = ''\\n # df6['Intent 2 intent'] =''\\n # df6['Intent 2 confidence'] = ''\\n # df6['Intent 3 intent'] =''\\n # df6['Intent 3 confidence'] = ''\\n new_cols_list = ['Confidence gap (between 1 and 2)', 'Intent 2 intent', 'Intent 2 confidence',\\n 'Intent 3 intent', 'Intent 3 confidence']\\n\\n df6.reindex(columns=[*df6.columns.tolist(), *new_cols_list], fill_value='')\\n\\n # Rename columns\\n if 'response_context_response_context_IntentStarted' in df6.columns \\\\\\n and 'response_context_response_context_IntentCompleted' in df6.columns:\\n df6.rename(columns={'response_nodes_visited': 'response.output.nodes_visited_s',\\n 'response_context_conversation_id': 'response.context.conversation_id',\\n 'response_timestamp': 'response.timestamp',\\n 'response_context_response_context_IntentStarted': 'response_context_IntentStarted',\\n 'response_context_response_context_IntentCompleted': 'response_context_IntentCompleted'},\\n inplace=True)\\n else:\\n df6.rename(columns={'response_nodes_visited': 'response.output.nodes_visited_s',\\n 'response_context_conversation_id': 'response.context.conversation_id',\\n 'response_timestamp': 'response.timestamp'},\\n inplace=True)\\n # Change format of numeric and date columns\\n df6['response.top_intent_confidence'] = pd.to_numeric(df6['response.top_intent_confidence'])\\n df6['response.timestamp'] = pd.to_datetime(df6['response.timestamp'])\\n df6['Date'] = [datetime.datetime.date(d) for d in df6['response.timestamp']] # extracting date from timestamp\\n df6['Customer ID (must retain for delete)'] = '' # Adding a column to retain customer id\\n\\n print('Completed!')\\n return df6\",\n \"def stream_to_s3(task_name,data,header,timestamp_suffix,**kwargs):\\n if kwargs:\\n file = '_'.join([task_name,timestamp_suffix,str(kwargs['batch_id'])])+'.csv'\\n else:\\n file = '_'.join([task_name,timestamp_suffix])+'.csv'\\n\\n f = io.StringIO()\\n with smart_open.open('s3://{bucket_name}/{task_name}/{file}'.format(bucket_name=bucket_name,task_name=task_name,file=file), 'w') as fout:\\n logger.info('Streaming file contents to S3')\\n _writer = csv.writer(fout)\\n _writer.writerow(header)\\n fout.write(f.getvalue())\\n \\n for row in data:\\n f.seek(0)\\n f.truncate(0)\\n _writer.writerow(row)\\n fout.write(f.getvalue())\\n \\n f.close()\\n logger.info('Complete')\\n\\n return file\",\n \"def process_data(self, data):\\n try:\\n payload = self.extract(data)\\n except (ValueError, InvalidToken) as doh:\\n self.log.error('Error: {}, Data: {}'.format(doh, data))\\n else:\\n fields = {}\\n tags = {}\\n # writing strings to a field in Influx requires a double-quote\\n tags['username'] = '\\\"{}\\\"'.format(payload['user'])\\n # Dumbass Influx doesn't let you group by fields or aggregate tags...\\n # I want to count the unique occurrences of a user over a period of time\\n # to show current connected user counts, *and* be able to group by\\n # those usernames over time to show specific user usage. Wish I\\n # used TimescaleDB instead of InfluxDB\\n fields['user'] = '\\\"{}\\\"'.format(payload.pop('user'))\\n fields['source'] = '\\\"{}\\\"'.format(payload.pop('source'))\\n fields['target'] = '\\\"{}\\\"'.format(payload.pop('target'))\\n fields['packets'] = 1 # each event represents a single packet\\n timestamp = payload.pop('time')\\n self.influx.write(fields=fields, tags=tags, timestamp=timestamp)\",\n \"def process_logs(logs):\\n all_data = {}\\n for log in logs:\\n with open(log) as f:\\n data = json.load(f)\\n scenario = data[0].get(\\\"scenario\\\", None)\\n if scenario is None:\\n # No scenario name, no way to organize the data\\n continue\\n\\n # Use the log's date as the run identifier\\n # This assumes the format is SCENARIO-YYYY-MM-DD.json\\n # NOTE: This may not match the GitHub Action run dates due to tests taking\\n # a very long time.\\n day = datetime.strptime(log[1+len(scenario):-5], \\\"%Y-%m-%d\\\").strftime(\\\"%Y%m%d\\\")\\n if day not in all_data:\\n all_data[day] = {}\\n\\n # Group them by scenario, assume each file is from one scenario per day\\n all_data[day][scenario] = data\\n return all_data\",\n \"def dump_job_data(s3, bucket, key, ecosystem, package, version):\\n data = s3.read_object(bucket, key)\\n timestamp_str = datetime.datetime.utcnow().strftime(\\\"%Y-%m-%dT%H:%M:%S.%f\\\")\\n filename = \\\"s3_data_{e}_{p}_{v}_{t}.json\\\".format(e=ecosystem,\\n p=package,\\n v=version,\\n t=timestamp_str)\\n with open(filename, 'w') as fout:\\n json.dump(data, fout)\",\n \"def main():\\n conn = psycopg2.connect(\\\"host=127.0.0.1 dbname=sparkifydb user=student password=student\\\")\\n cur = conn.cursor()\\n\\n process_data(cur, conn, filepath='data/song_data', func=process_song_file)\\n print('song file processing is complete')\\n process_data(cur, conn, filepath='data/log_data', func=process_log_file)\\n print('log file processing is complete')\\n conn.close()\",\n \"def deduce_schema(self, input_data, *, schema_map=None):\\n\\n if self.input_format == 'csv':\\n if self.csv_dialect:\\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\\n else:\\n reader = csv.DictReader(input_data)\\n elif self.input_format == 'json' or self.input_format is None:\\n reader = json_reader(input_data)\\n elif self.input_format == 'dict':\\n reader = input_data\\n else:\\n raise Exception(f\\\"Unknown input_format '{self.input_format}'\\\")\\n\\n if schema_map is None:\\n schema_map = OrderedDict()\\n\\n try:\\n for json_object in reader:\\n\\n # Print a progress message periodically.\\n self.line_number += 1\\n if self.line_number % self.debugging_interval == 0:\\n logging.info(f'Processing line {self.line_number}')\\n\\n # Deduce the schema from this given data record.\\n if isinstance(json_object, dict):\\n self.deduce_schema_for_record(\\n json_object=json_object,\\n schema_map=schema_map,\\n )\\n elif isinstance(json_object, Exception):\\n self.log_error(\\n f'Record could not be parsed: Exception: {json_object}'\\n )\\n if not self.ignore_invalid_lines:\\n raise json_object\\n else:\\n self.log_error(\\n 'Record should be a JSON Object '\\n f'but was a {type(json_object)}'\\n )\\n if not self.ignore_invalid_lines:\\n raise Exception(f'Record must be a JSON Object '\\n f'but was a {type(json_object)}')\\n finally:\\n logging.info(f'Processed {self.line_number} lines')\\n\\n return schema_map, self.error_logs\",\n \"def main(input_filepath, output_filepath):\\n logger = logging.getLogger(__name__)\\n logger.info('making final data set from raw data')\\n\\n # Get the data/raw/git-refactoring-commits-raw.csv file\\n dataset = pd.read_csv(input_filepath, usecols=['Message', 'CommitSHA', 'IsRefactoring'])\\n logger.info('Loaded data file ' + input_filepath + ' with ' + str(len(dataset)) + ' rows')\\n\\n logger.info('Applying pre-processing steps on the \\\"Message\\\" column...')\\n dataset['Message'] = dataset['Message'].apply(preprocess)\\n\\n # Save the processed subset on data data/processed/git-refactoring-commits.csv\\n logger.info('Saved processed results on ' + output_filepath + ' with ' + str(len(dataset)) + ' rows')\\n dataset.to_csv(output_filepath, encoding='utf-8', index=False)\",\n \"def create_dataset(input_file_path, output_file_path):\\n col_index_map = {'user_id': 0, 'session_id': 1, 'timestamp': 2, 'step': 3, 'action_type': 4, 'reference': 5,\\n 'platform': 6, 'city': 7, 'device': 8,\\n 'current_filters': 9, 'impressions': 10, 'prices': 11}\\n flat_dict = dict()\\n with open(input_file_path, 'r') as csvFile:\\n reader = csv.reader(csvFile)\\n header = next(reader)\\n col_names = [col_name for col_name in col_index_map.keys()]\\n col_names.pop(0)\\n index = 0\\n for row in tqdm(reader):\\n if len(flat_dict) > 40000:\\n index += 1\\n with open(output_file_path + \\\"_\\\" + str(index) + \\\".json\\\", \\\"w\\\") as file:\\n json.dump(flat_dict, file)\\n print(\\\" JSON : \\\", index)\\n flat_dict = dict()\\n col_values = [row[col_index_map[c_n]] for c_n in col_names]\\n dict_for_each_row = dict(zip(col_names, col_values))\\n to_list = dict_for_each_row['impressions']\\n dict_for_each_row['impressions'] = to_list.split('|')\\n to_list = dict_for_each_row['prices']\\n dict_for_each_row['prices'] = to_list.split('|')\\n user_id = row[col_index_map['user_id']]\\n if user_id in flat_dict:\\n flat_dict[user_id].append(dict_for_each_row)\\n else:\\n flat_dict[user_id] = [dict_for_each_row]\\n\\n print(\\\"Output is Saved\\\")\",\n \"def main():\\n spark = create_spark_session()\\n input_data = \\\"s3a://udacity-dend/\\\"\\n output_data = \\\"s3a://udacity-nanodegree-data-engineer/\\\"\\n \\n process_song_data(spark, input_data, output_data) \\n process_log_data(spark, input_data, output_data)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7315748","0.73054594","0.6975627","0.69641143","0.6958745","0.6947524","0.6941278","0.69293684","0.6911164","0.6907852","0.686215","0.6784478","0.6759412","0.6692344","0.66841125","0.6366269","0.62756515","0.6237044","0.62061685","0.61751795","0.59972167","0.5939527","0.5866242","0.57967514","0.567509","0.565705","0.5657001","0.5622568","0.56209975","0.5620446","0.5595221","0.5591331","0.5585552","0.55787104","0.55776334","0.5576928","0.5568119","0.55587995","0.555448","0.5544945","0.554229","0.5541075","0.5537971","0.55029804","0.5502841","0.54942673","0.5483128","0.5476927","0.5473878","0.54663646","0.54637015","0.54470223","0.5416641","0.5385047","0.5379023","0.5376929","0.5370862","0.5325947","0.5314946","0.5303931","0.5295463","0.52649665","0.5258383","0.52415574","0.52364767","0.52061397","0.51959574","0.5190549","0.51582855","0.5149686","0.5148432","0.50758964","0.50707114","0.5065309","0.5039602","0.5038143","0.50035596","0.49930972","0.4986368","0.49770397","0.49699938","0.49614275","0.49336246","0.49171922","0.49049136","0.49039418","0.4896005","0.48690093","0.4857497","0.48566782","0.485383","0.48424017","0.48398623","0.4828445","0.48282695","0.48234314","0.48178047","0.4809939","0.47976464","0.47946277"],"string":"[\n \"0.7315748\",\n \"0.73054594\",\n \"0.6975627\",\n \"0.69641143\",\n \"0.6958745\",\n \"0.6947524\",\n \"0.6941278\",\n \"0.69293684\",\n \"0.6911164\",\n \"0.6907852\",\n \"0.686215\",\n \"0.6784478\",\n \"0.6759412\",\n \"0.6692344\",\n \"0.66841125\",\n \"0.6366269\",\n \"0.62756515\",\n \"0.6237044\",\n \"0.62061685\",\n \"0.61751795\",\n \"0.59972167\",\n \"0.5939527\",\n \"0.5866242\",\n \"0.57967514\",\n \"0.567509\",\n \"0.565705\",\n \"0.5657001\",\n \"0.5622568\",\n \"0.56209975\",\n \"0.5620446\",\n \"0.5595221\",\n \"0.5591331\",\n \"0.5585552\",\n \"0.55787104\",\n \"0.55776334\",\n \"0.5576928\",\n \"0.5568119\",\n \"0.55587995\",\n \"0.555448\",\n \"0.5544945\",\n \"0.554229\",\n \"0.5541075\",\n \"0.5537971\",\n \"0.55029804\",\n \"0.5502841\",\n \"0.54942673\",\n \"0.5483128\",\n \"0.5476927\",\n \"0.5473878\",\n \"0.54663646\",\n \"0.54637015\",\n \"0.54470223\",\n \"0.5416641\",\n \"0.5385047\",\n \"0.5379023\",\n \"0.5376929\",\n \"0.5370862\",\n \"0.5325947\",\n \"0.5314946\",\n \"0.5303931\",\n \"0.5295463\",\n \"0.52649665\",\n \"0.5258383\",\n \"0.52415574\",\n \"0.52364767\",\n \"0.52061397\",\n \"0.51959574\",\n \"0.5190549\",\n \"0.51582855\",\n \"0.5149686\",\n \"0.5148432\",\n \"0.50758964\",\n \"0.50707114\",\n \"0.5065309\",\n \"0.5039602\",\n \"0.5038143\",\n \"0.50035596\",\n \"0.49930972\",\n \"0.4986368\",\n \"0.49770397\",\n \"0.49699938\",\n \"0.49614275\",\n \"0.49336246\",\n \"0.49171922\",\n \"0.49049136\",\n \"0.49039418\",\n \"0.4896005\",\n \"0.48690093\",\n \"0.4857497\",\n \"0.48566782\",\n \"0.485383\",\n \"0.48424017\",\n \"0.48398623\",\n \"0.4828445\",\n \"0.48282695\",\n \"0.48234314\",\n \"0.48178047\",\n \"0.4809939\",\n \"0.47976464\",\n \"0.47946277\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.66948694"},"document_rank":{"kind":"string","value":"13"}}},{"rowIdx":1393,"cells":{"query":{"kind":"string","value":"View function that handles inserting new comments via POST data (form submission)"},"document":{"kind":"string","value":"def post_comment_form(request):\n try:\n comment, previous_version = get_comment(request)\n except InvalidCommentException as e:\n raise\n\n parent_comment = comment.parent\n tree_root = parent_comment.get_root()\n parent_object = tree_root.content_object\n if not user_can_post_comment(request, comment):\n raise Exception(\"User can't create comments\")\n\n if is_past_max_depth(comment):\n raise Exception(\"Max depth reached\")\n\n # If the comment object (NOT the message) hasn't been saved yet...\n if comment._state.adding == True:\n comment = add_comment(comment)\n\n # Everything has checked out, so we save the new version and return the appropriate response\n version_form, new_version = create_new_version(request, comment)\n\n return comment"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def comments_new():\n comment = {\n \"title\": request.form.get(\"title\"),\n \"content\": request.form.get(\"content\"),\n \"playlist_id\": ObjectId(request.form.get(\"playlist._id\")),\n }\n print(comment)\n comment_id = db.comments.insert_one(comment).inserted_id\n return redirect(\n url_for(\"playlists.playlists_show\", playlist_id=request.form.get(\"playlist._id\"))\n )","def save_comments():\n potential_deal_id = int(request.form.get(\"id\"))\n action = request.form.get(\"action\")\n if action.lower() == \"none\":\n action = None\n comments = request.form.get(\"comments\")\n db_handler = DBHandler()\n db_handler.update_by_id(potential_deal_id, action, comments)\n # return redirect(url_for(\"home\"))\n return jsonify({\"success\": True}), 200","def add_comment(request):\n if request.method != 'POST':\n return HttpResponseRedirect(reverse('wainz.views.composite'))\n else:\n img_id = request.POST['id']\n try:\n img = Image.objects.get(pk=img_id)\n except:\n return HttpResponseRedirect(reverse('wainz.views.composite'))\n comment_text = request.POST['comment']\n #TODO sanitize input\n comment = ImageComment()\n comment.submission_date = timezone.now()\n comment.comment_text= comment_text\n comment.image_id = img_id\n comment.submitter_id = int(request.POST['uid'])\n comment.save()\n return rest.rest_success(request, img_id)","def on_comment(self, request, board_id):\n error = None\n if request.method == 'POST':\n creator = request.form['creator']\n comment = request.form['comment']\n if len(creator) > 30:\n error = 'creator name too long'\n elif len(comment) > 50:\n error = 'comment too long'\n else:\n self.insert_comment(request, board_id)\n return redirect('/board:' + board_id)\n return self.render_template('comment.html', error=error)","def post(self, request, pk):\n\n post = Blog.objects.get(pk=int(pk))\n user_id = self.request.session.get('USER_ID')\n\n try:\n user = User.objects.get(pk=user_id)\n except:\n pass\n body = self.request.POST.get('body')\n\n if user_id is None:\n messages.add_message(request, messages.ERROR, \"Please login to add comments.\")\n return HttpResponseRedirect(self)\n\n comments = Comment.objects.create(post=post, author=user, body=body)\n\n d = model_to_dict(post)\n messages.add_message(request, messages.SUCCESS, \"Comment added successfully.\")\n return self.render_to_response(d)","def newcomment(id):\n\n if g.is_logged == False:\n flash (\"You need to be logged in\")\n return redirect(url_for('show_place', id=id))\n\n if request.method == 'POST':\n rating = request.form['rating']\n\n if rating.isdigit() == False:\n flash (\"Rating must be between a number between 0 and 5 (inclusive)\")\n elif int(rating) < 0 or int(rating) > 5:\n flash (\"Rating must be between 0 and 5 (inclusive)\")\n else:\n db = get_db()\n db.execute('''insert into reviews (rating, title, message, user_id, place_id) values (?, ?, ?,?,?)''', [rating, request.form['title'], request.form['content'], g.user_id, id])\n db.commit()\n\n flash('Your comment was successfully added')\n return redirect(url_for('show_place', id=id))","def post_comment(id):\n \n form = CommentForm()\n title = 'post comment'\n post = Post.query.filter_by(id=id).first()\n\n if post is None:\n\n abort(404)\n\n if form.validate_on_submit():\n comment = form.comment.data\n new_comment = Comments(opinion = comment, user_id = current_user.id, posts_id = post.id)\n new_comment.save_comment()\n return redirect(url_for('main.view_post', id = post.id))\n\n return render_template('comments.html', form = form, title = title)","def createcomment(request, pk):\n issue = get_object_or_404(Issue, pk=pk)\n if request.method == \"POST\":\n form = CommentCreationForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.issue = issue\n comment.author = request.user\n comment.created_at = timezone.now()\n comment.save()\n return redirect('office:issue', pk=pk)\n else:\n form = CommentForm()\n return render(request, 'blog/add_comment_to_post.html', {'form': form})","def form_valid(self, form):\n post = self.get_object()\n #WAS: post.comment_add(form.cleaned_data['text'], self.request.user)\n post.add_comment(form.cleaned_data['text'], \n self.request.user,\n added_at=None, \n by_email=False\n )\n return views_support.response_success(self.request)","def post_comment(request, next=None, using=None):\n # Fill out some initial data fields from an authenticated user, if present\n data = request.POST.copy()\n if request.user.is_authenticated():\n if not data.get('name', ''):\n data[\"name\"] = request.user.get_full_name() or request.user.username\n if not data.get('email', ''):\n data[\"email\"] = request.user.email\n\n # Check to see if the POST data overrides the view's next argument.\n next = data.get(\"next\", next)\n\n # Look up the object we're trying to comment about\n ctype = data.get(\"content_type\")\n object_pk = data.get(\"object_pk\")\n model = models.get_model(*ctype.split(\".\", 1))\n target = model._default_manager.using(using).get(pk=object_pk)\n\n\n # Construct the comment form\n form = comments.get_form()(target, data=data)\n\n # Check security information\n if form.security_errors():\n return None\n # Create the comment\n comment = form.get_comment_object()\n comment.ip_address = request.META.get(\"REMOTE_ADDR\", None)\n if request.user.is_authenticated():\n comment.user = request.user\n\n # Signal that the comment is about to be saved\n responses = signals.comment_will_be_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n # Save the comment and signal that it was saved\n comment.save()\n message = get_object_or_404(Message, pk = object_pk)\n message.envoyer_commentaire_notification(comment.pk, request.user.username)\n \n signals.comment_was_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n comment_list = [comment]\n return render_to_response('comments/list.html', {'comment_list': comment_list},context_instance=RequestContext(request))","def comment_add(request,comment=None, error='', message=''):\n categories = Category.objects.all()\n error_fields=[]\n default_comment = Comment(date=datetime.date.today(), time=datetime.datetime.now().time, source='', detail='', category=Category.objects.filter(description='Events')[0], user_email='')\n\n try:\n added = bool(request.POST['add'])\n except:\n added = False\n try:\n action = request.POST['action']\n except:\n action = 'add'\n\n if added == True:\n try:\n new_date = parse(request.POST['date'], dayfirst=True)\n new_time = parse(request.POST['time'])\n except:\n error += ' Datetime invalid or not specified.'\n\n try:\n new_detail = request.POST['detail']\n if new_detail == '':\n error += ' Comment text is blank.'\n except:\n error += ' No comment text provided.'\n\n try:\n new_source = request.POST['source']\n if new_source == '':\n error += ' Source is blank.'\n except:\n error += ' No comment source provided.'\n\n try:\n new_category = Category.objects.filter(pk=int(request.POST['category_id']))[0] #The [0] is OK since the fact that category_id is a primary key ensures that the array has only length 1.\n except:\n error += ' Category invalid or nonexistent.'\n\n try:\n new_user_email = request.POST['user_email']\n if new_user_email == '':\n error += ' You haven\\'t provided your e-mail address.'\n except:\n error += ' No user e-mail address provided.'\n\n if error == '':\n try:\n new_comment = Comment(date=new_date, time=new_time, source=new_source, detail=new_detail, category=new_category, user_email=new_user_email)\n new_comment.full_clean()\n try:\n new_comment.save()\n message += 'Your comment was added to the database.'\n except:\n error += 'Failed to access the database.'\n except ValidationError as ve:\n for k in ve.message_dict.keys():\n error_fields.append(k)\n for m in ve.message_dict[k]:\n error += m + ' '\n default_comment = new_comment\n\n if action == 'saveandaddanother' or action == 'add' or error != '':\n return render_to_response('feedback/comment_add.html',\n {'categories': categories,\n 'error': error,\n 'error_fields': error_fields,\n 'message': message,\n 'added': added,\n 'comment': default_comment},\n context_instance=RequestContext(request))\n elif action == 'save':\n return index(request, error=error, message=message)\n else:\n error += 'Invalid submit action requested.'\n return render_to_response('feedback/comment_add.html',\n {'categories': categories,\n 'error': error,\n 'error_fields': error_fields,\n 'added': added,\n 'message': message,\n 'comment': default_comment},\n context_instance=RequestContext(request))","def add_comment_to_post(request, pk):\n post = get_object_or_404(Post, pk=pk)\n if request.method == 'POST':\n form = CommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.post = post\n comment.save()\n return redirect('post_detail', pk=post.pk)\n else:\n form = CommentForm()\n return render(request, 'blog/comment_form.html', {'form': form})","def community_post_create_view(request):\n task = \"Create New\"\n form = AddEditPostForm() # An unbound form\n\n if request.method == 'POST': # If the form has been submitted...\n form = AddEditPostForm(request.POST, request.FILES) # A form bound to the POST data\n if form.is_valid(): # All validation rules pass\n post = form.save(commit=False) # Create a new object from the form, but don't save it to the database\n post.author = request.user # Set the author to the current user\n post.save() # Save the object to the database\n slug_str = \"%s %s\" % (post.title, post.date_posted) # Create a slug from the title and date\n post.slug = slugify(slug_str) # Create the slug\n post.save() # Save the object to the database\n return redirect('community-home') # Redirect to the home page\n\n context = { # Pass the variables to the template\n 'task': task,\n 'form': form,\n }\n return render(request,\n 'pages/patient-community/community-create-update-post.html',\n context) # render the patient community create post page","def add_comment_view(request, e_pk):\n\n element = get_object_or_404(Element, pk=e_pk)\n group = element.tab.group\n\n if request.user not in group.users.all():\n return redirect(reverse('my_groups_view'))\n\n if request.method == 'POST':\n form = CreateCommentForm(request.POST)\n if form.is_valid():\n comment = Comment(\n text=form.cleaned_data['text'],\n creator=request.user,\n element=element,\n )\n comment.save()\n else:\n return HttpResponseBadRequest()\n\n return redirect(reverse('element_view', args=(e_pk,)))","def post(self):\n comment_id = self.request.get('comment_id')\n post_id = self.request.get('post_id')\n comment = Comment.get_by_id(int(comment_id), parent=comment_key())\n post = Post.get_by_id(int(post_id), parent=blog_key())\n if comment and self.user.key().id() == comment.user.key().id():\n comment.content = self.request.get('content')\n\n have_errors = False\n\n if not comment.content:\n error_content = \"Content is required\"\n have_errors = True\n\n if have_errors:\n self.render(\"edit_comment.html\",\n comment=comment,\n error_content=error_content,\n user=self.user)\n else:\n comment.put()\n time.sleep(0.1)\n\n self.redirect('/blog/%s' % str(post.key().id()))","def form_valid(self, form):\n action = self.get_object()\n #WAS: return action.comment_add(form.cleaned_data['text'], self.request.user)\n action.comment_add(form.cleaned_data['text'], self.request.user)\n return views_support.response_success(self.request)","def add_comment(request, listing_id):\n if request.method == \"POST\":\n try:\n listing = Listing.objects.get(pk=listing_id)\n except Listing.DoesNotExist:\n return render(request, \"auctions/errors.html\", {\"error_message\":\n \"something went wrong, the id url argument is not valid\"})\n\n CommentForm = modelform_factory(Comment, exclude=(\"commenter\",\"listing\"))\n # validate and save from the formdata to the database\n form = CommentForm(request.POST)\n try:\n comment = form.save(commit=False)\n comment.commenter = request.user\n comment.listing = listing\n comment.save()\n except:\n # if something went wrong with comment form \n return render(request, \"auctions/errors.html\", {\"error_message\":\n \"something went wrong with the submission of your comment, try again\"})\n\n return redirect(reverse(\"single_listing\", \n args=[listing.title]) +f\"?id={listing.id}\")","def post(self):\n modified_content = self.request.get('comment_edit')\n comment_id = self.request.get('comment_id')\n comment = Comments.get_by_id(int(comment_id))\n user = self.get_active_user()\n\n if user.key().id() == comment.submitter_id:\n comment.content = modified_content\n comment.put()\n self.redirect('/%s' % str(comment.post_id))\n else:\n self.error(403)","def post(self):\n post_id = int(self.request.get('post_id'))\n post = Posts.get_by_id(post_id)\n comment = self.request.get('comment')\n submitter_id = self.get_active_user().key().id()\n\n if submitter_id:\n comment = Comments(post_id=post_id, content=comment,\n submitter_id=submitter_id)\n comment.put()\n self.redirect('/%s' % str(post.key().id()))\n else:\n self.error(403)","def create_comment(request):\n\n # get data\n in_data = getRequestData(request)\n\n # get the Thread associated with the comments\n mythread = Thread.objects.get(id=in_data.get('mythreadid'))\n\n # save in database\n try:\n comment = Comment(pub_date = datetime.datetime.now(pytz.timezone('US/Eastern')), username = in_data.get('myusername'), text = in_data.get('mytext'), score = 0, thread = mythread )\n comment.save()\n except:\n return HttpResponseBadRequest('Error saving to database!')\n\n return JsonResponse(in_data)","def add_comment(request, entry_pk):\n\n blog = get_object_or_404(BlogEntry, pk=entry_pk)\n\n if not request.user.is_authenticated():\n raise PermissionDenied\n\n form = BlogCommentForm(creator=request.user, blog=blog, data=request.POST)\n\n if form.is_valid():\n form.save()\n return HttpResponseRedirect(blog.get_absolute_url())\n\n return single(request, entry_pk=entry_pk, comment_form=form)","def add_mvcomment(request, pk):\n\n # Getting the movie object hosting the comment\n movie = get_object_or_404(Movie, pk=pk)\n\n # if POST\n if request.method == \"POST\":\n form = MovieCommentForm(request.POST)\n\n # set the author and redirect if valid form\n if form.is_valid():\n comment = form.save(commit=False)\n comment.author = request.user\n comment.movie = movie\n comment.save()\n return redirect('../', pk=movie.pk)\n else:\n form = MovieCommentForm()\n\n # render the form through the template\n return render(request, {'form': form})","def new_from_post():\n # If you make a post request with a question_id we will assume you want a new question editor\n # we will prepopulate the question new page with data from that question (if it is a valid question id)\n question_id = request.form['question_id'] if request.form['question_id'] else ''\n\n return render_template('questionNew.html', question_id=question_id)","def create_comment(bid, pid):\n # pylint: disable=unused-argument\n form = CommentForm(request.form)\n if request.method == 'POST':\n if form.validate():\n DB.session.add(Comment(pid, current_user.uid, form.text.data))\n DB.session.commit()\n flash('Comment successfully created!')\n else:\n flash(constants.DEFAULT_SUBMISSION_ERR)\n return redirect(request.referrer)","def post(self):\n\n # 160 characters limit\n\n if len(client_data[\"content\"]) >= 200:\n self.write_json_with_status(400,{\n 'result' : 'fail',\n 'reason' : 'content too long'\n })\n\n client_data = self.data\n now = str(time.time())\n comment_id = md5(client_data['content']+now)\n\n new_comment = self.event_comment_table.put_item(data={\n 'CommentID' : comment_id,\n 'CreatorID' : creator_id,\n 'Content' : content,\n 'EventID' : event_id,\n 'Timestamp' : now\n })\n \n\n self.write_json({\n 'comment_id' : comment_id\n })","def questions_collection(request):\n if request.method == \"POST\":\n data = json.loads(request.body)\n task = Task.objects.get(id=data.get(\"taskId\", \"\"))\n commenter = User.objects.get(username=data.get(\"commenter\", \"\"))\n content = data.get(\"content\", \"\")\n\n question = Question(\n task=task,\n commenter=commenter,\n content=content\n )\n question.save()\n return JsonResponse({\"message\": \"Question created successfully\"}, status=201)","def postVisitView(request, pk, post_id):\n post = Blogger.objects.get(id=pk).post_set.get(id=post_id)\n comments = post.comment_set.all().order_by(\"-date_created\")\n\n data = {\n \"user\": request.user,\n \"post\": post,\n }\n\n form = CommentForm(initial=data)\n\n if request.method == \"POST\":\n form = CommentForm(request.POST, initial=data)\n if form.is_valid():\n form.save()\n return redirect(f\"/blogger/{pk}/post/{post_id}\")\n\n context = {\n \"post\": post,\n \"comments\": comments,\n \"form\": form,\n }\n return render(request, \"blog/post_visit.html\", context)","def post(self):\n post_id = self.request.get('post_id')\n post = Post.get_by_id(int(post_id), parent=blog_key())\n content = self.request.get('comment')\n\n if content:\n comment = Comment(parent=comment_key(),\n content=content,\n user=self.user,\n post=post)\n comment.put()\n\n time.sleep(0.1)\n self.redirect('/blog/%s' % str(post.key().id()))","def post_comment_ajax(request, using=None):\n if not request.is_ajax():\n return HttpResponseBadRequest(\"Expecting Ajax call\")\n\n data = request.POST.copy()\n if request.user.is_authenticated():\n if not data.get('name', ''):\n data[\"name\"] = request.user.get_full_name() or request.user.get_username()\n if not data.get('email', ''):\n data[\"email\"] = request.user.email\n\n # Look up the object we're trying to comment about\n ctype = data.get(\"content_type\")\n object_pk = data.get(\"object_pk\")\n if ctype is None or object_pk is None:\n return CommentPostBadRequest(\"Missing content_type or object_pk field.\")\n try:\n model = apps.get_model(*ctype.split(\".\", 1))\n target = model._default_manager.using(using).get(pk=object_pk)\n except TypeError:\n return CommentPostBadRequest(\n \"Invalid content_type value: %r\" % escape(ctype))\n except AttributeError:\n return CommentPostBadRequest(\n \"The given content-type %r does not resolve to a valid model.\" % escape(ctype))\n except ObjectDoesNotExist:\n return CommentPostBadRequest(\n \"No object matching content-type %r and object PK %r exists.\" % (\n escape(ctype), escape(object_pk)))\n except (ValueError, ValidationError) as e:\n return CommentPostBadRequest(\n \"Attempting go get content-type %r and object PK %r exists raised %s\" % (\n escape(ctype), escape(object_pk), e.__class__.__name__))\n\n # Do we want to preview the comment?\n preview = \"preview\" in data\n\n # Construct the comment form\n form = django_comments.get_form()(target, data=data)\n\n # Check security information\n if form.security_errors():\n return CommentPostBadRequest(\n \"The comment form failed security verification: %s\" % escape(str(form.security_errors())))\n\n # If there are errors or if we requested a preview show the comment\n if preview:\n comment = form.get_comment_object() if not form.errors else None\n if comment is not None and request.user.is_authenticated():\n comment.user = request.user\n return _ajax_result(request, form, \"preview\", comment, object_id=object_pk)\n if form.errors:\n return _ajax_result(request, form, \"post\", object_id=object_pk)\n\n # Otherwise create the comment\n comment = form.get_comment_object()\n comment.ip_address = get_trusted_ip(request)\n if request.user.is_authenticated():\n comment.user = request.user\n\n # Signal that the comment is about to be saved\n responses = signals.comment_will_be_posted.send(\n sender=comment.__class__,\n comment=comment,\n request=request\n )\n\n for (receiver, response) in responses:\n if response is False:\n return CommentPostBadRequest(\n \"comment_will_be_posted receiver %r killed the comment\" % receiver.__name__)\n\n # Save the comment and signal that it was saved\n comment.save()\n signals.comment_was_posted.send(\n sender=comment.__class__,\n comment=comment,\n request=request\n )\n\n return _ajax_result(request, form, \"post\", comment, object_id=object_pk)","def _post(self, data):\n new_comment_id = DB_COMMENT_TABLE.insert(data)\n return new_comment_id","def add_new_comment(request):\n token = request.data.get('token')\n text = request.data.get('text', '')\n post_id = request.data.get('post_id', '')\n permission = request.data.get('permission')\n\n if Token.objects.filter(key=token).exists():\n if len(text) < 10:\n return Response({\"error\": 24})\n if len(text) > 1000:\n return Response({\"error\": 25})\n\n if type(post_id) is int:\n if Post.objects.filter(pk=post_id).exists():\n token = get_object_or_404(Token, key=token)\n post = get_object_or_404(Post, pk=post_id)\n comment = Comment.objects.create(post=post,\n author_id=token.user_id,\n text=text,\n permission=permission)\n serializer = PostSerializer(post, context={'user_id': token.user_id})\n UserFeed.objects.create(user=post.author,\n action_user=token.user,\n post_comment=comment,\n action=\"PostComment\")\n\n printable = set(string.printable)\n msg = filter(lambda x: x in printable, comment.text) \n message = \"{} commented: {}\".format(token.user.username, msg)\n\n custom = {\n \"post_id\": post.id,\n \"avatar\": UserProfile.objects.get(user=token.user).avatar.url\n }\n\n if post.author != token.user:\n user_notification = UserNotification.objects.get(user=post.author)\n send_notification(custom, message, user_notification)\n\n # check @ for users \n for item in text.split(' '):\n if item and item[0] == '@':\n username = item[1:].lower()\n user = User.objects.filter(username__iexact=username).first()\n if not user or user == token.user:\n continue\n UserFeed.objects.create(user=user,\n action_user=token.user,\n post_comment=comment,\n action=\"PostCommentComment\")\n msg = filter(lambda x: x in printable, comment.text) \n message = \"{} commented: {}\".format(token.user.username, msg)\n user_notification = UserNotification.objects.get(user=user)\n send_notification(custom, message, user_notification)\n\n return Response({\"success\": 26,\n \"post\": serializer.data})\n else:\n return Response({\"error\": 27})\n else:\n return Response({\"error\": 17})","def add_comment(request, pk, pk2):\n template_var = base_template_vals(request)\n p = request.POST\n \n if p.has_key(\"content\") and p[\"content\"]:\n if request.user.is_authenticated():\n comment = Comment(event=Event.objects.get(id=pk))\n comment.user = UserProfile.objects.get(django_user=request.user)\n comment.content = p[\"content\"]\n comment.save()\n\n # Sys notification\n from_user = UserProfile.objects.get(django_user=pk2) # Who's event that is commented on\n to_user = Event.objects.get(id=pk).author\n event_id = pk\n sys_notification(to_user, \"add_comment\", from_user, event_id)\n return single(request, pk)","def post(self, post_id):\n comment_content = self.request.get(\"comment_content\")\n Post.add_comment(int(post_id), int(\n self.user.get_id()), comment_content)\n self.redirect(\"/blog/\" + post_id + \"/comments\")","def process_comment(request, comment, post):\n\n if request.user.is_authenticated:\n # We already set auth user's name and email in the form's inital vals.\n comment.author = request.user\n\n # Is this a threaded comment?\n if request.POST.get(\"parent_id\"):\n comment.parent = Comment.objects.get(id=request.POST.get(\"parent_id\"))\n\n # If commenter is logged in, override name and email with stored values from User object\n if request.user.is_authenticated:\n comment.name = request.user.get_full_name()\n comment.email = request.user.email\n\n # Set required relationship to Post object\n comment.post = post\n\n # Get commenter's IP and User-Agent string\n # ip = get_ip(request)\n # if ip is not None:\n # comment.ip_address = ip\n comment.user_agent = request.META.get(\"HTTP_USER_AGENT\", \"\")\n\n # Run spam check\n comment.spam = spam_check(comment)\n\n # Strip disallowed HTML tags. See tangerine docs to customize.\n comment.body = sanitize_comment(comment.body)\n\n # Call comment approval workflow\n comment.approved = get_comment_approval(comment.email, request.user.is_authenticated)\n if comment.approved:\n messages.add_message(request, messages.SUCCESS, \"Your comment has been posted.\")\n else:\n messages.add_message(request, messages.INFO, \"Your comment has been held for moderation.\")\n\n comment.save()\n\n # Alert post author that comment needs moderation, or that it's been auto-published:\n send_comment_moderation_email(comment)","def post(self, request, *args, **kwargs):\n serializer = CommentSerializer(data=request.data)\n post_pk = self.kwargs['post_pk']\n post = Post.objects.get(pk=post_pk)\n if serializer.is_valid():\n serializer.save(author=request.user, post=post)\n return Response(serializer.data, status=status.HTTP_201_CREATED)\n return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)","def create_post():\r\n\r\n # Check for and reject empty username or whinge\r\n if not request.values.get(\"username\") or not request.values.get(\"whinge\"):\r\n print(\"Ignoring request to with empty username or whinge\")\r\n else:\r\n # Form data ok; add to DB\r\n con = get_db()\r\n con.execute(\"INSERT INTO posts (submitter,content,ts) VALUES (?,?,?);\",\r\n (\r\n request.values.get(\"username\"), # form field username -> DB column submitter\r\n request.values.get(\"whinge\"), # form field whinge -> DB column content\r\n time.time()\r\n )\r\n )\r\n con.commit()\r\n con.close()\r\n \r\n # TODO: Handle possibility of failed INSERT\r\n\r\n # Send them back to the main page\r\n return redirect(url_for(\"display_top\"))","def post_detail(request, pk):\n post = get_object_or_404(Post, pk=pk)\n comments = post.comments.all\n post.views += 1\n post.save()\n \n if request.method == \"POST\":\n comment_form = CommentForm(request.POST)\n if comment_form.is_valid() and request.user:\n new_comment = comment_form.save(commit=False)\n new_comment.post = post\n new_comment.author = request.user\n new_comment.save()\n elif request.user:\n comment_form = CommentForm()\n \n return render(request, \"details.html\", {\"post\": post, \"comments\": comments, \"comment_form\": comment_form})","def post(self):\n\n subject = self.request.get('subject')\n content = self.request.get('content')\n\n have_errors = False\n\n if not subject:\n error_subject = \"Please write down the subject\"\n have_errors = True\n if not content:\n error_content = \"Content is required\"\n have_errors = True\n\n if have_errors:\n self.render(\"newpost.html\",\n subject=subject,\n content=content,\n error_subject=error_subject,\n error_content=error_content,\n user=self.user)\n else:\n post = Post(parent=blog_key(),\n subject=subject,\n content=content,\n user=self.user)\n post.put()\n self.redirect('/blog/%s' % str(post.key().id()))","def post(self, request, *args, **kwargs):\n del request, args, kwargs # unused\n self.enforce_xsrf(self.ACTION_ID)\n\n notes = []\n for param_key, value in self.request.POST.items():\n if param_key.startswith('note.'):\n note = model.Note.get(self.env.repo, param_key[5:])\n if note:\n if value in ['accept', 'flag']:\n note.reviewed = True\n if value == 'flag':\n note.hidden = True\n notes.append(note)\n db.put(notes)\n\n return django.shortcuts.redirect(self.build_absolute_path())","def add_accomment(request, pk):\n\n actor = get_object_or_404(Actor, pk=pk)\n if request.method == \"POST\":\n form = ActorCommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.author = request.user\n comment.actor = actor\n comment.save()\n return redirect('../', pk=actor.pk)\n else:\n form = ActorCommentForm()\n return render(request, {'form': form})","def post():\n\n form = forms.PostForm()\n if form.validate_on_submit():\n models.Post.create(title=form.title.data,\n date=form.date.data,\n time_spent=form.time_spent.data,\n details=form.details.data,\n remember=form.remember.data)\n return redirect(url_for('index'))\n return render_template('new.html', form=form)","def add_component_comment(request):\n try:\n person = get_person(request)\n\n print(\"Add components comment. Start.\")\n print(\"Add components comment. Request: \" + str(request))\n\n if request.method == \"POST\":\n # get values from form\n assessment_id = request.POST['assessment_id']\n element_id = None\n try:\n component_id = request.POST['component_id']\n except:\n component_id = None\n try:\n subcomponent_id = request.POST['subcomponent_id']\n except:\n subcomponent_id = None\n try:\n third_component_id = request.POST['third_component_id']\n except:\n third_component_id = None\n try:\n fourth_component_id = request.POST['fourth_component_id']\n except:\n fourth_component_id = None\n try:\n fifth_component_id = request.POST['fifth_component_id']\n except:\n fifth_component_id = None\n comment = request.POST['textComments']\n\n if fifth_component_id:\n element_id = fifth_component_id\n else:\n if fourth_component_id:\n element_id = fourth_component_id\n else:\n if fifth_component_id:\n element_id = fifth_component_id\n else:\n if third_component_id:\n element_id = third_component_id\n else:\n if subcomponent_id:\n element_id = subcomponent_id\n else:\n if component_id:\n element_id = component_id\n\n # get section and assessment\n component = Component.objects.get(id=element_id)\n\n print(\"Add components comment. Component: \" + component.name)\n print(\"Add components comment. comment: \" + comment)\n\n # create comment\n my_comment = AssessmentComponentComment()\n my_comment.assessment = Assessment.objects.get(id=assessment_id)\n my_comment.element = component\n my_comment.comment = comment\n my_comment.person = person\n my_comment.save()\n\n # trace action\n trace_action(TRACE_COMMENT, person, \"User added comment in component: \" + component.name)\n\n # send mail\n try:\n send_mail = request.POST['send_mail']\n t = Thread(target=send_comments_email, args=(my_comment.comment, \"Element: \" + component.name, person))\n t.start()\n # send_comments_email(my_comment.comment, section, person)\n except:\n # checkbox not set\n pass\n\n # redirect to section page\n url_to_redirect = \"/component_2/\" + assessment_id + SLASH\n\n if component_id:\n url_to_redirect += component_id + SLASH\n if subcomponent_id:\n url_to_redirect += subcomponent_id + SLASH\n if third_component_id:\n url_to_redirect += third_component_id + SLASH\n if fourth_component_id:\n url_to_redirect += fourth_component_id + SLASH\n if fifth_component_id:\n url_to_redirect += fifth_component_id + SLASH\n\n return redirect(url_to_redirect, context_instance=RequestContext(request))\n else:\n raise Exception(\"GET call to add new section comment\")\n except:\n if debug_is_on():\n raise\n else:\n return render_to_response(TEMPLATE_ERROR, {\"error_description\": sys.exc_info(), \"crpt_url\": CRPT_URL},\n context_instance=RequestContext(request))","def post_comment(self):\n self.post_question()\n return self.client.post(\"api/v2/1/comments\", headers={\"Authorization\": \"{}\".format(self.token())}, data=json.dumps(self.comment), content_type='application/json')","def add():\n if request.method == \"POST\":\n result = add_post(\n request.form[\"title\"],\n request.form[\"body\"]\n )\n flash(result)\n return redirect(url_for(\"show\"))\n else:\n return render_template(\"add.html\")","def write_review(request):\n form = ReviewForm\n\n if request.method == 'POST':\n form_data = {\n 'title': request.POST['title'],\n 'description': request.POST['description'],\n 'author': request.POST['author'],\n }\n\n form = ReviewForm(form_data)\n\n if form.is_valid:\n form.save()\n messages.success(\n request, f'Review added successfully! Thanks!')\n else:\n messages.error(\n request, f'Upps something went wrong, please try again')\n\n context = {\n 'form': form\n }\n return render(request, 'reviews/write_review.html', context)","def submit_textarea():\n print(\"--- submit ---\")\n post_content = request.form[\"content\"]\n author = request.form[\"author\"]\n\n post_object = {\n 'author': author,\n 'content': post_content,\n }\n\n # Submit a transaction\n new_tx_address = \"{}/new_transaction\".format(BASE_URL)\n\n requests.post(new_tx_address,\n json=post_object,\n headers={'Content-type': 'application/json'})\n\n return redirect('/')","def add_comment(request, model, object_id):\n obj = get_object_or_404(model, id=object_id)\n if request.method == \"POST\":\n form = CommentForm(request.POST)\n if form.is_valid():\n Comment.objects.create(\n content_type = ContentType.objects.get_for_model(model),\n object_id = object_id,\n author = request.user,\n added_at = datetime.datetime.now(),\n comment = form.cleaned_data['comment']\n )\n if request.is_ajax():\n return JsonResponse({'success': True})\n else:\n return HttpResponseRedirect(obj.get_absolute_url())\n elif request.is_ajax():\n return JsonResponse({'success': False, 'errors': form.errors})\n else:\n form = CommentForm()\n\n # Let the appropriate fallback view take care of display/redisplay\n if model is Question:\n return question_comments(request, obj, form=form)\n elif model is Answer:\n return answer_comments(request, object_id, answer=obj, form=form)","def new_post(request):\n if request.method != 'POST':\n # No data submitted; create a blank form.\n form = PostForm()\n else:\n # POST data submitted; process data.\n form = PostForm(data=request.POST)\n if form.is_valid():\n new_post = form.save(commit=False)\n new_post.owner = request.user\n new_post.save()\n return redirect('blogs:posts')\n\n # Display a blank or invalid form.\n context = {'form': form}\n return render(request, 'blogs/new_post.html', context)","def signup(request, entry_id):\n harvest = get_object_or_404(Harvest, pk=entry_id)\n if request.method == 'POST':\n form = HarvestSignupForm(request.POST)\n if form.is_valid():\n username = form.cleaned_data['username']\n password = form.cleaned_data['password']\n user = authenticate(username=username, password=password)\n login(request, user)\n harvest = get_object_or_404(Harvest, pk=entry_id)\n volunteer = Volunteer.objects.get(user=user)\n harvest.volunteers.add(volunteer)\n print form.cleaned_data['comments']\n new_comment = Comment(volunteer=volunteer, comment=form.cleaned_data['comments'])\n new_comment.save()\n harvest.comment.add(new_comment)\n return HttpResponse(\"Thanks! You're signed up.\")\n else:\n form = HarvestSignupForm()\n return render_to_response(\"signup.html\", {'form':form, 'harvest':harvest}, context_instance=RequestContext(request))","def post(self):\n subject = self.request.get('subject')\n post_content = self.request.get('post_content')\n submit = self.request.get('submit')\n cancel = self.request.get('cancel')\n user = self.get_active_user()\n created_by = int(user.key().id())\n post_id = self.request.get('post_id')\n\n if not user:\n self.redirect('/login')\n if post_id:\n post = Posts.get_by_id(int(post_id))\n else:\n post = None\n\n if cancel == \"cancel\":\n self.redirect('/%s' % str(post.key().id()))\n return\n if (post and post.submitter_id == user.key().id()) or not post:\n if submit == \"submit\" and subject and post_content:\n if post:\n post.subject = subject\n post.content = post_content\n post.put()\n else:\n post = Posts(subject=subject,\n content=post_content,\n submitter_id=created_by)\n post.put()\n self.redirect('/%s' % str(post.key().id()))\n else:\n self.render_newpage(user=user,\n subject=subject,\n post_content=post_content,\n error=\"\"\"Please provide both a subject and a\n post!\"\"\")\n else:\n self.redirect('/login')","def comment(request, object_id):\n send_charob = request.user.char_ob\n rec_charob = get_character_from_ob(object_id)\n comment_txt = request.POST[\"comment\"]\n roster.create_comment(send_charob, rec_charob, comment_txt)\n return HttpResponseRedirect(reverse(\"character:sheet\", args=(object_id,)))","def admincreate(object):\n if request.method == \"POST\":\n\n db = get_db()\n execute_string = 'INSERT INTO ' + object.title()\n\n if object == 'post':\n execute_string += '(title, content, authorId, categoryId) VALUES (\"' + request.form['title'] + '\", \"' + request.form[\"content\"] + '\", \"' + request.form[\"authorid\"] + '\", \"' + request.form[\"categoryid\"] + '\")'\n elif object == 'author':\n execute_string += '(name) VALUES (\"' + request.form['name'] + '\")'\n elif object == 'category':\n execute_string += '(name, description) VALUES (\"' + request.form['name'] + '\", \"' + request.form[\"description\"] + '\")'\n\n db.execute(execute_string)\n db.commit()\n return redirect(url_for(\"adminview\", object=object))\n\n return render_template(\"new.html\", object=object, item={})","def new_post():\n form = PostForm()\n if form.validate_on_submit():\n post = Post(pub_date=datetime.date.today())\n post.title = form.title.data\n post.content = form.content.data\n post.slug = slugify(post.title)\n db.session.add(post)\n db.session.commit()\n return flask.redirect(flask.url_for(\n 'view_post',\n year=post.pub_date.year,\n month=post.pub_date.month,\n day=post.pub_date.day,\n slug=post.slug\n ))\n return flask.render_template('new.html', form=form)","def add_comment() -> str:\n if \"markdown\" in request.form:\n if \"file\" in request.form:\n comment = Comment(\n markdown=request.form[\"markdown\"],\n submission_id=Submission.query.filter(\n Submission.filepath.contains(request.form[\"file\"])\n )\n .first()\n .id,\n cell_id=request.form[\"cell_id\"] if \"cell_id\" in request.form else None,\n user=UserModel.get_by_token(session[\"token\"]),\n )\n # If not cell_id this is a general comment\n comment.save()\n else:\n return \"Missing file or cell_id\", 400\n else:\n return \"Missing markdown\", 400\n\n comment_maker = get_template_attribute(\"_macros.html\", \"comment_block\")\n return comment_maker(comment)","def comment(postid):\n context = {}\n if \"username\" not in flask.session:\n raise InvalidUsage('Forbidden', status_code=403)\n\n connection = insta485.model.get_db()\n cursor = connection.execute(\n \"SELECT * FROM comments WHERE postid=:id\", {'id': postid})\n comments = cursor.fetchall()\n ''' \n if bool(comments) is False:\n raise InvalidUsage('Not Found', status_code=404)\n '''\n # User\n logname = flask.session[\"username\"]\n\n if flask.request.method == 'POST':\n data = flask.request.get_json(force=True)\n context['text'] = data['text']\n context['owner'] = logname\n context['owner_show_url'] = '/u/' + logname + '/'\n connection.execute('INSERT INTO comments (owner, postid, text) \\\n VALUES (?,?,?)', (logname, postid, data['text']))\n cursor = connection.execute('SELECT last_insert_rowid() AS id')\n commentid_dic = cursor.fetchone()\n context['commentid'] = commentid_dic['id']\n context['postid'] = postid\n return flask.jsonify(**context), 201\n\n # url\n context[\"url\"] = flask.request.path\n context['comments'] = []\n\n for i in comments:\n one_comment = {}\n one_comment['commentid'] = i['commentid']\n one_comment['owner'] = i['owner']\n one_comment['owner_show_url'] = '/u/' + i['owner'] + '/'\n one_comment['postid'] = postid\n one_comment['text'] = i['text']\n context['comments'].append(one_comment)\n\n return flask.jsonify(**context)","def post(self, request):\n\n # crear el formulario con los datos del post\n form = PostForm(request.POST)\n\n if form.is_valid():\n #crea el post\n post = form.save()\n\n #generar mensaje de exito\n msg = \"Post creado con éxito\"\n form = PostForm()\n else:\n msg = \"Ha ocurrido un error al guardar el post\" \\\n\n\n # renderiza la plantilla con el formulario\n context = {\n \"form\": form,\n \"msg\": msg\n }\n\n # renderiza y devuelve la plantilla\n return render(request, 'blogs/new-post.html', context)","def post(self):\n teacher = self.request.get(\"teacher\")\n student = self.request.get(\"student\")\n lessondate = self.request.get(\"lessondate\")\n reason = self.request.get(\"reason\")\n comment = self.request.get(\"comment\")\n\n if teacher and student and lessondate and reason:\n\n # create a new Post object and store it in the database !!!!!!!!!!!!!!!\n loglesson = Teacher(\n teacher=teacher,\n student=student,\n lessondate=lessondate,\n reason = reason,\n comment = comment)\n loglesson.put()\n\n # get the id of the new post, so we can render the post's page (via the permalink)\n id = loglesson.key().id()\n self.redirect(\"/loglesson/%s\" % id)\n else:\n error = \"Please include a teacher, student, lesson date, reason and comment!\"\n self.render_form(teacher, student, lessondate,reason, comment, error)","def add_awcomment(request, pk):\n\n award = get_object_or_404(Award, pk=pk)\n if request.method == \"POST\":\n form = AwardCommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.author = request.user\n comment.award = award\n comment.save()\n return redirect('../', pk=award.pk)\n else:\n form = AwardCommentForm()\n return render(request, {'form': form})","def post(self):\n\n title = self.request.get(\"title\")\n blogPost = self.request.get(\"blogPost\")\n author = self.request.cookies.get('name')\n\n if title and blogPost:\n\n bp = Blogposts(parent=blog_key(), title=title,\n blogPost=blogPost, author=check_secure_val(author))\n\n bp.put()\n\n self.redirect('/%s' % str(bp.key.integer_id()))\n else:\n error = \"Please submit both a title and a blogpost!\"\n self.render(\"newpost.html\", title=title,\n blogPost=blogPost, error=error)","def add_post():\n\tt_id = db.survey.insert(\n\t\tquestion = request.vars.question,\n\t\tuser_email = request.vars.email,\n\t\tuser_name = get_user_name_from_email(request.vars.email),\n\t\topt1 = request.vars.opt1,\n\t\topt2 = request.vars.opt2,\n\t\topt3 = request.vars.opt3,\n\t\topt4 = request.vars.opt4,\n\t\t#created_on_human = humanize.naturaltime(datetime.datetime.utcnow()),\n\n\t)\n\tt = db.survey(t_id)\n\treturn response.json(dict(post=t))","def submit_textarea():\n\n post_content = request.form[\"content\"]\n author = request.form[\"author\"]\n\n post_object = {\n 'author': author,\n 'content': post_content\n }\n\n # Submit a tx\n new_tx_address = f\"{CONNECTED_NODE_ADDRESS}/new_transaction\"\n\n request.post(new_tx_address,\n json=post_object, \n headers={'Content-type': 'application/json'})\n # return to homepage\n return redirect('/')","def _preview(request, context_processors, extra_context, form_class=ThreadedCommentForm):\r\n _adjust_max_comment_length(form_class)\r\n form = form_class(request.POST or None)\r\n context = {\r\n 'next' : _get_next(request),\r\n 'form' : form,\r\n }\r\n if form.is_valid():\r\n new_comment = form.save(commit=False)\r\n context['comment'] = new_comment\r\n else:\r\n context['comment'] = None\r\n return render_to_response(\r\n 'threadedcomments/preview_comment.html',\r\n extra_context, \r\n context_instance = RequestContext(request, context, context_processors)\r\n )","def test_add_new_comment(self):\n\n result = self.client.post(\"/add_new_comment/2\",\n data={\"user_id\": 25, \"park_id\": \"2\", \"content\": \"My dog loves this park!\"},\n follow_redirects=True)\n self.assertIn(\"<h1 class=\\\"title\\\">Bark Park!</h1>\", result.data)","def new_answer(request):\n if request.method == \"POST\":\n author = request.POST.get(\"author\")\n content = request.POST.get(\"content\")\n date = datetime.datetime.now()\n answer_tuple = {\n \"author\": author,\n \"content\": content,\n \"votes\": 0,\n \"topic_index\": request.matchdict[\"url\"],\n \"answer_date\": date.strftime(\"%d/%m/%Y\"),\n }\n request.db[\"answer\"].insert(answer_tuple)\n return HTTPFound(location=\"/topic/\" + request.matchdict[\"url\"])\n return HTTPFound(location=\"/\")","def post_comment(request, send_signal=True):\n # Based on variables passed in we get the comment the user is attempting to create/edit\n try:\n comment, previous_version = get_comment(request)\n except InvalidCommentException as e:\n transaction.rollback()\n return JsonResponse({\n 'ok': False,\n 'error_message': str(e),\n })\n\n # Check if the user doesn't pass the appropriate permission check (on the parent_object)...\n # We call this on the parent comment because the comment itself may not have been saved yet (can't call .get_root on it)\n # TODO: Fix this for root comment? (no parent)\n parent_comment = comment.parent\n tree_root = parent_comment.get_root()\n parent_object = tree_root.content_object\n if not user_can_post_comment(request, comment):\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You do not have permission to post this comment.\",\n })\n\n # Check to make sure we are not trying to save a comment \"deeper\" than we are allowed...\n if is_past_max_depth(comment):\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You cannot respond to this comment.\",\n })\n\n # If the comment object (NOT the message) hasn't been saved yet...\n if comment._state.adding == True:\n comment = add_comment(comment)\n\n # Now that we have a comment object, we get a 'lock' on it to prevent a race condition\n try:\n lock_comment(comment)\n except DatabaseError:\n transaction.set_rollback(True)\n # Someone is already trying to update this comment, so we need to return an appropriate error\n return JsonResponse({\n 'ok': False,\n 'error_message': \"Someone else is currently editing this comment. Please refresh your page and try again.\",\n })\n\n # Now we know we have sole access to the comment object at the moment so we need to check if we are editing the most recent version\n if not_most_recent_version(comment, previous_version):\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You are not editing the most recent version of this comment. Please refresh your page and try again.\",\n })\n\n # Everything has checked out, so we save the new version and return the appropriate response\n version_form, new_version = create_new_version(request, comment)\n if version_form.is_valid():\n comment_template, kwargs = get_template(request, comment, parent_object, tree_root, new_version, previous_version, send_signal=send_signal)\n\n return JsonResponse({\n 'ok': True,\n 'html_content': loader.render_to_string(comment_template, context=kwargs)\n })\n else:\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"There were errors in your submission. Please correct them and resubmit.\",\n })","def post(self):\n subject = self.request.get('subject')\n content = self.request.get('content')\n\n # if user enter good subject and content, redirect them to new post page\n if subject and content:\n p = Post(parent = blog_key(), subject = subject, content = content)\n p.put() # store the post element into database\n self.redirect('/blog/%s' % str(p.key().id()))\n # otherwise, render an error page \n else:\n error = \"subject and content, please!\"\n self.render(\"newpost.html\", subject=subject, content=content, error=error)","def _create_comment(request, course_key, thread_id=None, parent_id=None):\r\n assert isinstance(course_key, CourseKey)\r\n post = request.POST\r\n\r\n if 'body' not in post or not post['body'].strip():\r\n return JsonError(_(\"Body can't be empty\"))\r\n\r\n course = get_course_with_access(request.user, 'load', course_key)\r\n if course.allow_anonymous:\r\n anonymous = post.get('anonymous', 'false').lower() == 'true'\r\n else:\r\n anonymous = False\r\n\r\n if course.allow_anonymous_to_peers:\r\n anonymous_to_peers = post.get('anonymous_to_peers', 'false').lower() == 'true'\r\n else:\r\n anonymous_to_peers = False\r\n\r\n comment = cc.Comment(\r\n anonymous=anonymous,\r\n anonymous_to_peers=anonymous_to_peers,\r\n user_id=request.user.id,\r\n course_id=course_key.to_deprecated_string(),\r\n thread_id=thread_id,\r\n parent_id=parent_id,\r\n body=post[\"body\"]\r\n )\r\n comment.save()\r\n if post.get('auto_subscribe', 'false').lower() == 'true':\r\n user = cc.User.from_django_user(request.user)\r\n user.follow(comment.thread)\r\n if request.is_ajax():\r\n return ajax_content_response(request, course_key, comment.to_dict())\r\n else:\r\n return JsonResponse(utils.safe_content(comment.to_dict()))","def post(self, req):\n error_messages = []\n success_message = ''\n\n # Creamos owner y se lo pasamos al form con un objeto pre-establecido\n post_with_owner = Post()\n post_with_owner.owner = req.user\n post_with_owner.blog = Blog.objects.filter(owner=req.user)[0]\n\n form = PostCreateForm(req.POST, instance=post_with_owner)\n if form.is_valid():\n\n new_post = form.save()\n form = PostCreateForm()\n success_message = u'Post guardado con éxito! '\n success_message += u'<a href=\"{0}\">'.format(reverse('post_detail', args=[req.user.username, new_post.pk]))\n success_message += u'(ver post)</a>'\n else:\n error_messages.append(u'Formulario incompleto.')\n\n context = {\n 'form': form,\n 'success_message': success_message\n }\n return render(req, 'posts/new_post.html', context)","def post(request):\n if request.method == \"POST\":\n post = Post()\n post.content = request.POST['content']\n post.author = request.user\n post.save()\n return HttpResponseRedirect(reverse(\"index\"))","def add_comment(request, pk, redirect_user):\n\n if request.is_ajax():\n create_comment_and_status_notification(request, pk)\n if redirect_user == 'profile':\n return redirect('profile')\n if redirect_user == 'news_feed':\n return redirect('news_feed')","def post(self):\n title = self.request.get(\"title\")\n body = self.request.get(\"body\")\n\n if title and body:\n\n # create a new Post object and store it in the database\n post = Post(\n title=title,\n body=body\n )\n post.put()\n\n # get the id of the new post, so we can render the post's page (via the permalink)\n id = post.key().id()\n self.redirect(\"/blog/%s\" % id)\n else:\n error = \"we need both a title and a body!\"\n #self.render_form(title, body, error)\n self.render(\"newpost.html\", title, body, error)","def post(self, request):\n\n # crear el formulario con los datos del POST\n blog_with_user = Blog(owner=request.user)\n form = BlogForm(request.POST, instance=blog_with_user)\n\n if form.is_valid():\n #crea el post\n blog = form.save()\n\n #generar mensaje de exito\n msg = \"Blog creado con éxito\"\n\n # limpiamos el formulario creando uno vacío para pasar a la plantilla\n form = BlogForm()\n else:\n msg = \"Ha ocurrido un error al guardar el blog\" \\\n\n\n # renderiza la plantilla con el formulario\n context = {\n \"form\": form,\n \"msg\": msg\n }\n\n # renderiza y devuelve la plantilla\n return render(request, 'blogs/new-blog.html', context)","def post(self, request, slug):\n article = ArticleInst.fetch(slug)\n comment = request.data.get('comment', {})\n\n serializer = self.serializer_class(data=comment)\n serializer.is_valid(raise_exception=True)\n status_ = status.HTTP_201_CREATED\n\n try:\n Comment.objects.get(\n article=article,\n body=comment.get('body')\n )\n except Comment.DoesNotExist:\n serializer.save(author=request.user, article=article)\n resp = {'message': 'Comment created'}\n resp['data'] = serializer.data\n\n else:\n resp = {'message': \"Seems you've posted an exact comment before\"}\n status_ = status.HTTP_409_CONFLICT\n return Response(data=resp,\n status=status_\n )","def about(request):\n data = {}\n if request.method == \"POST\":\n about = AboutForm(request.POST)\n if about.is_valid():\n about.save()\n data['success']=1\n data['message']='Comment successfully added'\n return JsonResponse(data)\n else:\n data['success']=0\n data['message']='Error while adding comment'\n return JsonResponse(data)\n \n else:\n about = AboutForm()\n return render(request, 'login/addcomment.html',\n {'form':about})","def create():\n if request.method == 'POST':\n title = request.form['title']\n body = request.form['body']\n error = None\n\n if not title:\n error = 'Title is required.'\n\n if error is not None:\n flash(error)\n else:\n db = get_db()\n db.execute(\n 'INSERT INTO post (title, body, author_id)'\n ' VALUES (?, ?, ?)',\n (title, body, g.user['id'])\n )\n db.commit()\n return redirect(url_for('blog.index'))\n\n return render_template('blog/create.html')","def save_comment(self):\n self.save()","def annonceDetailView(request, pk):\n details = Annonce.objects.get(pk=pk)\n details.view_annonce += 1\n details.save()\n\n # comment = Comment.objects.filter(\n # for_post=details,\n # reply=None).order_by('-create_content')\n # is_favorite = False\n # if details.favorite.filter(id=request.user.id).exists():\n # is_favorite = True\n # else:\n # print('favorite is now False')\n # if request.method == \"POST\":\n # print(request.POST)\n # c_form = commentForm(request.POST or None)\n # if c_form.is_valid():\n # content = request.POST.get('content')\n # reply_id = request.POST.get('comment-id')\n # comment_qs = None # reply is null\n # if reply_id:\n # comment_qs = Comment.objects.get(id=reply_id) \n # comment_use = Comment(\n # commented_by=request.user,\n # for_post=details,\n # content=content,\n # reply=comment_qs\n # )\n # comment_use.save()\n # else:\n # c_form = commentForm()\n # print(f'send {is_favorite}')\n context = {\n # 'is_favorite': is_favorite,\n 'details': details,\n \n # 'comment': comment,\n # 'commentform': c_form,\n }\n # if request.is_ajax():\n # print('Ajax is true')\n # html = render_to_string(\n # 'annonce/comment.html',\n # context, request=request\n # )\n # return JsonResponse({'form': html})\n return render(request, 'Annonce/detail.html', context)","def add_comment_to_announcement():\n vars = request.vars\n logger.info(\"vars.comment_text: %r\" % (vars.comment_text))\n comment_id = db.Comments.insert(\n comment_text = vars.comment_text,\n score = 1,\n ann_id= vars.ann_id,\n )\n comment = db.Announcements(comment_id)\n\n logger.info(\"api:add_comment_to_announcement ==> comment= %r\" % (comment))\n\n return response.json(comment)","def snippet_new(request, template_name='dpaste/snippet_new.html'):\n if request.method == \"POST\":\n snippet_form = SnippetForm(data=request.POST, request=request)\n if snippet_form.is_valid():\n new_snippet = snippet_form.save()\n url = new_snippet.get_absolute_url()\n return HttpResponseRedirect(url)\n else:\n snippet_form = SnippetForm(request=request)\n\n template_context = {\n 'snippet_form': snippet_form,\n 'lexer_list': LEXER_LIST,\n 'is_new': True,\n }\n\n return render_to_response(\n template_name,\n template_context,\n RequestContext(request)\n )","def render_POST(self, request):","def get(self, request):\n form = PostForm()\n context = {\n 'form': form,\n 'success_message': ''\n }\n return render(request, 'posts/new-post.html', context)","def create(thing):\n fields = {}\n errors = []\n\n for col in thing.cols:\n new[col.field_name] = request.form.get(col.field_name)\n if col.required and not new[col.field_name]:\n errors.append('%s cannot be empty' % col.human_name)\n\n if errors:\n for e in errors:\n flash(e)\n add_template_variable('thing', thing)\n add_template_variable('fields', fields)\n return my_render_template('generic/create_post.html')\n\n # insert into database\n\n db = get_db()\n cursor = db.cursor()\n\n # create the two strings we use in the query\n field_names = \"'\" + \"', '\".join(thing.field_names) + \"'\"\n question_marks = \", \".join(map(lambda x: '?', thing.field_names.count() ))\n\n cursor.execute(\"insert into posts (%s) values (%s)\" % (field_names, question_marks), (title, body))\n db.commit()\n new_id = cursor.lastrowid\n\n # show new post to the user\n flash(\"You made a new %s\" % thing.human_name)\n return redirect(url_for('show_one', id_=new_id))","def create_post():\n\n #Get prompt id\n prompt_id = request.form.get('prompt_id')\n\n # Get post text\n post_text = request.form.get('user_post')\n\n # Create post timestamp\n created_at = datetime.now()\n user_facing_date = created_at.strftime(\"%B %d, %Y\")\n\n # Save post and related data to database\n post = crud.create_post(session['user_id'], prompt_id, post_text, session['lat'], session['lng'], session['user_facing_location'], created_at)\n\n return render_template('post_data.html', post=post, user_facing_date=user_facing_date)","def ajax_form_valid(self, form):\n\n try:\n comment = form.save(self.request)\n num_comments = models.CommentModel.objects.permitted().count()\n\n return core_utils.respond_with_json({\n 'success': True,\n 'comment': render_to_string(\n self.template_name,\n RequestContext(self.request, {'comment': comment})\n ),\n 'num_comments': num_comments\n })\n except exceptions.RapidCommentingError as e:\n return core_utils.respond_with_json({\n 'success': False,\n 'reason': e.value\n })","def newreply(request, post_id):\n if not request.user.is_authenticated():\n return redirect('/login/?next=%s' % request.path)\n else:\n\n reply = Reply.objects.create(\n creator = request.user,\n created = datetime.datetime.now(),\n body = request.POST.get('mensaje'),)\n post = Post.objects.get(id = post_id)\n post.reply.add(reply) \n return redirect('/home/')","def submit_comment(book_id):\n \n #Information for inserting\n score = request.form.get(\"score\")\n comment = request.form.get(\"comment\")\n\n if score is None or comment is None:\n return render_template(\"error.html\",message=\"Please submit the complete information.\")\n\n #Inserte a new review\n db.execute(\"INSERT INTO reviewer (id_book, id_user, comment, score_user) VALUES (:id_book, :id_user, :comment, :score_user)\",\n {\"id_book\":book_id, \"id_user\":session[\"user_id\"], \"comment\": comment, \"score_user\": score})\n \n db.commit()\n\n #Get the info of the book\n book = db.execute(\"SELECT * FROM book WHERE id = :book_id\",{\"book_id\": book_id}).fetchone()\n if book is None:\n return render_template(\"error.html\", message = \"No such Book.\")\n\n #Get the reviews joined with the name of the user\n stmt = \"SELECT user_library.*, reviewer.* FROM user_library INNER JOIN reviewer ON user_library.id=reviewer.id_user WHERE id_book = :book_id\"\n reviews = db.execute(stmt,{\"book_id\": book_id}).fetchall()\n\n #Get the user_review info\n user_review = db.execute(\"SELECT * FROM reviewer WHERE id_book = :book_id AND id_user = :user_id\",\n {\"book_id\": book_id, \"user_id\": session[\"user_id\"]}).fetchone()\n\n #If this info not exist we could add a comment, else we can not.\n is_commented = True\n if user_review is None:\n is_commented = False\n\n #Insert a new score if a new comment is introduced\n average_score = db.execute(\"SELECT AVG(score_user) FROM reviewer WHERE id_book = :book_id\",{\"book_id\":book_id}).fetchone()\n average_score = average_score.items()\n average_score = average_score[0]\n average_score = float(average_score[1])\n\n db.execute(\"UPDATE book SET score = :average_score WHERE id = :book_id\", {\"average_score\":average_score, \"book_id\": book_id}) \n db.commit()\n\n #Get the info of the book\n book = db.execute(\"SELECT * FROM book WHERE id = :book_id\",{\"book_id\": book_id}).fetchone()\n if book is None:\n return render_template(\"error.html\", message = \"No such Book.\")\n\n #Proccess for rating count of Goofreaders\n goodreader_info = requests.get(\"https://www.goodreads.com/book/review_counts.json\", params={\"key\": KEY, \"isbns\": book.isbn })\n goodreader_info = goodreader_info.json()\n goodreader_info = goodreader_info[\"books\"]\n\n average_rating = goodreader_info[0][\"average_rating\"]\n ratings_counts = goodreader_info[0][\"ratings_count\"]\n\n return render_template(\"book_info.html\",book=book, reviews = reviews, is_commented = is_commented\n , average_rating = average_rating, ratings_counts = ratings_counts )","def _add_comment():\r\n per_page = current_app.config['FLASKY_ANSWERS_PER_PAGE']\r\n id = request.args.get('answer_id')\r\n answer = Answer.query.get_or_404(id)\r\n comment =request.args.get('comment')\r\n answers = Answer.query.get_or_404(id)\r\n page = 1\r\n result= False\r\n if current_user.can(Permission.COMMENT):\r\n comment = Comment(body=comment,\r\n author=current_user._get_current_object(),\r\n answer_id=id)\r\n db.session.add(comment)\r\n db.session.commit()\r\n page = (answer.comments.count()-1)/per_page + 1\r\n result=True\r\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\r\n page,per_page=per_page,error_out=False\r\n )\r\n macro_comment = get_template_attribute(\"_comments.html\", \"render_comments\")\r\n macro_page = get_template_attribute(\"_page.html\", \"render_page\")\r\n comments = pagination.items\r\n return jsonify({'result': result,\r\n 'comment_html': macro_comment(comments),\r\n 'page_html': macro_page(pagination),\r\n 'comments_timestamp': [comment.timestamp for comment in comments],\r\n 'comments_id': [comment.id for comment in comments]\r\n })","def create_post(request):\n if request.method == 'POST':\n title = request.POST['title']\n content = request.POST['content']\n user_id = request.POST['author_id']\n category = request.POST['category']\n\n slug = \"-\".join(list(map(lambda word: word.lower(), title.split())))\n author = User.objects.get(id=int(user_id))\n\n # save info in models\n post = Post()\n post.author = author\n post.category = category\n post.title = title\n post.content = content\n post.slug = slug\n post.save()\n return redirect('post')\n\n return render(request, 'posts/create_post.html')","def handle_comments(self):\r\n comments = Comment.objects.all()\r\n for c in comments:\r\n new = ThreadedComment(\r\n content_type = c.content_type,\r\n object_id = c.object_id,\r\n comment = c.comment,\r\n user = c.user,\r\n date_submitted = c.submit_date,\r\n date_modified = c.submit_date,\r\n date_approved = c.submit_date,\r\n is_public = c.is_public,\r\n ip_address = c.ip_address,\r\n is_approved = not c.is_removed\r\n )\r\n new.save()","def add():\n if request.method == 'GET':\n return render_template('add.html')\n elif request.method == 'POST':\n data = {}\n for key in ('h', 'name', 'summary', 'content', 'published', 'updated', 'category',\n 'slug', 'location', 'in-reply-to', 'repost-of', 'syndication'):\n data[key] = None\n\n for title in request.form:\n data[title] = request.form[title]\n\n for title in request.files:\n data[title] = request.files[title].read()\n\n try:\n photo = request.files['photo']\n except:\n photo = None\n\n for key in data:\n if data[key] == \"\":\n data[key] = None\n\n data['published'] = datetime.now()\n\n location = create_entry(data, image=data['photo'], g=g)\n\n if data['in-reply-to']:\n send_mention('http://' + DOMAIN_NAME + '/e/'+location, data['in-reply-to'])\n\n if request.form.get('twitter'):\n t = Timer(30, bridgy_twitter, [location])\n t.start()\n\n if request.form.get('facebook'):\n t = Timer(30, bridgy_facebook, [location])\n t.start()\n return redirect(location)\n else:\n return redirect('/404'), 404","def post(self, request):\n pass","def free_comment(request, content_type=None, object_id=None, edit_id=None, parent_id=None, add_messages=False, ajax=False, model=FreeThreadedComment, form_class=FreeThreadedCommentForm, context_processors=[], extra_context={}):\r\n if not edit_id and not (content_type and object_id):\r\n raise Http404 # Must specify either content_type and object_id or edit_id\r\n if \"preview\" in request.POST:\r\n return _preview(request, context_processors, extra_context, form_class=form_class)\r\n if edit_id:\r\n instance = get_object_or_404(model, id=edit_id)\r\n else:\r\n instance = None\r\n _adjust_max_comment_length(form_class)\r\n form = form_class(request.POST, instance=instance)\r\n if form.is_valid():\r\n new_comment = form.save(commit=False)\r\n if not edit_id:\r\n new_comment.ip_address = request.META.get('REMOTE_ADDR', None)\r\n new_comment.content_type = get_object_or_404(ContentType, id = int(content_type))\r\n new_comment.object_id = int(object_id)\r\n if model == ThreadedComment:\r\n new_comment.user = request.user\r\n if parent_id:\r\n new_comment.parent = get_object_or_404(model, id = int(parent_id))\r\n new_comment.save()\r\n if model == ThreadedComment:\r\n if add_messages:\r\n request.user.message_set.create(message=\"Your message has been posted successfully.\")\r\n else:\r\n request.session['successful_data'] = {\r\n 'name' : form.cleaned_data['name'],\r\n 'website' : form.cleaned_data['website'],\r\n 'email' : form.cleaned_data['email'],\r\n }\r\n if ajax == 'json':\r\n return JSONResponse([new_comment,])\r\n elif ajax == 'xml':\r\n return XMLResponse([new_comment,])\r\n else:\r\n return HttpResponseRedirect(_get_next(request))\r\n elif ajax==\"json\":\r\n return JSONResponse({'errors' : form.errors}, is_iterable=False)\r\n elif ajax==\"xml\":\r\n template_str = \"\"\"\r\n<errorlist>\r\n {% for error,name in errors %}\r\n <field name=\"{{ name }}\">\r\n {% for suberror in error %}<error>{{ suberror }}</error>{% endfor %}\r\n </field>\r\n {% endfor %}\r\n</errorlist>\r\n \"\"\"\r\n response_str = Template(template_str).render(Context({'errors' : zip(form.errors.values(), form.errors.keys())}))\r\n return XMLResponse(response_str, is_iterable=False)\r\n else:\r\n return _preview(request, context_processors, extra_context, form_class=form_class)","def editor_save():\n markdown = request.form.get('markdown')\n html = request.form.get('html')\n title = request.form.get('title')\n if 'post_id' in request.form:\n post_id = int(request.form.get('post_id'))\n edit_post = Post.query.get(post_id)\n edit_post.markdown = markdown\n edit_post.html = html\n edit_post.title = title\n db.session.add(edit_post)\n db.session.commit()\n return jsonify(saved_success=True, new_post=None, post_id=None)\n else:\n new_post = Post(markdown=markdown, html=html, title=title);\n db.session.add(new_post)\n db.session.commit()\n return jsonify(saved_success=True, new_post=True, post_id=new_post.id)","def render_form(self, title=\"\", body=\"\", error=\"\"):\n self.render(\"newpost.html\", title=title, body=body, error=error)","def add_feedback(username):\n form = addFeedback()\n\n if \"user\" not in session: \n flash(\"Not logged in\")\n return redirect('/login')\n \n elif form.validate_on_submit():\n title = form.title.data\n content = form.content.data\n recipient = username\n user = session[\"user\"]\n\n new_feedback = Feedback(title=title, content=content, recipient=recipient, user=user)\n db.session.add(new_feedback)\n db.session.commit()\n\n flash(\"Added feedback\")\n return redirect(f'/users/{username}')\n else:\n return render_template(\"feedback_form.html\", form=form, username=username)","def create_post(request):\n\n # modified from: http://django-angular.readthedocs.org/en/latest/angular-model-form.html\n\n # get data\n in_data = getRequestData(request)\n\n try:\n # save in database\n # note that in_data.mytitle throws an error while in_data.get('mytitle') works smoothly\n post = Thread(pub_date = datetime.datetime.now(pytz.timezone('US/Eastern')), username = in_data.get('myusername'), title = in_data.get('mytitle'), description = in_data.get('mydescription'))\n post.save()\n except:\n return HttpResponseBadRequest('Error saving to database!')\n\n return JsonResponse(in_data)","def _comment():\r\n id = request.args.get('answer_id')\r\n per_page=current_app.config['FLASKY_ANSWERS_PER_PAGE']\r\n answer = Answer.query.get_or_404(id)\r\n page = request.args.get('page', type=int, default=1)\r\n comment =request.args.get('comment')\r\n if current_user.can(Permission.COMMENT) and comment is not None:\r\n comment = Comment(body=comment,\r\n author=current_user._get_current_object(),\r\n answer_id=id)\r\n db.session.add(comment)\r\n db.session.commit()\r\n page = -1\r\n if page == -1:\r\n page = answer.comments.count() / per_page\r\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\r\n page,per_page=per_page,error_out=False\r\n )\r\n macro_comment = get_template_attribute(\"_comments.html\", \"render_comments\")\r\n macro_page = get_template_attribute(\"_page.html\", \"render_page\")\r\n comments = pagination.items\r\n return jsonify({'result': True,\r\n 'comment_html': macro_comment(comments),\r\n 'page_html':macro_page(pagination),\r\n 'comments_timestamp':[comment.timestamp for comment in comments],\r\n 'comments_id':[comment.id for comment in comments]\r\n })","def test_editing_post_comment(self):\n\n form_data = {\"comment\": \"Here's my new comment!\"}\n new_comment = edit_post_comment(1, form_data)\n\n self.assertIn(\"my new comment\", new_comment.comment_body)","def feature_comment(request, id=id):\n feature = get_object_or_404(Feature, id=id)\n comment_form = FeatureCommentForm(request.POST, request.FILES)\n if comment_form.is_valid():\n comment = comment_form.save(commit=False)\n comment.user = request.user\n comment.feature = feature\n comment_form.save()\n return redirect(feature_detail, id)","def add_comment(request):\n \n \"\"\"\n device type\n \"\"\"\n is_Mobile = dmb.process_request(request)\n \n \"\"\"\n User validation \n \"\"\"\n \n \n if request.user.is_anonymous():\n return comm.redirect_login_path(is_Mobile, request)\n result = dayword_comment(request, 1) \n return HttpResponse(json.dumps(result), content_type='application/json')"],"string":"[\n \"def comments_new():\\n comment = {\\n \\\"title\\\": request.form.get(\\\"title\\\"),\\n \\\"content\\\": request.form.get(\\\"content\\\"),\\n \\\"playlist_id\\\": ObjectId(request.form.get(\\\"playlist._id\\\")),\\n }\\n print(comment)\\n comment_id = db.comments.insert_one(comment).inserted_id\\n return redirect(\\n url_for(\\\"playlists.playlists_show\\\", playlist_id=request.form.get(\\\"playlist._id\\\"))\\n )\",\n \"def save_comments():\\n potential_deal_id = int(request.form.get(\\\"id\\\"))\\n action = request.form.get(\\\"action\\\")\\n if action.lower() == \\\"none\\\":\\n action = None\\n comments = request.form.get(\\\"comments\\\")\\n db_handler = DBHandler()\\n db_handler.update_by_id(potential_deal_id, action, comments)\\n # return redirect(url_for(\\\"home\\\"))\\n return jsonify({\\\"success\\\": True}), 200\",\n \"def add_comment(request):\\n if request.method != 'POST':\\n return HttpResponseRedirect(reverse('wainz.views.composite'))\\n else:\\n img_id = request.POST['id']\\n try:\\n img = Image.objects.get(pk=img_id)\\n except:\\n return HttpResponseRedirect(reverse('wainz.views.composite'))\\n comment_text = request.POST['comment']\\n #TODO sanitize input\\n comment = ImageComment()\\n comment.submission_date = timezone.now()\\n comment.comment_text= comment_text\\n comment.image_id = img_id\\n comment.submitter_id = int(request.POST['uid'])\\n comment.save()\\n return rest.rest_success(request, img_id)\",\n \"def on_comment(self, request, board_id):\\n error = None\\n if request.method == 'POST':\\n creator = request.form['creator']\\n comment = request.form['comment']\\n if len(creator) > 30:\\n error = 'creator name too long'\\n elif len(comment) > 50:\\n error = 'comment too long'\\n else:\\n self.insert_comment(request, board_id)\\n return redirect('/board:' + board_id)\\n return self.render_template('comment.html', error=error)\",\n \"def post(self, request, pk):\\n\\n post = Blog.objects.get(pk=int(pk))\\n user_id = self.request.session.get('USER_ID')\\n\\n try:\\n user = User.objects.get(pk=user_id)\\n except:\\n pass\\n body = self.request.POST.get('body')\\n\\n if user_id is None:\\n messages.add_message(request, messages.ERROR, \\\"Please login to add comments.\\\")\\n return HttpResponseRedirect(self)\\n\\n comments = Comment.objects.create(post=post, author=user, body=body)\\n\\n d = model_to_dict(post)\\n messages.add_message(request, messages.SUCCESS, \\\"Comment added successfully.\\\")\\n return self.render_to_response(d)\",\n \"def newcomment(id):\\n\\n if g.is_logged == False:\\n flash (\\\"You need to be logged in\\\")\\n return redirect(url_for('show_place', id=id))\\n\\n if request.method == 'POST':\\n rating = request.form['rating']\\n\\n if rating.isdigit() == False:\\n flash (\\\"Rating must be between a number between 0 and 5 (inclusive)\\\")\\n elif int(rating) < 0 or int(rating) > 5:\\n flash (\\\"Rating must be between 0 and 5 (inclusive)\\\")\\n else:\\n db = get_db()\\n db.execute('''insert into reviews (rating, title, message, user_id, place_id) values (?, ?, ?,?,?)''', [rating, request.form['title'], request.form['content'], g.user_id, id])\\n db.commit()\\n\\n flash('Your comment was successfully added')\\n return redirect(url_for('show_place', id=id))\",\n \"def post_comment(id):\\n \\n form = CommentForm()\\n title = 'post comment'\\n post = Post.query.filter_by(id=id).first()\\n\\n if post is None:\\n\\n abort(404)\\n\\n if form.validate_on_submit():\\n comment = form.comment.data\\n new_comment = Comments(opinion = comment, user_id = current_user.id, posts_id = post.id)\\n new_comment.save_comment()\\n return redirect(url_for('main.view_post', id = post.id))\\n\\n return render_template('comments.html', form = form, title = title)\",\n \"def createcomment(request, pk):\\n issue = get_object_or_404(Issue, pk=pk)\\n if request.method == \\\"POST\\\":\\n form = CommentCreationForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.issue = issue\\n comment.author = request.user\\n comment.created_at = timezone.now()\\n comment.save()\\n return redirect('office:issue', pk=pk)\\n else:\\n form = CommentForm()\\n return render(request, 'blog/add_comment_to_post.html', {'form': form})\",\n \"def form_valid(self, form):\\n post = self.get_object()\\n #WAS: post.comment_add(form.cleaned_data['text'], self.request.user)\\n post.add_comment(form.cleaned_data['text'], \\n self.request.user,\\n added_at=None, \\n by_email=False\\n )\\n return views_support.response_success(self.request)\",\n \"def post_comment(request, next=None, using=None):\\n # Fill out some initial data fields from an authenticated user, if present\\n data = request.POST.copy()\\n if request.user.is_authenticated():\\n if not data.get('name', ''):\\n data[\\\"name\\\"] = request.user.get_full_name() or request.user.username\\n if not data.get('email', ''):\\n data[\\\"email\\\"] = request.user.email\\n\\n # Check to see if the POST data overrides the view's next argument.\\n next = data.get(\\\"next\\\", next)\\n\\n # Look up the object we're trying to comment about\\n ctype = data.get(\\\"content_type\\\")\\n object_pk = data.get(\\\"object_pk\\\")\\n model = models.get_model(*ctype.split(\\\".\\\", 1))\\n target = model._default_manager.using(using).get(pk=object_pk)\\n\\n\\n # Construct the comment form\\n form = comments.get_form()(target, data=data)\\n\\n # Check security information\\n if form.security_errors():\\n return None\\n # Create the comment\\n comment = form.get_comment_object()\\n comment.ip_address = request.META.get(\\\"REMOTE_ADDR\\\", None)\\n if request.user.is_authenticated():\\n comment.user = request.user\\n\\n # Signal that the comment is about to be saved\\n responses = signals.comment_will_be_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n # Save the comment and signal that it was saved\\n comment.save()\\n message = get_object_or_404(Message, pk = object_pk)\\n message.envoyer_commentaire_notification(comment.pk, request.user.username)\\n \\n signals.comment_was_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n comment_list = [comment]\\n return render_to_response('comments/list.html', {'comment_list': comment_list},context_instance=RequestContext(request))\",\n \"def comment_add(request,comment=None, error='', message=''):\\n categories = Category.objects.all()\\n error_fields=[]\\n default_comment = Comment(date=datetime.date.today(), time=datetime.datetime.now().time, source='', detail='', category=Category.objects.filter(description='Events')[0], user_email='')\\n\\n try:\\n added = bool(request.POST['add'])\\n except:\\n added = False\\n try:\\n action = request.POST['action']\\n except:\\n action = 'add'\\n\\n if added == True:\\n try:\\n new_date = parse(request.POST['date'], dayfirst=True)\\n new_time = parse(request.POST['time'])\\n except:\\n error += ' Datetime invalid or not specified.'\\n\\n try:\\n new_detail = request.POST['detail']\\n if new_detail == '':\\n error += ' Comment text is blank.'\\n except:\\n error += ' No comment text provided.'\\n\\n try:\\n new_source = request.POST['source']\\n if new_source == '':\\n error += ' Source is blank.'\\n except:\\n error += ' No comment source provided.'\\n\\n try:\\n new_category = Category.objects.filter(pk=int(request.POST['category_id']))[0] #The [0] is OK since the fact that category_id is a primary key ensures that the array has only length 1.\\n except:\\n error += ' Category invalid or nonexistent.'\\n\\n try:\\n new_user_email = request.POST['user_email']\\n if new_user_email == '':\\n error += ' You haven\\\\'t provided your e-mail address.'\\n except:\\n error += ' No user e-mail address provided.'\\n\\n if error == '':\\n try:\\n new_comment = Comment(date=new_date, time=new_time, source=new_source, detail=new_detail, category=new_category, user_email=new_user_email)\\n new_comment.full_clean()\\n try:\\n new_comment.save()\\n message += 'Your comment was added to the database.'\\n except:\\n error += 'Failed to access the database.'\\n except ValidationError as ve:\\n for k in ve.message_dict.keys():\\n error_fields.append(k)\\n for m in ve.message_dict[k]:\\n error += m + ' '\\n default_comment = new_comment\\n\\n if action == 'saveandaddanother' or action == 'add' or error != '':\\n return render_to_response('feedback/comment_add.html',\\n {'categories': categories,\\n 'error': error,\\n 'error_fields': error_fields,\\n 'message': message,\\n 'added': added,\\n 'comment': default_comment},\\n context_instance=RequestContext(request))\\n elif action == 'save':\\n return index(request, error=error, message=message)\\n else:\\n error += 'Invalid submit action requested.'\\n return render_to_response('feedback/comment_add.html',\\n {'categories': categories,\\n 'error': error,\\n 'error_fields': error_fields,\\n 'added': added,\\n 'message': message,\\n 'comment': default_comment},\\n context_instance=RequestContext(request))\",\n \"def add_comment_to_post(request, pk):\\n post = get_object_or_404(Post, pk=pk)\\n if request.method == 'POST':\\n form = CommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.post = post\\n comment.save()\\n return redirect('post_detail', pk=post.pk)\\n else:\\n form = CommentForm()\\n return render(request, 'blog/comment_form.html', {'form': form})\",\n \"def community_post_create_view(request):\\n task = \\\"Create New\\\"\\n form = AddEditPostForm() # An unbound form\\n\\n if request.method == 'POST': # If the form has been submitted...\\n form = AddEditPostForm(request.POST, request.FILES) # A form bound to the POST data\\n if form.is_valid(): # All validation rules pass\\n post = form.save(commit=False) # Create a new object from the form, but don't save it to the database\\n post.author = request.user # Set the author to the current user\\n post.save() # Save the object to the database\\n slug_str = \\\"%s %s\\\" % (post.title, post.date_posted) # Create a slug from the title and date\\n post.slug = slugify(slug_str) # Create the slug\\n post.save() # Save the object to the database\\n return redirect('community-home') # Redirect to the home page\\n\\n context = { # Pass the variables to the template\\n 'task': task,\\n 'form': form,\\n }\\n return render(request,\\n 'pages/patient-community/community-create-update-post.html',\\n context) # render the patient community create post page\",\n \"def add_comment_view(request, e_pk):\\n\\n element = get_object_or_404(Element, pk=e_pk)\\n group = element.tab.group\\n\\n if request.user not in group.users.all():\\n return redirect(reverse('my_groups_view'))\\n\\n if request.method == 'POST':\\n form = CreateCommentForm(request.POST)\\n if form.is_valid():\\n comment = Comment(\\n text=form.cleaned_data['text'],\\n creator=request.user,\\n element=element,\\n )\\n comment.save()\\n else:\\n return HttpResponseBadRequest()\\n\\n return redirect(reverse('element_view', args=(e_pk,)))\",\n \"def post(self):\\n comment_id = self.request.get('comment_id')\\n post_id = self.request.get('post_id')\\n comment = Comment.get_by_id(int(comment_id), parent=comment_key())\\n post = Post.get_by_id(int(post_id), parent=blog_key())\\n if comment and self.user.key().id() == comment.user.key().id():\\n comment.content = self.request.get('content')\\n\\n have_errors = False\\n\\n if not comment.content:\\n error_content = \\\"Content is required\\\"\\n have_errors = True\\n\\n if have_errors:\\n self.render(\\\"edit_comment.html\\\",\\n comment=comment,\\n error_content=error_content,\\n user=self.user)\\n else:\\n comment.put()\\n time.sleep(0.1)\\n\\n self.redirect('/blog/%s' % str(post.key().id()))\",\n \"def form_valid(self, form):\\n action = self.get_object()\\n #WAS: return action.comment_add(form.cleaned_data['text'], self.request.user)\\n action.comment_add(form.cleaned_data['text'], self.request.user)\\n return views_support.response_success(self.request)\",\n \"def add_comment(request, listing_id):\\n if request.method == \\\"POST\\\":\\n try:\\n listing = Listing.objects.get(pk=listing_id)\\n except Listing.DoesNotExist:\\n return render(request, \\\"auctions/errors.html\\\", {\\\"error_message\\\":\\n \\\"something went wrong, the id url argument is not valid\\\"})\\n\\n CommentForm = modelform_factory(Comment, exclude=(\\\"commenter\\\",\\\"listing\\\"))\\n # validate and save from the formdata to the database\\n form = CommentForm(request.POST)\\n try:\\n comment = form.save(commit=False)\\n comment.commenter = request.user\\n comment.listing = listing\\n comment.save()\\n except:\\n # if something went wrong with comment form \\n return render(request, \\\"auctions/errors.html\\\", {\\\"error_message\\\":\\n \\\"something went wrong with the submission of your comment, try again\\\"})\\n\\n return redirect(reverse(\\\"single_listing\\\", \\n args=[listing.title]) +f\\\"?id={listing.id}\\\")\",\n \"def post(self):\\n modified_content = self.request.get('comment_edit')\\n comment_id = self.request.get('comment_id')\\n comment = Comments.get_by_id(int(comment_id))\\n user = self.get_active_user()\\n\\n if user.key().id() == comment.submitter_id:\\n comment.content = modified_content\\n comment.put()\\n self.redirect('/%s' % str(comment.post_id))\\n else:\\n self.error(403)\",\n \"def post(self):\\n post_id = int(self.request.get('post_id'))\\n post = Posts.get_by_id(post_id)\\n comment = self.request.get('comment')\\n submitter_id = self.get_active_user().key().id()\\n\\n if submitter_id:\\n comment = Comments(post_id=post_id, content=comment,\\n submitter_id=submitter_id)\\n comment.put()\\n self.redirect('/%s' % str(post.key().id()))\\n else:\\n self.error(403)\",\n \"def create_comment(request):\\n\\n # get data\\n in_data = getRequestData(request)\\n\\n # get the Thread associated with the comments\\n mythread = Thread.objects.get(id=in_data.get('mythreadid'))\\n\\n # save in database\\n try:\\n comment = Comment(pub_date = datetime.datetime.now(pytz.timezone('US/Eastern')), username = in_data.get('myusername'), text = in_data.get('mytext'), score = 0, thread = mythread )\\n comment.save()\\n except:\\n return HttpResponseBadRequest('Error saving to database!')\\n\\n return JsonResponse(in_data)\",\n \"def add_comment(request, entry_pk):\\n\\n blog = get_object_or_404(BlogEntry, pk=entry_pk)\\n\\n if not request.user.is_authenticated():\\n raise PermissionDenied\\n\\n form = BlogCommentForm(creator=request.user, blog=blog, data=request.POST)\\n\\n if form.is_valid():\\n form.save()\\n return HttpResponseRedirect(blog.get_absolute_url())\\n\\n return single(request, entry_pk=entry_pk, comment_form=form)\",\n \"def add_mvcomment(request, pk):\\n\\n # Getting the movie object hosting the comment\\n movie = get_object_or_404(Movie, pk=pk)\\n\\n # if POST\\n if request.method == \\\"POST\\\":\\n form = MovieCommentForm(request.POST)\\n\\n # set the author and redirect if valid form\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.author = request.user\\n comment.movie = movie\\n comment.save()\\n return redirect('../', pk=movie.pk)\\n else:\\n form = MovieCommentForm()\\n\\n # render the form through the template\\n return render(request, {'form': form})\",\n \"def new_from_post():\\n # If you make a post request with a question_id we will assume you want a new question editor\\n # we will prepopulate the question new page with data from that question (if it is a valid question id)\\n question_id = request.form['question_id'] if request.form['question_id'] else ''\\n\\n return render_template('questionNew.html', question_id=question_id)\",\n \"def create_comment(bid, pid):\\n # pylint: disable=unused-argument\\n form = CommentForm(request.form)\\n if request.method == 'POST':\\n if form.validate():\\n DB.session.add(Comment(pid, current_user.uid, form.text.data))\\n DB.session.commit()\\n flash('Comment successfully created!')\\n else:\\n flash(constants.DEFAULT_SUBMISSION_ERR)\\n return redirect(request.referrer)\",\n \"def post(self):\\n\\n # 160 characters limit\\n\\n if len(client_data[\\\"content\\\"]) >= 200:\\n self.write_json_with_status(400,{\\n 'result' : 'fail',\\n 'reason' : 'content too long'\\n })\\n\\n client_data = self.data\\n now = str(time.time())\\n comment_id = md5(client_data['content']+now)\\n\\n new_comment = self.event_comment_table.put_item(data={\\n 'CommentID' : comment_id,\\n 'CreatorID' : creator_id,\\n 'Content' : content,\\n 'EventID' : event_id,\\n 'Timestamp' : now\\n })\\n \\n\\n self.write_json({\\n 'comment_id' : comment_id\\n })\",\n \"def questions_collection(request):\\n if request.method == \\\"POST\\\":\\n data = json.loads(request.body)\\n task = Task.objects.get(id=data.get(\\\"taskId\\\", \\\"\\\"))\\n commenter = User.objects.get(username=data.get(\\\"commenter\\\", \\\"\\\"))\\n content = data.get(\\\"content\\\", \\\"\\\")\\n\\n question = Question(\\n task=task,\\n commenter=commenter,\\n content=content\\n )\\n question.save()\\n return JsonResponse({\\\"message\\\": \\\"Question created successfully\\\"}, status=201)\",\n \"def postVisitView(request, pk, post_id):\\n post = Blogger.objects.get(id=pk).post_set.get(id=post_id)\\n comments = post.comment_set.all().order_by(\\\"-date_created\\\")\\n\\n data = {\\n \\\"user\\\": request.user,\\n \\\"post\\\": post,\\n }\\n\\n form = CommentForm(initial=data)\\n\\n if request.method == \\\"POST\\\":\\n form = CommentForm(request.POST, initial=data)\\n if form.is_valid():\\n form.save()\\n return redirect(f\\\"/blogger/{pk}/post/{post_id}\\\")\\n\\n context = {\\n \\\"post\\\": post,\\n \\\"comments\\\": comments,\\n \\\"form\\\": form,\\n }\\n return render(request, \\\"blog/post_visit.html\\\", context)\",\n \"def post(self):\\n post_id = self.request.get('post_id')\\n post = Post.get_by_id(int(post_id), parent=blog_key())\\n content = self.request.get('comment')\\n\\n if content:\\n comment = Comment(parent=comment_key(),\\n content=content,\\n user=self.user,\\n post=post)\\n comment.put()\\n\\n time.sleep(0.1)\\n self.redirect('/blog/%s' % str(post.key().id()))\",\n \"def post_comment_ajax(request, using=None):\\n if not request.is_ajax():\\n return HttpResponseBadRequest(\\\"Expecting Ajax call\\\")\\n\\n data = request.POST.copy()\\n if request.user.is_authenticated():\\n if not data.get('name', ''):\\n data[\\\"name\\\"] = request.user.get_full_name() or request.user.get_username()\\n if not data.get('email', ''):\\n data[\\\"email\\\"] = request.user.email\\n\\n # Look up the object we're trying to comment about\\n ctype = data.get(\\\"content_type\\\")\\n object_pk = data.get(\\\"object_pk\\\")\\n if ctype is None or object_pk is None:\\n return CommentPostBadRequest(\\\"Missing content_type or object_pk field.\\\")\\n try:\\n model = apps.get_model(*ctype.split(\\\".\\\", 1))\\n target = model._default_manager.using(using).get(pk=object_pk)\\n except TypeError:\\n return CommentPostBadRequest(\\n \\\"Invalid content_type value: %r\\\" % escape(ctype))\\n except AttributeError:\\n return CommentPostBadRequest(\\n \\\"The given content-type %r does not resolve to a valid model.\\\" % escape(ctype))\\n except ObjectDoesNotExist:\\n return CommentPostBadRequest(\\n \\\"No object matching content-type %r and object PK %r exists.\\\" % (\\n escape(ctype), escape(object_pk)))\\n except (ValueError, ValidationError) as e:\\n return CommentPostBadRequest(\\n \\\"Attempting go get content-type %r and object PK %r exists raised %s\\\" % (\\n escape(ctype), escape(object_pk), e.__class__.__name__))\\n\\n # Do we want to preview the comment?\\n preview = \\\"preview\\\" in data\\n\\n # Construct the comment form\\n form = django_comments.get_form()(target, data=data)\\n\\n # Check security information\\n if form.security_errors():\\n return CommentPostBadRequest(\\n \\\"The comment form failed security verification: %s\\\" % escape(str(form.security_errors())))\\n\\n # If there are errors or if we requested a preview show the comment\\n if preview:\\n comment = form.get_comment_object() if not form.errors else None\\n if comment is not None and request.user.is_authenticated():\\n comment.user = request.user\\n return _ajax_result(request, form, \\\"preview\\\", comment, object_id=object_pk)\\n if form.errors:\\n return _ajax_result(request, form, \\\"post\\\", object_id=object_pk)\\n\\n # Otherwise create the comment\\n comment = form.get_comment_object()\\n comment.ip_address = get_trusted_ip(request)\\n if request.user.is_authenticated():\\n comment.user = request.user\\n\\n # Signal that the comment is about to be saved\\n responses = signals.comment_will_be_posted.send(\\n sender=comment.__class__,\\n comment=comment,\\n request=request\\n )\\n\\n for (receiver, response) in responses:\\n if response is False:\\n return CommentPostBadRequest(\\n \\\"comment_will_be_posted receiver %r killed the comment\\\" % receiver.__name__)\\n\\n # Save the comment and signal that it was saved\\n comment.save()\\n signals.comment_was_posted.send(\\n sender=comment.__class__,\\n comment=comment,\\n request=request\\n )\\n\\n return _ajax_result(request, form, \\\"post\\\", comment, object_id=object_pk)\",\n \"def _post(self, data):\\n new_comment_id = DB_COMMENT_TABLE.insert(data)\\n return new_comment_id\",\n \"def add_new_comment(request):\\n token = request.data.get('token')\\n text = request.data.get('text', '')\\n post_id = request.data.get('post_id', '')\\n permission = request.data.get('permission')\\n\\n if Token.objects.filter(key=token).exists():\\n if len(text) < 10:\\n return Response({\\\"error\\\": 24})\\n if len(text) > 1000:\\n return Response({\\\"error\\\": 25})\\n\\n if type(post_id) is int:\\n if Post.objects.filter(pk=post_id).exists():\\n token = get_object_or_404(Token, key=token)\\n post = get_object_or_404(Post, pk=post_id)\\n comment = Comment.objects.create(post=post,\\n author_id=token.user_id,\\n text=text,\\n permission=permission)\\n serializer = PostSerializer(post, context={'user_id': token.user_id})\\n UserFeed.objects.create(user=post.author,\\n action_user=token.user,\\n post_comment=comment,\\n action=\\\"PostComment\\\")\\n\\n printable = set(string.printable)\\n msg = filter(lambda x: x in printable, comment.text) \\n message = \\\"{} commented: {}\\\".format(token.user.username, msg)\\n\\n custom = {\\n \\\"post_id\\\": post.id,\\n \\\"avatar\\\": UserProfile.objects.get(user=token.user).avatar.url\\n }\\n\\n if post.author != token.user:\\n user_notification = UserNotification.objects.get(user=post.author)\\n send_notification(custom, message, user_notification)\\n\\n # check @ for users \\n for item in text.split(' '):\\n if item and item[0] == '@':\\n username = item[1:].lower()\\n user = User.objects.filter(username__iexact=username).first()\\n if not user or user == token.user:\\n continue\\n UserFeed.objects.create(user=user,\\n action_user=token.user,\\n post_comment=comment,\\n action=\\\"PostCommentComment\\\")\\n msg = filter(lambda x: x in printable, comment.text) \\n message = \\\"{} commented: {}\\\".format(token.user.username, msg)\\n user_notification = UserNotification.objects.get(user=user)\\n send_notification(custom, message, user_notification)\\n\\n return Response({\\\"success\\\": 26,\\n \\\"post\\\": serializer.data})\\n else:\\n return Response({\\\"error\\\": 27})\\n else:\\n return Response({\\\"error\\\": 17})\",\n \"def add_comment(request, pk, pk2):\\n template_var = base_template_vals(request)\\n p = request.POST\\n \\n if p.has_key(\\\"content\\\") and p[\\\"content\\\"]:\\n if request.user.is_authenticated():\\n comment = Comment(event=Event.objects.get(id=pk))\\n comment.user = UserProfile.objects.get(django_user=request.user)\\n comment.content = p[\\\"content\\\"]\\n comment.save()\\n\\n # Sys notification\\n from_user = UserProfile.objects.get(django_user=pk2) # Who's event that is commented on\\n to_user = Event.objects.get(id=pk).author\\n event_id = pk\\n sys_notification(to_user, \\\"add_comment\\\", from_user, event_id)\\n return single(request, pk)\",\n \"def post(self, post_id):\\n comment_content = self.request.get(\\\"comment_content\\\")\\n Post.add_comment(int(post_id), int(\\n self.user.get_id()), comment_content)\\n self.redirect(\\\"/blog/\\\" + post_id + \\\"/comments\\\")\",\n \"def process_comment(request, comment, post):\\n\\n if request.user.is_authenticated:\\n # We already set auth user's name and email in the form's inital vals.\\n comment.author = request.user\\n\\n # Is this a threaded comment?\\n if request.POST.get(\\\"parent_id\\\"):\\n comment.parent = Comment.objects.get(id=request.POST.get(\\\"parent_id\\\"))\\n\\n # If commenter is logged in, override name and email with stored values from User object\\n if request.user.is_authenticated:\\n comment.name = request.user.get_full_name()\\n comment.email = request.user.email\\n\\n # Set required relationship to Post object\\n comment.post = post\\n\\n # Get commenter's IP and User-Agent string\\n # ip = get_ip(request)\\n # if ip is not None:\\n # comment.ip_address = ip\\n comment.user_agent = request.META.get(\\\"HTTP_USER_AGENT\\\", \\\"\\\")\\n\\n # Run spam check\\n comment.spam = spam_check(comment)\\n\\n # Strip disallowed HTML tags. See tangerine docs to customize.\\n comment.body = sanitize_comment(comment.body)\\n\\n # Call comment approval workflow\\n comment.approved = get_comment_approval(comment.email, request.user.is_authenticated)\\n if comment.approved:\\n messages.add_message(request, messages.SUCCESS, \\\"Your comment has been posted.\\\")\\n else:\\n messages.add_message(request, messages.INFO, \\\"Your comment has been held for moderation.\\\")\\n\\n comment.save()\\n\\n # Alert post author that comment needs moderation, or that it's been auto-published:\\n send_comment_moderation_email(comment)\",\n \"def post(self, request, *args, **kwargs):\\n serializer = CommentSerializer(data=request.data)\\n post_pk = self.kwargs['post_pk']\\n post = Post.objects.get(pk=post_pk)\\n if serializer.is_valid():\\n serializer.save(author=request.user, post=post)\\n return Response(serializer.data, status=status.HTTP_201_CREATED)\\n return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)\",\n \"def create_post():\\r\\n\\r\\n # Check for and reject empty username or whinge\\r\\n if not request.values.get(\\\"username\\\") or not request.values.get(\\\"whinge\\\"):\\r\\n print(\\\"Ignoring request to with empty username or whinge\\\")\\r\\n else:\\r\\n # Form data ok; add to DB\\r\\n con = get_db()\\r\\n con.execute(\\\"INSERT INTO posts (submitter,content,ts) VALUES (?,?,?);\\\",\\r\\n (\\r\\n request.values.get(\\\"username\\\"), # form field username -> DB column submitter\\r\\n request.values.get(\\\"whinge\\\"), # form field whinge -> DB column content\\r\\n time.time()\\r\\n )\\r\\n )\\r\\n con.commit()\\r\\n con.close()\\r\\n \\r\\n # TODO: Handle possibility of failed INSERT\\r\\n\\r\\n # Send them back to the main page\\r\\n return redirect(url_for(\\\"display_top\\\"))\",\n \"def post_detail(request, pk):\\n post = get_object_or_404(Post, pk=pk)\\n comments = post.comments.all\\n post.views += 1\\n post.save()\\n \\n if request.method == \\\"POST\\\":\\n comment_form = CommentForm(request.POST)\\n if comment_form.is_valid() and request.user:\\n new_comment = comment_form.save(commit=False)\\n new_comment.post = post\\n new_comment.author = request.user\\n new_comment.save()\\n elif request.user:\\n comment_form = CommentForm()\\n \\n return render(request, \\\"details.html\\\", {\\\"post\\\": post, \\\"comments\\\": comments, \\\"comment_form\\\": comment_form})\",\n \"def post(self):\\n\\n subject = self.request.get('subject')\\n content = self.request.get('content')\\n\\n have_errors = False\\n\\n if not subject:\\n error_subject = \\\"Please write down the subject\\\"\\n have_errors = True\\n if not content:\\n error_content = \\\"Content is required\\\"\\n have_errors = True\\n\\n if have_errors:\\n self.render(\\\"newpost.html\\\",\\n subject=subject,\\n content=content,\\n error_subject=error_subject,\\n error_content=error_content,\\n user=self.user)\\n else:\\n post = Post(parent=blog_key(),\\n subject=subject,\\n content=content,\\n user=self.user)\\n post.put()\\n self.redirect('/blog/%s' % str(post.key().id()))\",\n \"def post(self, request, *args, **kwargs):\\n del request, args, kwargs # unused\\n self.enforce_xsrf(self.ACTION_ID)\\n\\n notes = []\\n for param_key, value in self.request.POST.items():\\n if param_key.startswith('note.'):\\n note = model.Note.get(self.env.repo, param_key[5:])\\n if note:\\n if value in ['accept', 'flag']:\\n note.reviewed = True\\n if value == 'flag':\\n note.hidden = True\\n notes.append(note)\\n db.put(notes)\\n\\n return django.shortcuts.redirect(self.build_absolute_path())\",\n \"def add_accomment(request, pk):\\n\\n actor = get_object_or_404(Actor, pk=pk)\\n if request.method == \\\"POST\\\":\\n form = ActorCommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.author = request.user\\n comment.actor = actor\\n comment.save()\\n return redirect('../', pk=actor.pk)\\n else:\\n form = ActorCommentForm()\\n return render(request, {'form': form})\",\n \"def post():\\n\\n form = forms.PostForm()\\n if form.validate_on_submit():\\n models.Post.create(title=form.title.data,\\n date=form.date.data,\\n time_spent=form.time_spent.data,\\n details=form.details.data,\\n remember=form.remember.data)\\n return redirect(url_for('index'))\\n return render_template('new.html', form=form)\",\n \"def add_component_comment(request):\\n try:\\n person = get_person(request)\\n\\n print(\\\"Add components comment. Start.\\\")\\n print(\\\"Add components comment. Request: \\\" + str(request))\\n\\n if request.method == \\\"POST\\\":\\n # get values from form\\n assessment_id = request.POST['assessment_id']\\n element_id = None\\n try:\\n component_id = request.POST['component_id']\\n except:\\n component_id = None\\n try:\\n subcomponent_id = request.POST['subcomponent_id']\\n except:\\n subcomponent_id = None\\n try:\\n third_component_id = request.POST['third_component_id']\\n except:\\n third_component_id = None\\n try:\\n fourth_component_id = request.POST['fourth_component_id']\\n except:\\n fourth_component_id = None\\n try:\\n fifth_component_id = request.POST['fifth_component_id']\\n except:\\n fifth_component_id = None\\n comment = request.POST['textComments']\\n\\n if fifth_component_id:\\n element_id = fifth_component_id\\n else:\\n if fourth_component_id:\\n element_id = fourth_component_id\\n else:\\n if fifth_component_id:\\n element_id = fifth_component_id\\n else:\\n if third_component_id:\\n element_id = third_component_id\\n else:\\n if subcomponent_id:\\n element_id = subcomponent_id\\n else:\\n if component_id:\\n element_id = component_id\\n\\n # get section and assessment\\n component = Component.objects.get(id=element_id)\\n\\n print(\\\"Add components comment. Component: \\\" + component.name)\\n print(\\\"Add components comment. comment: \\\" + comment)\\n\\n # create comment\\n my_comment = AssessmentComponentComment()\\n my_comment.assessment = Assessment.objects.get(id=assessment_id)\\n my_comment.element = component\\n my_comment.comment = comment\\n my_comment.person = person\\n my_comment.save()\\n\\n # trace action\\n trace_action(TRACE_COMMENT, person, \\\"User added comment in component: \\\" + component.name)\\n\\n # send mail\\n try:\\n send_mail = request.POST['send_mail']\\n t = Thread(target=send_comments_email, args=(my_comment.comment, \\\"Element: \\\" + component.name, person))\\n t.start()\\n # send_comments_email(my_comment.comment, section, person)\\n except:\\n # checkbox not set\\n pass\\n\\n # redirect to section page\\n url_to_redirect = \\\"/component_2/\\\" + assessment_id + SLASH\\n\\n if component_id:\\n url_to_redirect += component_id + SLASH\\n if subcomponent_id:\\n url_to_redirect += subcomponent_id + SLASH\\n if third_component_id:\\n url_to_redirect += third_component_id + SLASH\\n if fourth_component_id:\\n url_to_redirect += fourth_component_id + SLASH\\n if fifth_component_id:\\n url_to_redirect += fifth_component_id + SLASH\\n\\n return redirect(url_to_redirect, context_instance=RequestContext(request))\\n else:\\n raise Exception(\\\"GET call to add new section comment\\\")\\n except:\\n if debug_is_on():\\n raise\\n else:\\n return render_to_response(TEMPLATE_ERROR, {\\\"error_description\\\": sys.exc_info(), \\\"crpt_url\\\": CRPT_URL},\\n context_instance=RequestContext(request))\",\n \"def post_comment(self):\\n self.post_question()\\n return self.client.post(\\\"api/v2/1/comments\\\", headers={\\\"Authorization\\\": \\\"{}\\\".format(self.token())}, data=json.dumps(self.comment), content_type='application/json')\",\n \"def add():\\n if request.method == \\\"POST\\\":\\n result = add_post(\\n request.form[\\\"title\\\"],\\n request.form[\\\"body\\\"]\\n )\\n flash(result)\\n return redirect(url_for(\\\"show\\\"))\\n else:\\n return render_template(\\\"add.html\\\")\",\n \"def write_review(request):\\n form = ReviewForm\\n\\n if request.method == 'POST':\\n form_data = {\\n 'title': request.POST['title'],\\n 'description': request.POST['description'],\\n 'author': request.POST['author'],\\n }\\n\\n form = ReviewForm(form_data)\\n\\n if form.is_valid:\\n form.save()\\n messages.success(\\n request, f'Review added successfully! Thanks!')\\n else:\\n messages.error(\\n request, f'Upps something went wrong, please try again')\\n\\n context = {\\n 'form': form\\n }\\n return render(request, 'reviews/write_review.html', context)\",\n \"def submit_textarea():\\n print(\\\"--- submit ---\\\")\\n post_content = request.form[\\\"content\\\"]\\n author = request.form[\\\"author\\\"]\\n\\n post_object = {\\n 'author': author,\\n 'content': post_content,\\n }\\n\\n # Submit a transaction\\n new_tx_address = \\\"{}/new_transaction\\\".format(BASE_URL)\\n\\n requests.post(new_tx_address,\\n json=post_object,\\n headers={'Content-type': 'application/json'})\\n\\n return redirect('/')\",\n \"def add_comment(request, model, object_id):\\n obj = get_object_or_404(model, id=object_id)\\n if request.method == \\\"POST\\\":\\n form = CommentForm(request.POST)\\n if form.is_valid():\\n Comment.objects.create(\\n content_type = ContentType.objects.get_for_model(model),\\n object_id = object_id,\\n author = request.user,\\n added_at = datetime.datetime.now(),\\n comment = form.cleaned_data['comment']\\n )\\n if request.is_ajax():\\n return JsonResponse({'success': True})\\n else:\\n return HttpResponseRedirect(obj.get_absolute_url())\\n elif request.is_ajax():\\n return JsonResponse({'success': False, 'errors': form.errors})\\n else:\\n form = CommentForm()\\n\\n # Let the appropriate fallback view take care of display/redisplay\\n if model is Question:\\n return question_comments(request, obj, form=form)\\n elif model is Answer:\\n return answer_comments(request, object_id, answer=obj, form=form)\",\n \"def new_post(request):\\n if request.method != 'POST':\\n # No data submitted; create a blank form.\\n form = PostForm()\\n else:\\n # POST data submitted; process data.\\n form = PostForm(data=request.POST)\\n if form.is_valid():\\n new_post = form.save(commit=False)\\n new_post.owner = request.user\\n new_post.save()\\n return redirect('blogs:posts')\\n\\n # Display a blank or invalid form.\\n context = {'form': form}\\n return render(request, 'blogs/new_post.html', context)\",\n \"def signup(request, entry_id):\\n harvest = get_object_or_404(Harvest, pk=entry_id)\\n if request.method == 'POST':\\n form = HarvestSignupForm(request.POST)\\n if form.is_valid():\\n username = form.cleaned_data['username']\\n password = form.cleaned_data['password']\\n user = authenticate(username=username, password=password)\\n login(request, user)\\n harvest = get_object_or_404(Harvest, pk=entry_id)\\n volunteer = Volunteer.objects.get(user=user)\\n harvest.volunteers.add(volunteer)\\n print form.cleaned_data['comments']\\n new_comment = Comment(volunteer=volunteer, comment=form.cleaned_data['comments'])\\n new_comment.save()\\n harvest.comment.add(new_comment)\\n return HttpResponse(\\\"Thanks! You're signed up.\\\")\\n else:\\n form = HarvestSignupForm()\\n return render_to_response(\\\"signup.html\\\", {'form':form, 'harvest':harvest}, context_instance=RequestContext(request))\",\n \"def post(self):\\n subject = self.request.get('subject')\\n post_content = self.request.get('post_content')\\n submit = self.request.get('submit')\\n cancel = self.request.get('cancel')\\n user = self.get_active_user()\\n created_by = int(user.key().id())\\n post_id = self.request.get('post_id')\\n\\n if not user:\\n self.redirect('/login')\\n if post_id:\\n post = Posts.get_by_id(int(post_id))\\n else:\\n post = None\\n\\n if cancel == \\\"cancel\\\":\\n self.redirect('/%s' % str(post.key().id()))\\n return\\n if (post and post.submitter_id == user.key().id()) or not post:\\n if submit == \\\"submit\\\" and subject and post_content:\\n if post:\\n post.subject = subject\\n post.content = post_content\\n post.put()\\n else:\\n post = Posts(subject=subject,\\n content=post_content,\\n submitter_id=created_by)\\n post.put()\\n self.redirect('/%s' % str(post.key().id()))\\n else:\\n self.render_newpage(user=user,\\n subject=subject,\\n post_content=post_content,\\n error=\\\"\\\"\\\"Please provide both a subject and a\\n post!\\\"\\\"\\\")\\n else:\\n self.redirect('/login')\",\n \"def comment(request, object_id):\\n send_charob = request.user.char_ob\\n rec_charob = get_character_from_ob(object_id)\\n comment_txt = request.POST[\\\"comment\\\"]\\n roster.create_comment(send_charob, rec_charob, comment_txt)\\n return HttpResponseRedirect(reverse(\\\"character:sheet\\\", args=(object_id,)))\",\n \"def admincreate(object):\\n if request.method == \\\"POST\\\":\\n\\n db = get_db()\\n execute_string = 'INSERT INTO ' + object.title()\\n\\n if object == 'post':\\n execute_string += '(title, content, authorId, categoryId) VALUES (\\\"' + request.form['title'] + '\\\", \\\"' + request.form[\\\"content\\\"] + '\\\", \\\"' + request.form[\\\"authorid\\\"] + '\\\", \\\"' + request.form[\\\"categoryid\\\"] + '\\\")'\\n elif object == 'author':\\n execute_string += '(name) VALUES (\\\"' + request.form['name'] + '\\\")'\\n elif object == 'category':\\n execute_string += '(name, description) VALUES (\\\"' + request.form['name'] + '\\\", \\\"' + request.form[\\\"description\\\"] + '\\\")'\\n\\n db.execute(execute_string)\\n db.commit()\\n return redirect(url_for(\\\"adminview\\\", object=object))\\n\\n return render_template(\\\"new.html\\\", object=object, item={})\",\n \"def new_post():\\n form = PostForm()\\n if form.validate_on_submit():\\n post = Post(pub_date=datetime.date.today())\\n post.title = form.title.data\\n post.content = form.content.data\\n post.slug = slugify(post.title)\\n db.session.add(post)\\n db.session.commit()\\n return flask.redirect(flask.url_for(\\n 'view_post',\\n year=post.pub_date.year,\\n month=post.pub_date.month,\\n day=post.pub_date.day,\\n slug=post.slug\\n ))\\n return flask.render_template('new.html', form=form)\",\n \"def add_comment() -> str:\\n if \\\"markdown\\\" in request.form:\\n if \\\"file\\\" in request.form:\\n comment = Comment(\\n markdown=request.form[\\\"markdown\\\"],\\n submission_id=Submission.query.filter(\\n Submission.filepath.contains(request.form[\\\"file\\\"])\\n )\\n .first()\\n .id,\\n cell_id=request.form[\\\"cell_id\\\"] if \\\"cell_id\\\" in request.form else None,\\n user=UserModel.get_by_token(session[\\\"token\\\"]),\\n )\\n # If not cell_id this is a general comment\\n comment.save()\\n else:\\n return \\\"Missing file or cell_id\\\", 400\\n else:\\n return \\\"Missing markdown\\\", 400\\n\\n comment_maker = get_template_attribute(\\\"_macros.html\\\", \\\"comment_block\\\")\\n return comment_maker(comment)\",\n \"def comment(postid):\\n context = {}\\n if \\\"username\\\" not in flask.session:\\n raise InvalidUsage('Forbidden', status_code=403)\\n\\n connection = insta485.model.get_db()\\n cursor = connection.execute(\\n \\\"SELECT * FROM comments WHERE postid=:id\\\", {'id': postid})\\n comments = cursor.fetchall()\\n ''' \\n if bool(comments) is False:\\n raise InvalidUsage('Not Found', status_code=404)\\n '''\\n # User\\n logname = flask.session[\\\"username\\\"]\\n\\n if flask.request.method == 'POST':\\n data = flask.request.get_json(force=True)\\n context['text'] = data['text']\\n context['owner'] = logname\\n context['owner_show_url'] = '/u/' + logname + '/'\\n connection.execute('INSERT INTO comments (owner, postid, text) \\\\\\n VALUES (?,?,?)', (logname, postid, data['text']))\\n cursor = connection.execute('SELECT last_insert_rowid() AS id')\\n commentid_dic = cursor.fetchone()\\n context['commentid'] = commentid_dic['id']\\n context['postid'] = postid\\n return flask.jsonify(**context), 201\\n\\n # url\\n context[\\\"url\\\"] = flask.request.path\\n context['comments'] = []\\n\\n for i in comments:\\n one_comment = {}\\n one_comment['commentid'] = i['commentid']\\n one_comment['owner'] = i['owner']\\n one_comment['owner_show_url'] = '/u/' + i['owner'] + '/'\\n one_comment['postid'] = postid\\n one_comment['text'] = i['text']\\n context['comments'].append(one_comment)\\n\\n return flask.jsonify(**context)\",\n \"def post(self, request):\\n\\n # crear el formulario con los datos del post\\n form = PostForm(request.POST)\\n\\n if form.is_valid():\\n #crea el post\\n post = form.save()\\n\\n #generar mensaje de exito\\n msg = \\\"Post creado con éxito\\\"\\n form = PostForm()\\n else:\\n msg = \\\"Ha ocurrido un error al guardar el post\\\" \\\\\\n\\n\\n # renderiza la plantilla con el formulario\\n context = {\\n \\\"form\\\": form,\\n \\\"msg\\\": msg\\n }\\n\\n # renderiza y devuelve la plantilla\\n return render(request, 'blogs/new-post.html', context)\",\n \"def post(self):\\n teacher = self.request.get(\\\"teacher\\\")\\n student = self.request.get(\\\"student\\\")\\n lessondate = self.request.get(\\\"lessondate\\\")\\n reason = self.request.get(\\\"reason\\\")\\n comment = self.request.get(\\\"comment\\\")\\n\\n if teacher and student and lessondate and reason:\\n\\n # create a new Post object and store it in the database !!!!!!!!!!!!!!!\\n loglesson = Teacher(\\n teacher=teacher,\\n student=student,\\n lessondate=lessondate,\\n reason = reason,\\n comment = comment)\\n loglesson.put()\\n\\n # get the id of the new post, so we can render the post's page (via the permalink)\\n id = loglesson.key().id()\\n self.redirect(\\\"/loglesson/%s\\\" % id)\\n else:\\n error = \\\"Please include a teacher, student, lesson date, reason and comment!\\\"\\n self.render_form(teacher, student, lessondate,reason, comment, error)\",\n \"def add_awcomment(request, pk):\\n\\n award = get_object_or_404(Award, pk=pk)\\n if request.method == \\\"POST\\\":\\n form = AwardCommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.author = request.user\\n comment.award = award\\n comment.save()\\n return redirect('../', pk=award.pk)\\n else:\\n form = AwardCommentForm()\\n return render(request, {'form': form})\",\n \"def post(self):\\n\\n title = self.request.get(\\\"title\\\")\\n blogPost = self.request.get(\\\"blogPost\\\")\\n author = self.request.cookies.get('name')\\n\\n if title and blogPost:\\n\\n bp = Blogposts(parent=blog_key(), title=title,\\n blogPost=blogPost, author=check_secure_val(author))\\n\\n bp.put()\\n\\n self.redirect('/%s' % str(bp.key.integer_id()))\\n else:\\n error = \\\"Please submit both a title and a blogpost!\\\"\\n self.render(\\\"newpost.html\\\", title=title,\\n blogPost=blogPost, error=error)\",\n \"def add_post():\\n\\tt_id = db.survey.insert(\\n\\t\\tquestion = request.vars.question,\\n\\t\\tuser_email = request.vars.email,\\n\\t\\tuser_name = get_user_name_from_email(request.vars.email),\\n\\t\\topt1 = request.vars.opt1,\\n\\t\\topt2 = request.vars.opt2,\\n\\t\\topt3 = request.vars.opt3,\\n\\t\\topt4 = request.vars.opt4,\\n\\t\\t#created_on_human = humanize.naturaltime(datetime.datetime.utcnow()),\\n\\n\\t)\\n\\tt = db.survey(t_id)\\n\\treturn response.json(dict(post=t))\",\n \"def submit_textarea():\\n\\n post_content = request.form[\\\"content\\\"]\\n author = request.form[\\\"author\\\"]\\n\\n post_object = {\\n 'author': author,\\n 'content': post_content\\n }\\n\\n # Submit a tx\\n new_tx_address = f\\\"{CONNECTED_NODE_ADDRESS}/new_transaction\\\"\\n\\n request.post(new_tx_address,\\n json=post_object, \\n headers={'Content-type': 'application/json'})\\n # return to homepage\\n return redirect('/')\",\n \"def _preview(request, context_processors, extra_context, form_class=ThreadedCommentForm):\\r\\n _adjust_max_comment_length(form_class)\\r\\n form = form_class(request.POST or None)\\r\\n context = {\\r\\n 'next' : _get_next(request),\\r\\n 'form' : form,\\r\\n }\\r\\n if form.is_valid():\\r\\n new_comment = form.save(commit=False)\\r\\n context['comment'] = new_comment\\r\\n else:\\r\\n context['comment'] = None\\r\\n return render_to_response(\\r\\n 'threadedcomments/preview_comment.html',\\r\\n extra_context, \\r\\n context_instance = RequestContext(request, context, context_processors)\\r\\n )\",\n \"def test_add_new_comment(self):\\n\\n result = self.client.post(\\\"/add_new_comment/2\\\",\\n data={\\\"user_id\\\": 25, \\\"park_id\\\": \\\"2\\\", \\\"content\\\": \\\"My dog loves this park!\\\"},\\n follow_redirects=True)\\n self.assertIn(\\\"<h1 class=\\\\\\\"title\\\\\\\">Bark Park!</h1>\\\", result.data)\",\n \"def new_answer(request):\\n if request.method == \\\"POST\\\":\\n author = request.POST.get(\\\"author\\\")\\n content = request.POST.get(\\\"content\\\")\\n date = datetime.datetime.now()\\n answer_tuple = {\\n \\\"author\\\": author,\\n \\\"content\\\": content,\\n \\\"votes\\\": 0,\\n \\\"topic_index\\\": request.matchdict[\\\"url\\\"],\\n \\\"answer_date\\\": date.strftime(\\\"%d/%m/%Y\\\"),\\n }\\n request.db[\\\"answer\\\"].insert(answer_tuple)\\n return HTTPFound(location=\\\"/topic/\\\" + request.matchdict[\\\"url\\\"])\\n return HTTPFound(location=\\\"/\\\")\",\n \"def post_comment(request, send_signal=True):\\n # Based on variables passed in we get the comment the user is attempting to create/edit\\n try:\\n comment, previous_version = get_comment(request)\\n except InvalidCommentException as e:\\n transaction.rollback()\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': str(e),\\n })\\n\\n # Check if the user doesn't pass the appropriate permission check (on the parent_object)...\\n # We call this on the parent comment because the comment itself may not have been saved yet (can't call .get_root on it)\\n # TODO: Fix this for root comment? (no parent)\\n parent_comment = comment.parent\\n tree_root = parent_comment.get_root()\\n parent_object = tree_root.content_object\\n if not user_can_post_comment(request, comment):\\n transaction.set_rollback(True)\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': \\\"You do not have permission to post this comment.\\\",\\n })\\n\\n # Check to make sure we are not trying to save a comment \\\"deeper\\\" than we are allowed...\\n if is_past_max_depth(comment):\\n transaction.set_rollback(True)\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': \\\"You cannot respond to this comment.\\\",\\n })\\n\\n # If the comment object (NOT the message) hasn't been saved yet...\\n if comment._state.adding == True:\\n comment = add_comment(comment)\\n\\n # Now that we have a comment object, we get a 'lock' on it to prevent a race condition\\n try:\\n lock_comment(comment)\\n except DatabaseError:\\n transaction.set_rollback(True)\\n # Someone is already trying to update this comment, so we need to return an appropriate error\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': \\\"Someone else is currently editing this comment. Please refresh your page and try again.\\\",\\n })\\n\\n # Now we know we have sole access to the comment object at the moment so we need to check if we are editing the most recent version\\n if not_most_recent_version(comment, previous_version):\\n transaction.set_rollback(True)\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': \\\"You are not editing the most recent version of this comment. Please refresh your page and try again.\\\",\\n })\\n\\n # Everything has checked out, so we save the new version and return the appropriate response\\n version_form, new_version = create_new_version(request, comment)\\n if version_form.is_valid():\\n comment_template, kwargs = get_template(request, comment, parent_object, tree_root, new_version, previous_version, send_signal=send_signal)\\n\\n return JsonResponse({\\n 'ok': True,\\n 'html_content': loader.render_to_string(comment_template, context=kwargs)\\n })\\n else:\\n transaction.set_rollback(True)\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': \\\"There were errors in your submission. Please correct them and resubmit.\\\",\\n })\",\n \"def post(self):\\n subject = self.request.get('subject')\\n content = self.request.get('content')\\n\\n # if user enter good subject and content, redirect them to new post page\\n if subject and content:\\n p = Post(parent = blog_key(), subject = subject, content = content)\\n p.put() # store the post element into database\\n self.redirect('/blog/%s' % str(p.key().id()))\\n # otherwise, render an error page \\n else:\\n error = \\\"subject and content, please!\\\"\\n self.render(\\\"newpost.html\\\", subject=subject, content=content, error=error)\",\n \"def _create_comment(request, course_key, thread_id=None, parent_id=None):\\r\\n assert isinstance(course_key, CourseKey)\\r\\n post = request.POST\\r\\n\\r\\n if 'body' not in post or not post['body'].strip():\\r\\n return JsonError(_(\\\"Body can't be empty\\\"))\\r\\n\\r\\n course = get_course_with_access(request.user, 'load', course_key)\\r\\n if course.allow_anonymous:\\r\\n anonymous = post.get('anonymous', 'false').lower() == 'true'\\r\\n else:\\r\\n anonymous = False\\r\\n\\r\\n if course.allow_anonymous_to_peers:\\r\\n anonymous_to_peers = post.get('anonymous_to_peers', 'false').lower() == 'true'\\r\\n else:\\r\\n anonymous_to_peers = False\\r\\n\\r\\n comment = cc.Comment(\\r\\n anonymous=anonymous,\\r\\n anonymous_to_peers=anonymous_to_peers,\\r\\n user_id=request.user.id,\\r\\n course_id=course_key.to_deprecated_string(),\\r\\n thread_id=thread_id,\\r\\n parent_id=parent_id,\\r\\n body=post[\\\"body\\\"]\\r\\n )\\r\\n comment.save()\\r\\n if post.get('auto_subscribe', 'false').lower() == 'true':\\r\\n user = cc.User.from_django_user(request.user)\\r\\n user.follow(comment.thread)\\r\\n if request.is_ajax():\\r\\n return ajax_content_response(request, course_key, comment.to_dict())\\r\\n else:\\r\\n return JsonResponse(utils.safe_content(comment.to_dict()))\",\n \"def post(self, req):\\n error_messages = []\\n success_message = ''\\n\\n # Creamos owner y se lo pasamos al form con un objeto pre-establecido\\n post_with_owner = Post()\\n post_with_owner.owner = req.user\\n post_with_owner.blog = Blog.objects.filter(owner=req.user)[0]\\n\\n form = PostCreateForm(req.POST, instance=post_with_owner)\\n if form.is_valid():\\n\\n new_post = form.save()\\n form = PostCreateForm()\\n success_message = u'Post guardado con éxito! '\\n success_message += u'<a href=\\\"{0}\\\">'.format(reverse('post_detail', args=[req.user.username, new_post.pk]))\\n success_message += u'(ver post)</a>'\\n else:\\n error_messages.append(u'Formulario incompleto.')\\n\\n context = {\\n 'form': form,\\n 'success_message': success_message\\n }\\n return render(req, 'posts/new_post.html', context)\",\n \"def post(request):\\n if request.method == \\\"POST\\\":\\n post = Post()\\n post.content = request.POST['content']\\n post.author = request.user\\n post.save()\\n return HttpResponseRedirect(reverse(\\\"index\\\"))\",\n \"def add_comment(request, pk, redirect_user):\\n\\n if request.is_ajax():\\n create_comment_and_status_notification(request, pk)\\n if redirect_user == 'profile':\\n return redirect('profile')\\n if redirect_user == 'news_feed':\\n return redirect('news_feed')\",\n \"def post(self):\\n title = self.request.get(\\\"title\\\")\\n body = self.request.get(\\\"body\\\")\\n\\n if title and body:\\n\\n # create a new Post object and store it in the database\\n post = Post(\\n title=title,\\n body=body\\n )\\n post.put()\\n\\n # get the id of the new post, so we can render the post's page (via the permalink)\\n id = post.key().id()\\n self.redirect(\\\"/blog/%s\\\" % id)\\n else:\\n error = \\\"we need both a title and a body!\\\"\\n #self.render_form(title, body, error)\\n self.render(\\\"newpost.html\\\", title, body, error)\",\n \"def post(self, request):\\n\\n # crear el formulario con los datos del POST\\n blog_with_user = Blog(owner=request.user)\\n form = BlogForm(request.POST, instance=blog_with_user)\\n\\n if form.is_valid():\\n #crea el post\\n blog = form.save()\\n\\n #generar mensaje de exito\\n msg = \\\"Blog creado con éxito\\\"\\n\\n # limpiamos el formulario creando uno vacío para pasar a la plantilla\\n form = BlogForm()\\n else:\\n msg = \\\"Ha ocurrido un error al guardar el blog\\\" \\\\\\n\\n\\n # renderiza la plantilla con el formulario\\n context = {\\n \\\"form\\\": form,\\n \\\"msg\\\": msg\\n }\\n\\n # renderiza y devuelve la plantilla\\n return render(request, 'blogs/new-blog.html', context)\",\n \"def post(self, request, slug):\\n article = ArticleInst.fetch(slug)\\n comment = request.data.get('comment', {})\\n\\n serializer = self.serializer_class(data=comment)\\n serializer.is_valid(raise_exception=True)\\n status_ = status.HTTP_201_CREATED\\n\\n try:\\n Comment.objects.get(\\n article=article,\\n body=comment.get('body')\\n )\\n except Comment.DoesNotExist:\\n serializer.save(author=request.user, article=article)\\n resp = {'message': 'Comment created'}\\n resp['data'] = serializer.data\\n\\n else:\\n resp = {'message': \\\"Seems you've posted an exact comment before\\\"}\\n status_ = status.HTTP_409_CONFLICT\\n return Response(data=resp,\\n status=status_\\n )\",\n \"def about(request):\\n data = {}\\n if request.method == \\\"POST\\\":\\n about = AboutForm(request.POST)\\n if about.is_valid():\\n about.save()\\n data['success']=1\\n data['message']='Comment successfully added'\\n return JsonResponse(data)\\n else:\\n data['success']=0\\n data['message']='Error while adding comment'\\n return JsonResponse(data)\\n \\n else:\\n about = AboutForm()\\n return render(request, 'login/addcomment.html',\\n {'form':about})\",\n \"def create():\\n if request.method == 'POST':\\n title = request.form['title']\\n body = request.form['body']\\n error = None\\n\\n if not title:\\n error = 'Title is required.'\\n\\n if error is not None:\\n flash(error)\\n else:\\n db = get_db()\\n db.execute(\\n 'INSERT INTO post (title, body, author_id)'\\n ' VALUES (?, ?, ?)',\\n (title, body, g.user['id'])\\n )\\n db.commit()\\n return redirect(url_for('blog.index'))\\n\\n return render_template('blog/create.html')\",\n \"def save_comment(self):\\n self.save()\",\n \"def annonceDetailView(request, pk):\\n details = Annonce.objects.get(pk=pk)\\n details.view_annonce += 1\\n details.save()\\n\\n # comment = Comment.objects.filter(\\n # for_post=details,\\n # reply=None).order_by('-create_content')\\n # is_favorite = False\\n # if details.favorite.filter(id=request.user.id).exists():\\n # is_favorite = True\\n # else:\\n # print('favorite is now False')\\n # if request.method == \\\"POST\\\":\\n # print(request.POST)\\n # c_form = commentForm(request.POST or None)\\n # if c_form.is_valid():\\n # content = request.POST.get('content')\\n # reply_id = request.POST.get('comment-id')\\n # comment_qs = None # reply is null\\n # if reply_id:\\n # comment_qs = Comment.objects.get(id=reply_id) \\n # comment_use = Comment(\\n # commented_by=request.user,\\n # for_post=details,\\n # content=content,\\n # reply=comment_qs\\n # )\\n # comment_use.save()\\n # else:\\n # c_form = commentForm()\\n # print(f'send {is_favorite}')\\n context = {\\n # 'is_favorite': is_favorite,\\n 'details': details,\\n \\n # 'comment': comment,\\n # 'commentform': c_form,\\n }\\n # if request.is_ajax():\\n # print('Ajax is true')\\n # html = render_to_string(\\n # 'annonce/comment.html',\\n # context, request=request\\n # )\\n # return JsonResponse({'form': html})\\n return render(request, 'Annonce/detail.html', context)\",\n \"def add_comment_to_announcement():\\n vars = request.vars\\n logger.info(\\\"vars.comment_text: %r\\\" % (vars.comment_text))\\n comment_id = db.Comments.insert(\\n comment_text = vars.comment_text,\\n score = 1,\\n ann_id= vars.ann_id,\\n )\\n comment = db.Announcements(comment_id)\\n\\n logger.info(\\\"api:add_comment_to_announcement ==> comment= %r\\\" % (comment))\\n\\n return response.json(comment)\",\n \"def snippet_new(request, template_name='dpaste/snippet_new.html'):\\n if request.method == \\\"POST\\\":\\n snippet_form = SnippetForm(data=request.POST, request=request)\\n if snippet_form.is_valid():\\n new_snippet = snippet_form.save()\\n url = new_snippet.get_absolute_url()\\n return HttpResponseRedirect(url)\\n else:\\n snippet_form = SnippetForm(request=request)\\n\\n template_context = {\\n 'snippet_form': snippet_form,\\n 'lexer_list': LEXER_LIST,\\n 'is_new': True,\\n }\\n\\n return render_to_response(\\n template_name,\\n template_context,\\n RequestContext(request)\\n )\",\n \"def render_POST(self, request):\",\n \"def get(self, request):\\n form = PostForm()\\n context = {\\n 'form': form,\\n 'success_message': ''\\n }\\n return render(request, 'posts/new-post.html', context)\",\n \"def create(thing):\\n fields = {}\\n errors = []\\n\\n for col in thing.cols:\\n new[col.field_name] = request.form.get(col.field_name)\\n if col.required and not new[col.field_name]:\\n errors.append('%s cannot be empty' % col.human_name)\\n\\n if errors:\\n for e in errors:\\n flash(e)\\n add_template_variable('thing', thing)\\n add_template_variable('fields', fields)\\n return my_render_template('generic/create_post.html')\\n\\n # insert into database\\n\\n db = get_db()\\n cursor = db.cursor()\\n\\n # create the two strings we use in the query\\n field_names = \\\"'\\\" + \\\"', '\\\".join(thing.field_names) + \\\"'\\\"\\n question_marks = \\\", \\\".join(map(lambda x: '?', thing.field_names.count() ))\\n\\n cursor.execute(\\\"insert into posts (%s) values (%s)\\\" % (field_names, question_marks), (title, body))\\n db.commit()\\n new_id = cursor.lastrowid\\n\\n # show new post to the user\\n flash(\\\"You made a new %s\\\" % thing.human_name)\\n return redirect(url_for('show_one', id_=new_id))\",\n \"def create_post():\\n\\n #Get prompt id\\n prompt_id = request.form.get('prompt_id')\\n\\n # Get post text\\n post_text = request.form.get('user_post')\\n\\n # Create post timestamp\\n created_at = datetime.now()\\n user_facing_date = created_at.strftime(\\\"%B %d, %Y\\\")\\n\\n # Save post and related data to database\\n post = crud.create_post(session['user_id'], prompt_id, post_text, session['lat'], session['lng'], session['user_facing_location'], created_at)\\n\\n return render_template('post_data.html', post=post, user_facing_date=user_facing_date)\",\n \"def ajax_form_valid(self, form):\\n\\n try:\\n comment = form.save(self.request)\\n num_comments = models.CommentModel.objects.permitted().count()\\n\\n return core_utils.respond_with_json({\\n 'success': True,\\n 'comment': render_to_string(\\n self.template_name,\\n RequestContext(self.request, {'comment': comment})\\n ),\\n 'num_comments': num_comments\\n })\\n except exceptions.RapidCommentingError as e:\\n return core_utils.respond_with_json({\\n 'success': False,\\n 'reason': e.value\\n })\",\n \"def newreply(request, post_id):\\n if not request.user.is_authenticated():\\n return redirect('/login/?next=%s' % request.path)\\n else:\\n\\n reply = Reply.objects.create(\\n creator = request.user,\\n created = datetime.datetime.now(),\\n body = request.POST.get('mensaje'),)\\n post = Post.objects.get(id = post_id)\\n post.reply.add(reply) \\n return redirect('/home/')\",\n \"def submit_comment(book_id):\\n \\n #Information for inserting\\n score = request.form.get(\\\"score\\\")\\n comment = request.form.get(\\\"comment\\\")\\n\\n if score is None or comment is None:\\n return render_template(\\\"error.html\\\",message=\\\"Please submit the complete information.\\\")\\n\\n #Inserte a new review\\n db.execute(\\\"INSERT INTO reviewer (id_book, id_user, comment, score_user) VALUES (:id_book, :id_user, :comment, :score_user)\\\",\\n {\\\"id_book\\\":book_id, \\\"id_user\\\":session[\\\"user_id\\\"], \\\"comment\\\": comment, \\\"score_user\\\": score})\\n \\n db.commit()\\n\\n #Get the info of the book\\n book = db.execute(\\\"SELECT * FROM book WHERE id = :book_id\\\",{\\\"book_id\\\": book_id}).fetchone()\\n if book is None:\\n return render_template(\\\"error.html\\\", message = \\\"No such Book.\\\")\\n\\n #Get the reviews joined with the name of the user\\n stmt = \\\"SELECT user_library.*, reviewer.* FROM user_library INNER JOIN reviewer ON user_library.id=reviewer.id_user WHERE id_book = :book_id\\\"\\n reviews = db.execute(stmt,{\\\"book_id\\\": book_id}).fetchall()\\n\\n #Get the user_review info\\n user_review = db.execute(\\\"SELECT * FROM reviewer WHERE id_book = :book_id AND id_user = :user_id\\\",\\n {\\\"book_id\\\": book_id, \\\"user_id\\\": session[\\\"user_id\\\"]}).fetchone()\\n\\n #If this info not exist we could add a comment, else we can not.\\n is_commented = True\\n if user_review is None:\\n is_commented = False\\n\\n #Insert a new score if a new comment is introduced\\n average_score = db.execute(\\\"SELECT AVG(score_user) FROM reviewer WHERE id_book = :book_id\\\",{\\\"book_id\\\":book_id}).fetchone()\\n average_score = average_score.items()\\n average_score = average_score[0]\\n average_score = float(average_score[1])\\n\\n db.execute(\\\"UPDATE book SET score = :average_score WHERE id = :book_id\\\", {\\\"average_score\\\":average_score, \\\"book_id\\\": book_id}) \\n db.commit()\\n\\n #Get the info of the book\\n book = db.execute(\\\"SELECT * FROM book WHERE id = :book_id\\\",{\\\"book_id\\\": book_id}).fetchone()\\n if book is None:\\n return render_template(\\\"error.html\\\", message = \\\"No such Book.\\\")\\n\\n #Proccess for rating count of Goofreaders\\n goodreader_info = requests.get(\\\"https://www.goodreads.com/book/review_counts.json\\\", params={\\\"key\\\": KEY, \\\"isbns\\\": book.isbn })\\n goodreader_info = goodreader_info.json()\\n goodreader_info = goodreader_info[\\\"books\\\"]\\n\\n average_rating = goodreader_info[0][\\\"average_rating\\\"]\\n ratings_counts = goodreader_info[0][\\\"ratings_count\\\"]\\n\\n return render_template(\\\"book_info.html\\\",book=book, reviews = reviews, is_commented = is_commented\\n , average_rating = average_rating, ratings_counts = ratings_counts )\",\n \"def _add_comment():\\r\\n per_page = current_app.config['FLASKY_ANSWERS_PER_PAGE']\\r\\n id = request.args.get('answer_id')\\r\\n answer = Answer.query.get_or_404(id)\\r\\n comment =request.args.get('comment')\\r\\n answers = Answer.query.get_or_404(id)\\r\\n page = 1\\r\\n result= False\\r\\n if current_user.can(Permission.COMMENT):\\r\\n comment = Comment(body=comment,\\r\\n author=current_user._get_current_object(),\\r\\n answer_id=id)\\r\\n db.session.add(comment)\\r\\n db.session.commit()\\r\\n page = (answer.comments.count()-1)/per_page + 1\\r\\n result=True\\r\\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\\r\\n page,per_page=per_page,error_out=False\\r\\n )\\r\\n macro_comment = get_template_attribute(\\\"_comments.html\\\", \\\"render_comments\\\")\\r\\n macro_page = get_template_attribute(\\\"_page.html\\\", \\\"render_page\\\")\\r\\n comments = pagination.items\\r\\n return jsonify({'result': result,\\r\\n 'comment_html': macro_comment(comments),\\r\\n 'page_html': macro_page(pagination),\\r\\n 'comments_timestamp': [comment.timestamp for comment in comments],\\r\\n 'comments_id': [comment.id for comment in comments]\\r\\n })\",\n \"def create_post(request):\\n if request.method == 'POST':\\n title = request.POST['title']\\n content = request.POST['content']\\n user_id = request.POST['author_id']\\n category = request.POST['category']\\n\\n slug = \\\"-\\\".join(list(map(lambda word: word.lower(), title.split())))\\n author = User.objects.get(id=int(user_id))\\n\\n # save info in models\\n post = Post()\\n post.author = author\\n post.category = category\\n post.title = title\\n post.content = content\\n post.slug = slug\\n post.save()\\n return redirect('post')\\n\\n return render(request, 'posts/create_post.html')\",\n \"def handle_comments(self):\\r\\n comments = Comment.objects.all()\\r\\n for c in comments:\\r\\n new = ThreadedComment(\\r\\n content_type = c.content_type,\\r\\n object_id = c.object_id,\\r\\n comment = c.comment,\\r\\n user = c.user,\\r\\n date_submitted = c.submit_date,\\r\\n date_modified = c.submit_date,\\r\\n date_approved = c.submit_date,\\r\\n is_public = c.is_public,\\r\\n ip_address = c.ip_address,\\r\\n is_approved = not c.is_removed\\r\\n )\\r\\n new.save()\",\n \"def add():\\n if request.method == 'GET':\\n return render_template('add.html')\\n elif request.method == 'POST':\\n data = {}\\n for key in ('h', 'name', 'summary', 'content', 'published', 'updated', 'category',\\n 'slug', 'location', 'in-reply-to', 'repost-of', 'syndication'):\\n data[key] = None\\n\\n for title in request.form:\\n data[title] = request.form[title]\\n\\n for title in request.files:\\n data[title] = request.files[title].read()\\n\\n try:\\n photo = request.files['photo']\\n except:\\n photo = None\\n\\n for key in data:\\n if data[key] == \\\"\\\":\\n data[key] = None\\n\\n data['published'] = datetime.now()\\n\\n location = create_entry(data, image=data['photo'], g=g)\\n\\n if data['in-reply-to']:\\n send_mention('http://' + DOMAIN_NAME + '/e/'+location, data['in-reply-to'])\\n\\n if request.form.get('twitter'):\\n t = Timer(30, bridgy_twitter, [location])\\n t.start()\\n\\n if request.form.get('facebook'):\\n t = Timer(30, bridgy_facebook, [location])\\n t.start()\\n return redirect(location)\\n else:\\n return redirect('/404'), 404\",\n \"def post(self, request):\\n pass\",\n \"def free_comment(request, content_type=None, object_id=None, edit_id=None, parent_id=None, add_messages=False, ajax=False, model=FreeThreadedComment, form_class=FreeThreadedCommentForm, context_processors=[], extra_context={}):\\r\\n if not edit_id and not (content_type and object_id):\\r\\n raise Http404 # Must specify either content_type and object_id or edit_id\\r\\n if \\\"preview\\\" in request.POST:\\r\\n return _preview(request, context_processors, extra_context, form_class=form_class)\\r\\n if edit_id:\\r\\n instance = get_object_or_404(model, id=edit_id)\\r\\n else:\\r\\n instance = None\\r\\n _adjust_max_comment_length(form_class)\\r\\n form = form_class(request.POST, instance=instance)\\r\\n if form.is_valid():\\r\\n new_comment = form.save(commit=False)\\r\\n if not edit_id:\\r\\n new_comment.ip_address = request.META.get('REMOTE_ADDR', None)\\r\\n new_comment.content_type = get_object_or_404(ContentType, id = int(content_type))\\r\\n new_comment.object_id = int(object_id)\\r\\n if model == ThreadedComment:\\r\\n new_comment.user = request.user\\r\\n if parent_id:\\r\\n new_comment.parent = get_object_or_404(model, id = int(parent_id))\\r\\n new_comment.save()\\r\\n if model == ThreadedComment:\\r\\n if add_messages:\\r\\n request.user.message_set.create(message=\\\"Your message has been posted successfully.\\\")\\r\\n else:\\r\\n request.session['successful_data'] = {\\r\\n 'name' : form.cleaned_data['name'],\\r\\n 'website' : form.cleaned_data['website'],\\r\\n 'email' : form.cleaned_data['email'],\\r\\n }\\r\\n if ajax == 'json':\\r\\n return JSONResponse([new_comment,])\\r\\n elif ajax == 'xml':\\r\\n return XMLResponse([new_comment,])\\r\\n else:\\r\\n return HttpResponseRedirect(_get_next(request))\\r\\n elif ajax==\\\"json\\\":\\r\\n return JSONResponse({'errors' : form.errors}, is_iterable=False)\\r\\n elif ajax==\\\"xml\\\":\\r\\n template_str = \\\"\\\"\\\"\\r\\n<errorlist>\\r\\n {% for error,name in errors %}\\r\\n <field name=\\\"{{ name }}\\\">\\r\\n {% for suberror in error %}<error>{{ suberror }}</error>{% endfor %}\\r\\n </field>\\r\\n {% endfor %}\\r\\n</errorlist>\\r\\n \\\"\\\"\\\"\\r\\n response_str = Template(template_str).render(Context({'errors' : zip(form.errors.values(), form.errors.keys())}))\\r\\n return XMLResponse(response_str, is_iterable=False)\\r\\n else:\\r\\n return _preview(request, context_processors, extra_context, form_class=form_class)\",\n \"def editor_save():\\n markdown = request.form.get('markdown')\\n html = request.form.get('html')\\n title = request.form.get('title')\\n if 'post_id' in request.form:\\n post_id = int(request.form.get('post_id'))\\n edit_post = Post.query.get(post_id)\\n edit_post.markdown = markdown\\n edit_post.html = html\\n edit_post.title = title\\n db.session.add(edit_post)\\n db.session.commit()\\n return jsonify(saved_success=True, new_post=None, post_id=None)\\n else:\\n new_post = Post(markdown=markdown, html=html, title=title);\\n db.session.add(new_post)\\n db.session.commit()\\n return jsonify(saved_success=True, new_post=True, post_id=new_post.id)\",\n \"def render_form(self, title=\\\"\\\", body=\\\"\\\", error=\\\"\\\"):\\n self.render(\\\"newpost.html\\\", title=title, body=body, error=error)\",\n \"def add_feedback(username):\\n form = addFeedback()\\n\\n if \\\"user\\\" not in session: \\n flash(\\\"Not logged in\\\")\\n return redirect('/login')\\n \\n elif form.validate_on_submit():\\n title = form.title.data\\n content = form.content.data\\n recipient = username\\n user = session[\\\"user\\\"]\\n\\n new_feedback = Feedback(title=title, content=content, recipient=recipient, user=user)\\n db.session.add(new_feedback)\\n db.session.commit()\\n\\n flash(\\\"Added feedback\\\")\\n return redirect(f'/users/{username}')\\n else:\\n return render_template(\\\"feedback_form.html\\\", form=form, username=username)\",\n \"def create_post(request):\\n\\n # modified from: http://django-angular.readthedocs.org/en/latest/angular-model-form.html\\n\\n # get data\\n in_data = getRequestData(request)\\n\\n try:\\n # save in database\\n # note that in_data.mytitle throws an error while in_data.get('mytitle') works smoothly\\n post = Thread(pub_date = datetime.datetime.now(pytz.timezone('US/Eastern')), username = in_data.get('myusername'), title = in_data.get('mytitle'), description = in_data.get('mydescription'))\\n post.save()\\n except:\\n return HttpResponseBadRequest('Error saving to database!')\\n\\n return JsonResponse(in_data)\",\n \"def _comment():\\r\\n id = request.args.get('answer_id')\\r\\n per_page=current_app.config['FLASKY_ANSWERS_PER_PAGE']\\r\\n answer = Answer.query.get_or_404(id)\\r\\n page = request.args.get('page', type=int, default=1)\\r\\n comment =request.args.get('comment')\\r\\n if current_user.can(Permission.COMMENT) and comment is not None:\\r\\n comment = Comment(body=comment,\\r\\n author=current_user._get_current_object(),\\r\\n answer_id=id)\\r\\n db.session.add(comment)\\r\\n db.session.commit()\\r\\n page = -1\\r\\n if page == -1:\\r\\n page = answer.comments.count() / per_page\\r\\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\\r\\n page,per_page=per_page,error_out=False\\r\\n )\\r\\n macro_comment = get_template_attribute(\\\"_comments.html\\\", \\\"render_comments\\\")\\r\\n macro_page = get_template_attribute(\\\"_page.html\\\", \\\"render_page\\\")\\r\\n comments = pagination.items\\r\\n return jsonify({'result': True,\\r\\n 'comment_html': macro_comment(comments),\\r\\n 'page_html':macro_page(pagination),\\r\\n 'comments_timestamp':[comment.timestamp for comment in comments],\\r\\n 'comments_id':[comment.id for comment in comments]\\r\\n })\",\n \"def test_editing_post_comment(self):\\n\\n form_data = {\\\"comment\\\": \\\"Here's my new comment!\\\"}\\n new_comment = edit_post_comment(1, form_data)\\n\\n self.assertIn(\\\"my new comment\\\", new_comment.comment_body)\",\n \"def feature_comment(request, id=id):\\n feature = get_object_or_404(Feature, id=id)\\n comment_form = FeatureCommentForm(request.POST, request.FILES)\\n if comment_form.is_valid():\\n comment = comment_form.save(commit=False)\\n comment.user = request.user\\n comment.feature = feature\\n comment_form.save()\\n return redirect(feature_detail, id)\",\n \"def add_comment(request):\\n \\n \\\"\\\"\\\"\\n device type\\n \\\"\\\"\\\"\\n is_Mobile = dmb.process_request(request)\\n \\n \\\"\\\"\\\"\\n User validation \\n \\\"\\\"\\\"\\n \\n \\n if request.user.is_anonymous():\\n return comm.redirect_login_path(is_Mobile, request)\\n result = dayword_comment(request, 1) \\n return HttpResponse(json.dumps(result), content_type='application/json')\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7209647","0.7182928","0.70809394","0.70615923","0.7031212","0.70248646","0.70202553","0.6970048","0.6925778","0.69036263","0.68516064","0.68059367","0.6770113","0.6715247","0.6710386","0.67016625","0.6607484","0.66067475","0.6575949","0.65087175","0.6499307","0.6476845","0.64617276","0.637791","0.6375545","0.6353876","0.6315487","0.6289599","0.62716705","0.6266605","0.62648076","0.6261812","0.6259241","0.62570554","0.625627","0.6253319","0.6239593","0.6234117","0.62293494","0.6222089","0.62117875","0.6206138","0.6204796","0.6200007","0.61994505","0.61745656","0.61737365","0.6167005","0.61664474","0.61655486","0.61279416","0.612402","0.61196035","0.61087453","0.6105337","0.6104828","0.6095142","0.6086812","0.6054424","0.60527503","0.6052165","0.6046809","0.6039737","0.603921","0.60349","0.60330176","0.6030738","0.6029808","0.6022376","0.60217243","0.6020527","0.60122335","0.599389","0.5989844","0.5988574","0.59855855","0.5981686","0.5971458","0.596457","0.59589964","0.59544003","0.59532696","0.5935298","0.5935246","0.59105366","0.59048736","0.590446","0.5897863","0.5897683","0.5886206","0.5885844","0.5881842","0.5878892","0.5854371","0.5851145","0.58455896","0.58395094","0.582897","0.5825102","0.58209664"],"string":"[\n \"0.7209647\",\n \"0.7182928\",\n \"0.70809394\",\n \"0.70615923\",\n \"0.7031212\",\n \"0.70248646\",\n \"0.70202553\",\n \"0.6970048\",\n \"0.6925778\",\n \"0.69036263\",\n \"0.68516064\",\n \"0.68059367\",\n \"0.6770113\",\n \"0.6715247\",\n \"0.6710386\",\n \"0.67016625\",\n \"0.6607484\",\n \"0.66067475\",\n \"0.6575949\",\n \"0.65087175\",\n \"0.6499307\",\n \"0.6476845\",\n \"0.64617276\",\n \"0.637791\",\n \"0.6375545\",\n \"0.6353876\",\n \"0.6315487\",\n \"0.6289599\",\n \"0.62716705\",\n \"0.6266605\",\n \"0.62648076\",\n \"0.6261812\",\n \"0.6259241\",\n \"0.62570554\",\n \"0.625627\",\n \"0.6253319\",\n \"0.6239593\",\n \"0.6234117\",\n \"0.62293494\",\n \"0.6222089\",\n \"0.62117875\",\n \"0.6206138\",\n \"0.6204796\",\n \"0.6200007\",\n \"0.61994505\",\n \"0.61745656\",\n \"0.61737365\",\n \"0.6167005\",\n \"0.61664474\",\n \"0.61655486\",\n \"0.61279416\",\n \"0.612402\",\n \"0.61196035\",\n \"0.61087453\",\n \"0.6105337\",\n \"0.6104828\",\n \"0.6095142\",\n \"0.6086812\",\n \"0.6054424\",\n \"0.60527503\",\n \"0.6052165\",\n \"0.6046809\",\n \"0.6039737\",\n \"0.603921\",\n \"0.60349\",\n \"0.60330176\",\n \"0.6030738\",\n \"0.6029808\",\n \"0.6022376\",\n \"0.60217243\",\n \"0.6020527\",\n \"0.60122335\",\n \"0.599389\",\n \"0.5989844\",\n \"0.5988574\",\n \"0.59855855\",\n \"0.5981686\",\n \"0.5971458\",\n \"0.596457\",\n \"0.59589964\",\n \"0.59544003\",\n \"0.59532696\",\n \"0.5935298\",\n \"0.5935246\",\n \"0.59105366\",\n \"0.59048736\",\n \"0.590446\",\n \"0.5897863\",\n \"0.5897683\",\n \"0.5886206\",\n \"0.5885844\",\n \"0.5881842\",\n \"0.5878892\",\n \"0.5854371\",\n \"0.5851145\",\n \"0.58455896\",\n \"0.58395094\",\n \"0.582897\",\n \"0.5825102\",\n \"0.58209664\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.70013684"},"document_rank":{"kind":"string","value":"7"}}},{"rowIdx":1394,"cells":{"query":{"kind":"string","value":"View function that handles inserting new/editing previously existing comments via Ajax"},"document":{"kind":"string","value":"def post_comment(request, send_signal=True):\n # Based on variables passed in we get the comment the user is attempting to create/edit\n try:\n comment, previous_version = get_comment(request)\n except InvalidCommentException as e:\n transaction.rollback()\n return JsonResponse({\n 'ok': False,\n 'error_message': str(e),\n })\n\n # Check if the user doesn't pass the appropriate permission check (on the parent_object)...\n # We call this on the parent comment because the comment itself may not have been saved yet (can't call .get_root on it)\n # TODO: Fix this for root comment? (no parent)\n parent_comment = comment.parent\n tree_root = parent_comment.get_root()\n parent_object = tree_root.content_object\n if not user_can_post_comment(request, comment):\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You do not have permission to post this comment.\",\n })\n\n # Check to make sure we are not trying to save a comment \"deeper\" than we are allowed...\n if is_past_max_depth(comment):\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You cannot respond to this comment.\",\n })\n\n # If the comment object (NOT the message) hasn't been saved yet...\n if comment._state.adding == True:\n comment = add_comment(comment)\n\n # Now that we have a comment object, we get a 'lock' on it to prevent a race condition\n try:\n lock_comment(comment)\n except DatabaseError:\n transaction.set_rollback(True)\n # Someone is already trying to update this comment, so we need to return an appropriate error\n return JsonResponse({\n 'ok': False,\n 'error_message': \"Someone else is currently editing this comment. Please refresh your page and try again.\",\n })\n\n # Now we know we have sole access to the comment object at the moment so we need to check if we are editing the most recent version\n if not_most_recent_version(comment, previous_version):\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You are not editing the most recent version of this comment. Please refresh your page and try again.\",\n })\n\n # Everything has checked out, so we save the new version and return the appropriate response\n version_form, new_version = create_new_version(request, comment)\n if version_form.is_valid():\n comment_template, kwargs = get_template(request, comment, parent_object, tree_root, new_version, previous_version, send_signal=send_signal)\n\n return JsonResponse({\n 'ok': True,\n 'html_content': loader.render_to_string(comment_template, context=kwargs)\n })\n else:\n transaction.set_rollback(True)\n return JsonResponse({\n 'ok': False,\n 'error_message': \"There were errors in your submission. Please correct them and resubmit.\",\n })"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def save_comments():\n potential_deal_id = int(request.form.get(\"id\"))\n action = request.form.get(\"action\")\n if action.lower() == \"none\":\n action = None\n comments = request.form.get(\"comments\")\n db_handler = DBHandler()\n db_handler.update_by_id(potential_deal_id, action, comments)\n # return redirect(url_for(\"home\"))\n return jsonify({\"success\": True}), 200","def on_comment(self, request, board_id):\n error = None\n if request.method == 'POST':\n creator = request.form['creator']\n comment = request.form['comment']\n if len(creator) > 30:\n error = 'creator name too long'\n elif len(comment) > 50:\n error = 'comment too long'\n else:\n self.insert_comment(request, board_id)\n return redirect('/board:' + board_id)\n return self.render_template('comment.html', error=error)","def comments_new():\n comment = {\n \"title\": request.form.get(\"title\"),\n \"content\": request.form.get(\"content\"),\n \"playlist_id\": ObjectId(request.form.get(\"playlist._id\")),\n }\n print(comment)\n comment_id = db.comments.insert_one(comment).inserted_id\n return redirect(\n url_for(\"playlists.playlists_show\", playlist_id=request.form.get(\"playlist._id\"))\n )","def add_comment(request):\n if request.method != 'POST':\n return HttpResponseRedirect(reverse('wainz.views.composite'))\n else:\n img_id = request.POST['id']\n try:\n img = Image.objects.get(pk=img_id)\n except:\n return HttpResponseRedirect(reverse('wainz.views.composite'))\n comment_text = request.POST['comment']\n #TODO sanitize input\n comment = ImageComment()\n comment.submission_date = timezone.now()\n comment.comment_text= comment_text\n comment.image_id = img_id\n comment.submitter_id = int(request.POST['uid'])\n comment.save()\n return rest.rest_success(request, img_id)","def add_comment(request, model, object_id):\n obj = get_object_or_404(model, id=object_id)\n if request.method == \"POST\":\n form = CommentForm(request.POST)\n if form.is_valid():\n Comment.objects.create(\n content_type = ContentType.objects.get_for_model(model),\n object_id = object_id,\n author = request.user,\n added_at = datetime.datetime.now(),\n comment = form.cleaned_data['comment']\n )\n if request.is_ajax():\n return JsonResponse({'success': True})\n else:\n return HttpResponseRedirect(obj.get_absolute_url())\n elif request.is_ajax():\n return JsonResponse({'success': False, 'errors': form.errors})\n else:\n form = CommentForm()\n\n # Let the appropriate fallback view take care of display/redisplay\n if model is Question:\n return question_comments(request, obj, form=form)\n elif model is Answer:\n return answer_comments(request, object_id, answer=obj, form=form)","def annonceDetailView(request, pk):\n details = Annonce.objects.get(pk=pk)\n details.view_annonce += 1\n details.save()\n\n # comment = Comment.objects.filter(\n # for_post=details,\n # reply=None).order_by('-create_content')\n # is_favorite = False\n # if details.favorite.filter(id=request.user.id).exists():\n # is_favorite = True\n # else:\n # print('favorite is now False')\n # if request.method == \"POST\":\n # print(request.POST)\n # c_form = commentForm(request.POST or None)\n # if c_form.is_valid():\n # content = request.POST.get('content')\n # reply_id = request.POST.get('comment-id')\n # comment_qs = None # reply is null\n # if reply_id:\n # comment_qs = Comment.objects.get(id=reply_id) \n # comment_use = Comment(\n # commented_by=request.user,\n # for_post=details,\n # content=content,\n # reply=comment_qs\n # )\n # comment_use.save()\n # else:\n # c_form = commentForm()\n # print(f'send {is_favorite}')\n context = {\n # 'is_favorite': is_favorite,\n 'details': details,\n \n # 'comment': comment,\n # 'commentform': c_form,\n }\n # if request.is_ajax():\n # print('Ajax is true')\n # html = render_to_string(\n # 'annonce/comment.html',\n # context, request=request\n # )\n # return JsonResponse({'form': html})\n return render(request, 'Annonce/detail.html', context)","def post_comment_ajax(request, using=None):\n if not request.is_ajax():\n return HttpResponseBadRequest(\"Expecting Ajax call\")\n\n data = request.POST.copy()\n if request.user.is_authenticated():\n if not data.get('name', ''):\n data[\"name\"] = request.user.get_full_name() or request.user.get_username()\n if not data.get('email', ''):\n data[\"email\"] = request.user.email\n\n # Look up the object we're trying to comment about\n ctype = data.get(\"content_type\")\n object_pk = data.get(\"object_pk\")\n if ctype is None or object_pk is None:\n return CommentPostBadRequest(\"Missing content_type or object_pk field.\")\n try:\n model = apps.get_model(*ctype.split(\".\", 1))\n target = model._default_manager.using(using).get(pk=object_pk)\n except TypeError:\n return CommentPostBadRequest(\n \"Invalid content_type value: %r\" % escape(ctype))\n except AttributeError:\n return CommentPostBadRequest(\n \"The given content-type %r does not resolve to a valid model.\" % escape(ctype))\n except ObjectDoesNotExist:\n return CommentPostBadRequest(\n \"No object matching content-type %r and object PK %r exists.\" % (\n escape(ctype), escape(object_pk)))\n except (ValueError, ValidationError) as e:\n return CommentPostBadRequest(\n \"Attempting go get content-type %r and object PK %r exists raised %s\" % (\n escape(ctype), escape(object_pk), e.__class__.__name__))\n\n # Do we want to preview the comment?\n preview = \"preview\" in data\n\n # Construct the comment form\n form = django_comments.get_form()(target, data=data)\n\n # Check security information\n if form.security_errors():\n return CommentPostBadRequest(\n \"The comment form failed security verification: %s\" % escape(str(form.security_errors())))\n\n # If there are errors or if we requested a preview show the comment\n if preview:\n comment = form.get_comment_object() if not form.errors else None\n if comment is not None and request.user.is_authenticated():\n comment.user = request.user\n return _ajax_result(request, form, \"preview\", comment, object_id=object_pk)\n if form.errors:\n return _ajax_result(request, form, \"post\", object_id=object_pk)\n\n # Otherwise create the comment\n comment = form.get_comment_object()\n comment.ip_address = get_trusted_ip(request)\n if request.user.is_authenticated():\n comment.user = request.user\n\n # Signal that the comment is about to be saved\n responses = signals.comment_will_be_posted.send(\n sender=comment.__class__,\n comment=comment,\n request=request\n )\n\n for (receiver, response) in responses:\n if response is False:\n return CommentPostBadRequest(\n \"comment_will_be_posted receiver %r killed the comment\" % receiver.__name__)\n\n # Save the comment and signal that it was saved\n comment.save()\n signals.comment_was_posted.send(\n sender=comment.__class__,\n comment=comment,\n request=request\n )\n\n return _ajax_result(request, form, \"post\", comment, object_id=object_pk)","def add_comment(request, pk, redirect_user):\n\n if request.is_ajax():\n create_comment_and_status_notification(request, pk)\n if redirect_user == 'profile':\n return redirect('profile')\n if redirect_user == 'news_feed':\n return redirect('news_feed')","def _comment():\r\n id = request.args.get('answer_id')\r\n per_page=current_app.config['FLASKY_ANSWERS_PER_PAGE']\r\n answer = Answer.query.get_or_404(id)\r\n page = request.args.get('page', type=int, default=1)\r\n comment =request.args.get('comment')\r\n if current_user.can(Permission.COMMENT) and comment is not None:\r\n comment = Comment(body=comment,\r\n author=current_user._get_current_object(),\r\n answer_id=id)\r\n db.session.add(comment)\r\n db.session.commit()\r\n page = -1\r\n if page == -1:\r\n page = answer.comments.count() / per_page\r\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\r\n page,per_page=per_page,error_out=False\r\n )\r\n macro_comment = get_template_attribute(\"_comments.html\", \"render_comments\")\r\n macro_page = get_template_attribute(\"_page.html\", \"render_page\")\r\n comments = pagination.items\r\n return jsonify({'result': True,\r\n 'comment_html': macro_comment(comments),\r\n 'page_html':macro_page(pagination),\r\n 'comments_timestamp':[comment.timestamp for comment in comments],\r\n 'comments_id':[comment.id for comment in comments]\r\n })","def _add_comment():\r\n per_page = current_app.config['FLASKY_ANSWERS_PER_PAGE']\r\n id = request.args.get('answer_id')\r\n answer = Answer.query.get_or_404(id)\r\n comment =request.args.get('comment')\r\n answers = Answer.query.get_or_404(id)\r\n page = 1\r\n result= False\r\n if current_user.can(Permission.COMMENT):\r\n comment = Comment(body=comment,\r\n author=current_user._get_current_object(),\r\n answer_id=id)\r\n db.session.add(comment)\r\n db.session.commit()\r\n page = (answer.comments.count()-1)/per_page + 1\r\n result=True\r\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\r\n page,per_page=per_page,error_out=False\r\n )\r\n macro_comment = get_template_attribute(\"_comments.html\", \"render_comments\")\r\n macro_page = get_template_attribute(\"_page.html\", \"render_page\")\r\n comments = pagination.items\r\n return jsonify({'result': result,\r\n 'comment_html': macro_comment(comments),\r\n 'page_html': macro_page(pagination),\r\n 'comments_timestamp': [comment.timestamp for comment in comments],\r\n 'comments_id': [comment.id for comment in comments]\r\n })","def comment_add(request,comment=None, error='', message=''):\n categories = Category.objects.all()\n error_fields=[]\n default_comment = Comment(date=datetime.date.today(), time=datetime.datetime.now().time, source='', detail='', category=Category.objects.filter(description='Events')[0], user_email='')\n\n try:\n added = bool(request.POST['add'])\n except:\n added = False\n try:\n action = request.POST['action']\n except:\n action = 'add'\n\n if added == True:\n try:\n new_date = parse(request.POST['date'], dayfirst=True)\n new_time = parse(request.POST['time'])\n except:\n error += ' Datetime invalid or not specified.'\n\n try:\n new_detail = request.POST['detail']\n if new_detail == '':\n error += ' Comment text is blank.'\n except:\n error += ' No comment text provided.'\n\n try:\n new_source = request.POST['source']\n if new_source == '':\n error += ' Source is blank.'\n except:\n error += ' No comment source provided.'\n\n try:\n new_category = Category.objects.filter(pk=int(request.POST['category_id']))[0] #The [0] is OK since the fact that category_id is a primary key ensures that the array has only length 1.\n except:\n error += ' Category invalid or nonexistent.'\n\n try:\n new_user_email = request.POST['user_email']\n if new_user_email == '':\n error += ' You haven\\'t provided your e-mail address.'\n except:\n error += ' No user e-mail address provided.'\n\n if error == '':\n try:\n new_comment = Comment(date=new_date, time=new_time, source=new_source, detail=new_detail, category=new_category, user_email=new_user_email)\n new_comment.full_clean()\n try:\n new_comment.save()\n message += 'Your comment was added to the database.'\n except:\n error += 'Failed to access the database.'\n except ValidationError as ve:\n for k in ve.message_dict.keys():\n error_fields.append(k)\n for m in ve.message_dict[k]:\n error += m + ' '\n default_comment = new_comment\n\n if action == 'saveandaddanother' or action == 'add' or error != '':\n return render_to_response('feedback/comment_add.html',\n {'categories': categories,\n 'error': error,\n 'error_fields': error_fields,\n 'message': message,\n 'added': added,\n 'comment': default_comment},\n context_instance=RequestContext(request))\n elif action == 'save':\n return index(request, error=error, message=message)\n else:\n error += 'Invalid submit action requested.'\n return render_to_response('feedback/comment_add.html',\n {'categories': categories,\n 'error': error,\n 'error_fields': error_fields,\n 'added': added,\n 'message': message,\n 'comment': default_comment},\n context_instance=RequestContext(request))","def add_comment(request, pk, pk2):\n template_var = base_template_vals(request)\n p = request.POST\n \n if p.has_key(\"content\") and p[\"content\"]:\n if request.user.is_authenticated():\n comment = Comment(event=Event.objects.get(id=pk))\n comment.user = UserProfile.objects.get(django_user=request.user)\n comment.content = p[\"content\"]\n comment.save()\n\n # Sys notification\n from_user = UserProfile.objects.get(django_user=pk2) # Who's event that is commented on\n to_user = Event.objects.get(id=pk).author\n event_id = pk\n sys_notification(to_user, \"add_comment\", from_user, event_id)\n return single(request, pk)","def newcomment(id):\n\n if g.is_logged == False:\n flash (\"You need to be logged in\")\n return redirect(url_for('show_place', id=id))\n\n if request.method == 'POST':\n rating = request.form['rating']\n\n if rating.isdigit() == False:\n flash (\"Rating must be between a number between 0 and 5 (inclusive)\")\n elif int(rating) < 0 or int(rating) > 5:\n flash (\"Rating must be between 0 and 5 (inclusive)\")\n else:\n db = get_db()\n db.execute('''insert into reviews (rating, title, message, user_id, place_id) values (?, ?, ?,?,?)''', [rating, request.form['title'], request.form['content'], g.user_id, id])\n db.commit()\n\n flash('Your comment was successfully added')\n return redirect(url_for('show_place', id=id))","def free_comment(request, content_type=None, object_id=None, edit_id=None, parent_id=None, add_messages=False, ajax=False, model=FreeThreadedComment, form_class=FreeThreadedCommentForm, context_processors=[], extra_context={}):\r\n if not edit_id and not (content_type and object_id):\r\n raise Http404 # Must specify either content_type and object_id or edit_id\r\n if \"preview\" in request.POST:\r\n return _preview(request, context_processors, extra_context, form_class=form_class)\r\n if edit_id:\r\n instance = get_object_or_404(model, id=edit_id)\r\n else:\r\n instance = None\r\n _adjust_max_comment_length(form_class)\r\n form = form_class(request.POST, instance=instance)\r\n if form.is_valid():\r\n new_comment = form.save(commit=False)\r\n if not edit_id:\r\n new_comment.ip_address = request.META.get('REMOTE_ADDR', None)\r\n new_comment.content_type = get_object_or_404(ContentType, id = int(content_type))\r\n new_comment.object_id = int(object_id)\r\n if model == ThreadedComment:\r\n new_comment.user = request.user\r\n if parent_id:\r\n new_comment.parent = get_object_or_404(model, id = int(parent_id))\r\n new_comment.save()\r\n if model == ThreadedComment:\r\n if add_messages:\r\n request.user.message_set.create(message=\"Your message has been posted successfully.\")\r\n else:\r\n request.session['successful_data'] = {\r\n 'name' : form.cleaned_data['name'],\r\n 'website' : form.cleaned_data['website'],\r\n 'email' : form.cleaned_data['email'],\r\n }\r\n if ajax == 'json':\r\n return JSONResponse([new_comment,])\r\n elif ajax == 'xml':\r\n return XMLResponse([new_comment,])\r\n else:\r\n return HttpResponseRedirect(_get_next(request))\r\n elif ajax==\"json\":\r\n return JSONResponse({'errors' : form.errors}, is_iterable=False)\r\n elif ajax==\"xml\":\r\n template_str = \"\"\"\r\n<errorlist>\r\n {% for error,name in errors %}\r\n <field name=\"{{ name }}\">\r\n {% for suberror in error %}<error>{{ suberror }}</error>{% endfor %}\r\n </field>\r\n {% endfor %}\r\n</errorlist>\r\n \"\"\"\r\n response_str = Template(template_str).render(Context({'errors' : zip(form.errors.values(), form.errors.keys())}))\r\n return XMLResponse(response_str, is_iterable=False)\r\n else:\r\n return _preview(request, context_processors, extra_context, form_class=form_class)","def ajax_form_valid(self, form):\n\n try:\n comment = form.save(self.request)\n num_comments = models.CommentModel.objects.permitted().count()\n\n return core_utils.respond_with_json({\n 'success': True,\n 'comment': render_to_string(\n self.template_name,\n RequestContext(self.request, {'comment': comment})\n ),\n 'num_comments': num_comments\n })\n except exceptions.RapidCommentingError as e:\n return core_utils.respond_with_json({\n 'success': False,\n 'reason': e.value\n })","def create_comment(request):\n\n # get data\n in_data = getRequestData(request)\n\n # get the Thread associated with the comments\n mythread = Thread.objects.get(id=in_data.get('mythreadid'))\n\n # save in database\n try:\n comment = Comment(pub_date = datetime.datetime.now(pytz.timezone('US/Eastern')), username = in_data.get('myusername'), text = in_data.get('mytext'), score = 0, thread = mythread )\n comment.save()\n except:\n return HttpResponseBadRequest('Error saving to database!')\n\n return JsonResponse(in_data)","def comments():\n return render_template(\"/scene/comments/comments.html\")","def post_comment(id):\n \n form = CommentForm()\n title = 'post comment'\n post = Post.query.filter_by(id=id).first()\n\n if post is None:\n\n abort(404)\n\n if form.validate_on_submit():\n comment = form.comment.data\n new_comment = Comments(opinion = comment, user_id = current_user.id, posts_id = post.id)\n new_comment.save_comment()\n return redirect(url_for('main.view_post', id = post.id))\n\n return render_template('comments.html', form = form, title = title)","def update_comment(request, course_id, comment_id):\r\n comment = cc.Comment.find(comment_id)\r\n if 'body' not in request.POST or not request.POST['body'].strip():\r\n return JsonError(_(\"Body can't be empty\"))\r\n comment.body = request.POST[\"body\"]\r\n comment.save()\r\n if request.is_ajax():\r\n return ajax_content_response(request, SlashSeparatedCourseKey.from_deprecated_string(course_id), comment.to_dict())\r\n else:\r\n return JsonResponse(utils.safe_content(comment.to_dict()))","def edit_comment():\n # Implement me!\n\n logger.info(\"vars: %r\" % request.vars)\n logger.info(\"vars_comment_text: %r\" % request.vars.comment_text)\n logger.info(\"vars id: %r\" % request.vars.comment_id)\n logger.info(\"comment_text: %r\" % db(db.Comments.id == request.vars.comment_id))\n\n #comment.comment_text = request.vars.comment_text\n #comment.edited_on = datetime.datetime.utcnow()\n db(db.Comments.id == request.vars.comment_id).update(comment_text=request.vars.comment_text, edited_on=datetime.datetime.utcnow())\n db.commit()\n logger.info(\"comment_text: %r\" % db(db.Comments.id == request.vars.comment_id))\n return \"ok\"","def add_comment_view(request, e_pk):\n\n element = get_object_or_404(Element, pk=e_pk)\n group = element.tab.group\n\n if request.user not in group.users.all():\n return redirect(reverse('my_groups_view'))\n\n if request.method == 'POST':\n form = CreateCommentForm(request.POST)\n if form.is_valid():\n comment = Comment(\n text=form.cleaned_data['text'],\n creator=request.user,\n element=element,\n )\n comment.save()\n else:\n return HttpResponseBadRequest()\n\n return redirect(reverse('element_view', args=(e_pk,)))","def load_comments(request):\n # TODO: Add the ability to return comment tree in JSON format.\n # First we get the root of the comment tree being requested\n try:\n tree_root, parent_object = _get_or_create_tree_root(request)\n except InvalidCommentException as e:\n return JsonResponse({\n 'ok': False,\n 'error_message': str(e),\n })\n\n # Check if the user doesn't pass the appropriate permission check (on the parent_object)...\n if not user_has_permission(request, parent_object, 'can_view_comments'):\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You do not have permission to view comments for this object.\",\n })\n\n # Once we have our desired nodes, we tack on all of the select/prefetch related stuff\n nodes = tree_root.get_family().select_related('deleted_user_info', 'created_by', 'parent', 'content_type')\\\n .prefetch_related(Prefetch('versions', queryset=CommentVersion.objects.order_by('-date_posted')\\\n .select_related('posting_user', 'deleted_user_info')))\n\n # The 'X_KWARGS' header is populated by settings.kwarg in comments.js\n kwargs = json.loads(request.META.get('HTTP_X_KWARGS', {}))\n kwargs.update({\n 'nodes': nodes,\n 'parent_object': parent_object,\n 'max_depth': tree_root.max_depth\n })\n\n comments_template = get_attr_val(request, parent_object, 'comments_template', 'comments/comments.html', **kwargs)\n\n # In the parent_object, sites can define a function called 'filter_nodes' if they wish to apply any additional filtering to the nodes queryset before it's rendered to the template.\n # Default value is the nodes tree with the deleted comments filtered out.\n nodes = get_attr_val(request, parent_object, \"filter_nodes\", default=nodes.filter(deleted=False), **kwargs)\n kwargs.update({\"nodes\": nodes, 'request': request})\n\n # Checks/assigns permissions to each node (so the template doesn't have to)\n _process_node_permissions(**kwargs)\n\n return JsonResponse({\n 'ok': True,\n 'html_content': loader.render_to_string(comments_template, context=kwargs, request=request),\n 'number_of_comments': tree_root.get_descendant_count()\n })","def post(self):\n comment_id = self.request.get('comment_id')\n post_id = self.request.get('post_id')\n comment = Comment.get_by_id(int(comment_id), parent=comment_key())\n post = Post.get_by_id(int(post_id), parent=blog_key())\n if comment and self.user.key().id() == comment.user.key().id():\n comment.content = self.request.get('content')\n\n have_errors = False\n\n if not comment.content:\n error_content = \"Content is required\"\n have_errors = True\n\n if have_errors:\n self.render(\"edit_comment.html\",\n comment=comment,\n error_content=error_content,\n user=self.user)\n else:\n comment.put()\n time.sleep(0.1)\n\n self.redirect('/blog/%s' % str(post.key().id()))","def add_comment_to_announcement():\n vars = request.vars\n logger.info(\"vars.comment_text: %r\" % (vars.comment_text))\n comment_id = db.Comments.insert(\n comment_text = vars.comment_text,\n score = 1,\n ann_id= vars.ann_id,\n )\n comment = db.Announcements(comment_id)\n\n logger.info(\"api:add_comment_to_announcement ==> comment= %r\" % (comment))\n\n return response.json(comment)","def createcomment(request, pk):\n issue = get_object_or_404(Issue, pk=pk)\n if request.method == \"POST\":\n form = CommentCreationForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.issue = issue\n comment.author = request.user\n comment.created_at = timezone.now()\n comment.save()\n return redirect('office:issue', pk=pk)\n else:\n form = CommentForm()\n return render(request, 'blog/add_comment_to_post.html', {'form': form})","def comment(postid):\n context = {}\n if \"username\" not in flask.session:\n raise InvalidUsage('Forbidden', status_code=403)\n\n connection = insta485.model.get_db()\n cursor = connection.execute(\n \"SELECT * FROM comments WHERE postid=:id\", {'id': postid})\n comments = cursor.fetchall()\n ''' \n if bool(comments) is False:\n raise InvalidUsage('Not Found', status_code=404)\n '''\n # User\n logname = flask.session[\"username\"]\n\n if flask.request.method == 'POST':\n data = flask.request.get_json(force=True)\n context['text'] = data['text']\n context['owner'] = logname\n context['owner_show_url'] = '/u/' + logname + '/'\n connection.execute('INSERT INTO comments (owner, postid, text) \\\n VALUES (?,?,?)', (logname, postid, data['text']))\n cursor = connection.execute('SELECT last_insert_rowid() AS id')\n commentid_dic = cursor.fetchone()\n context['commentid'] = commentid_dic['id']\n context['postid'] = postid\n return flask.jsonify(**context), 201\n\n # url\n context[\"url\"] = flask.request.path\n context['comments'] = []\n\n for i in comments:\n one_comment = {}\n one_comment['commentid'] = i['commentid']\n one_comment['owner'] = i['owner']\n one_comment['owner_show_url'] = '/u/' + i['owner'] + '/'\n one_comment['postid'] = postid\n one_comment['text'] = i['text']\n context['comments'].append(one_comment)\n\n return flask.jsonify(**context)","def about(request):\n data = {}\n if request.method == \"POST\":\n about = AboutForm(request.POST)\n if about.is_valid():\n about.save()\n data['success']=1\n data['message']='Comment successfully added'\n return JsonResponse(data)\n else:\n data['success']=0\n data['message']='Error while adding comment'\n return JsonResponse(data)\n \n else:\n about = AboutForm()\n return render(request, 'login/addcomment.html',\n {'form':about})","def handle_comments(self):\r\n comments = Comment.objects.all()\r\n for c in comments:\r\n new = ThreadedComment(\r\n content_type = c.content_type,\r\n object_id = c.object_id,\r\n comment = c.comment,\r\n user = c.user,\r\n date_submitted = c.submit_date,\r\n date_modified = c.submit_date,\r\n date_approved = c.submit_date,\r\n is_public = c.is_public,\r\n ip_address = c.ip_address,\r\n is_approved = not c.is_removed\r\n )\r\n new.save()","def comment(request, object_id):\n send_charob = request.user.char_ob\n rec_charob = get_character_from_ob(object_id)\n comment_txt = request.POST[\"comment\"]\n roster.create_comment(send_charob, rec_charob, comment_txt)\n return HttpResponseRedirect(reverse(\"character:sheet\", args=(object_id,)))","def save_comment(self):\n self.save()","def post(self, request, pk):\n\n post = Blog.objects.get(pk=int(pk))\n user_id = self.request.session.get('USER_ID')\n\n try:\n user = User.objects.get(pk=user_id)\n except:\n pass\n body = self.request.POST.get('body')\n\n if user_id is None:\n messages.add_message(request, messages.ERROR, \"Please login to add comments.\")\n return HttpResponseRedirect(self)\n\n comments = Comment.objects.create(post=post, author=user, body=body)\n\n d = model_to_dict(post)\n messages.add_message(request, messages.SUCCESS, \"Comment added successfully.\")\n return self.render_to_response(d)","def save_comment(data):\n data['comment_id'] = len(commentslist) + 1\n data['message'] =\"message\"\n data['author'] = \"author\"\n data['date_created'] = datetime.datetime.now()\n # save to list\n commentslist.append(data)","def add_comment_to_post(request, pk):\n post = get_object_or_404(Post, pk=pk)\n if request.method == 'POST':\n form = CommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.post = post\n comment.save()\n return redirect('post_detail', pk=post.pk)\n else:\n form = CommentForm()\n return render(request, 'blog/comment_form.html', {'form': form})","def questions_collection(request):\n if request.method == \"POST\":\n data = json.loads(request.body)\n task = Task.objects.get(id=data.get(\"taskId\", \"\"))\n commenter = User.objects.get(username=data.get(\"commenter\", \"\"))\n content = data.get(\"content\", \"\")\n\n question = Question(\n task=task,\n commenter=commenter,\n content=content\n )\n question.save()\n return JsonResponse({\"message\": \"Question created successfully\"}, status=201)","def comments(self, request, pk=None):\n post = self.get_object()\n comments = Comment.objects.filter(post=post).order_by('created_at')\n serializer = PostCommentsSerializer(comments, many=True)\n return Response(serializer.data, status.HTTP_200_OK)","def add_mvcomment(request, pk):\n\n # Getting the movie object hosting the comment\n movie = get_object_or_404(Movie, pk=pk)\n\n # if POST\n if request.method == \"POST\":\n form = MovieCommentForm(request.POST)\n\n # set the author and redirect if valid form\n if form.is_valid():\n comment = form.save(commit=False)\n comment.author = request.user\n comment.movie = movie\n comment.save()\n return redirect('../', pk=movie.pk)\n else:\n form = MovieCommentForm()\n\n # render the form through the template\n return render(request, {'form': form})","def post_comment(request, next=None, using=None):\n # Fill out some initial data fields from an authenticated user, if present\n data = request.POST.copy()\n if request.user.is_authenticated():\n if not data.get('name', ''):\n data[\"name\"] = request.user.get_full_name() or request.user.username\n if not data.get('email', ''):\n data[\"email\"] = request.user.email\n\n # Check to see if the POST data overrides the view's next argument.\n next = data.get(\"next\", next)\n\n # Look up the object we're trying to comment about\n ctype = data.get(\"content_type\")\n object_pk = data.get(\"object_pk\")\n model = models.get_model(*ctype.split(\".\", 1))\n target = model._default_manager.using(using).get(pk=object_pk)\n\n\n # Construct the comment form\n form = comments.get_form()(target, data=data)\n\n # Check security information\n if form.security_errors():\n return None\n # Create the comment\n comment = form.get_comment_object()\n comment.ip_address = request.META.get(\"REMOTE_ADDR\", None)\n if request.user.is_authenticated():\n comment.user = request.user\n\n # Signal that the comment is about to be saved\n responses = signals.comment_will_be_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n # Save the comment and signal that it was saved\n comment.save()\n message = get_object_or_404(Message, pk = object_pk)\n message.envoyer_commentaire_notification(comment.pk, request.user.username)\n \n signals.comment_was_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n comment_list = [comment]\n return render_to_response('comments/list.html', {'comment_list': comment_list},context_instance=RequestContext(request))","def add_new_comment(request):\n token = request.data.get('token')\n text = request.data.get('text', '')\n post_id = request.data.get('post_id', '')\n permission = request.data.get('permission')\n\n if Token.objects.filter(key=token).exists():\n if len(text) < 10:\n return Response({\"error\": 24})\n if len(text) > 1000:\n return Response({\"error\": 25})\n\n if type(post_id) is int:\n if Post.objects.filter(pk=post_id).exists():\n token = get_object_or_404(Token, key=token)\n post = get_object_or_404(Post, pk=post_id)\n comment = Comment.objects.create(post=post,\n author_id=token.user_id,\n text=text,\n permission=permission)\n serializer = PostSerializer(post, context={'user_id': token.user_id})\n UserFeed.objects.create(user=post.author,\n action_user=token.user,\n post_comment=comment,\n action=\"PostComment\")\n\n printable = set(string.printable)\n msg = filter(lambda x: x in printable, comment.text) \n message = \"{} commented: {}\".format(token.user.username, msg)\n\n custom = {\n \"post_id\": post.id,\n \"avatar\": UserProfile.objects.get(user=token.user).avatar.url\n }\n\n if post.author != token.user:\n user_notification = UserNotification.objects.get(user=post.author)\n send_notification(custom, message, user_notification)\n\n # check @ for users \n for item in text.split(' '):\n if item and item[0] == '@':\n username = item[1:].lower()\n user = User.objects.filter(username__iexact=username).first()\n if not user or user == token.user:\n continue\n UserFeed.objects.create(user=user,\n action_user=token.user,\n post_comment=comment,\n action=\"PostCommentComment\")\n msg = filter(lambda x: x in printable, comment.text) \n message = \"{} commented: {}\".format(token.user.username, msg)\n user_notification = UserNotification.objects.get(user=user)\n send_notification(custom, message, user_notification)\n\n return Response({\"success\": 26,\n \"post\": serializer.data})\n else:\n return Response({\"error\": 27})\n else:\n return Response({\"error\": 17})","def post(self):\n modified_content = self.request.get('comment_edit')\n comment_id = self.request.get('comment_id')\n comment = Comments.get_by_id(int(comment_id))\n user = self.get_active_user()\n\n if user.key().id() == comment.submitter_id:\n comment.content = modified_content\n comment.put()\n self.redirect('/%s' % str(comment.post_id))\n else:\n self.error(403)","def add_comment(request, entry_pk):\n\n blog = get_object_or_404(BlogEntry, pk=entry_pk)\n\n if not request.user.is_authenticated():\n raise PermissionDenied\n\n form = BlogCommentForm(creator=request.user, blog=blog, data=request.POST)\n\n if form.is_valid():\n form.save()\n return HttpResponseRedirect(blog.get_absolute_url())\n\n return single(request, entry_pk=entry_pk, comment_form=form)","def comment_added(self, event):\n pass","def edit(request, comment_id, next=None):\n comment = get_object_or_404(\n get_model(), pk=comment_id, site__pk=settings.SITE_ID\n )\n \n # Make sure user has correct permissions to change the comment,\n # or return a 401 Unauthorized error.\n if not (request.user == comment.user and request.user.has_perm(\"comments.change_comment\")\n or request.user.has_perm(\"comments.can_moderate\")):\n return HttpResponse(\"Unauthorized\", status=401)\n \n # Populate POST data with all required initial data\n # unless they are already in POST\n data = request.POST.copy()\n if not data.get(\"user_name\", \"\"):\n data[\"user_name\"] = request.user.get_full_name() or request.user.username\n if not data.get(\"user_email\"):\n data[\"user_email\"] = request.user.email\n \n next = data.get(\"next\", next)\n CommentEditForm = comments_extension.get_edit_form()\n form = CommentEditForm(data, instance=comment)\n\n if form.security_errors():\n # NOTE: security hash fails!\n return CommentEditBadRequest(\n \"The comment form failed security verification: %s\" % \\\n escape(str(form.security_errors())))\n\n # If there are errors, or if a preview is requested\n if form.errors or \"preview\" in data:\n app_label, model = (form.instance.content_type.app_label, form.instance.content_type.model)\n template_search_list = [\n \"comments/%s/%s/edit-preview.html\" % (app_label, model),\n \"comments/%s/edit-preview.html\" % model,\n \"comments/edit-preview.html\"\n ]\n return render_to_response(\n template_search_list, {\n \"comment_obj\": comment,\n \"comment\": form.data.get(\"comment\", \"\"),\n \"form\": form,\n \"next\": next,\n },\n RequestContext(request, {})\n )\n \n # Otherwise, try to save the comment and emit signals\n if form.is_valid():\n MODERATOR_EDITED = \"moderator edited\"\n flag, created = CommentFlag.objects.get_or_create(\n comment = form.instance,\n user = request.user,\n flag = MODERATOR_EDITED\n )\n \n form.instance.is_removed = False\n form.save()\n\n comment_was_flagged.send(\n sender = comment.__class__,\n comment = comment,\n flag = flag,\n created = created,\n request = request\n )\n \n return utils.next_redirect(\n request, fallback=next or 'comments-comment-done', c=comment._get_pk_val()\n )\n \n else:\n # If we got here, raise Bad Request error.\n return CommentEditBadRequest(\"Could not complete request!\")","def comment_modal(request, comment_id):\n comment = Comment.objects.get(id=comment_id)\n tags = Tag.objects.all()\n return render_to_response('feedback/tagmodal.html', {\n 'object': comment, 'type': 'comment', 'tags': tags,\n }, context_instance=RequestContext(request))","def _create_comment(request, course_key, thread_id=None, parent_id=None):\r\n assert isinstance(course_key, CourseKey)\r\n post = request.POST\r\n\r\n if 'body' not in post or not post['body'].strip():\r\n return JsonError(_(\"Body can't be empty\"))\r\n\r\n course = get_course_with_access(request.user, 'load', course_key)\r\n if course.allow_anonymous:\r\n anonymous = post.get('anonymous', 'false').lower() == 'true'\r\n else:\r\n anonymous = False\r\n\r\n if course.allow_anonymous_to_peers:\r\n anonymous_to_peers = post.get('anonymous_to_peers', 'false').lower() == 'true'\r\n else:\r\n anonymous_to_peers = False\r\n\r\n comment = cc.Comment(\r\n anonymous=anonymous,\r\n anonymous_to_peers=anonymous_to_peers,\r\n user_id=request.user.id,\r\n course_id=course_key.to_deprecated_string(),\r\n thread_id=thread_id,\r\n parent_id=parent_id,\r\n body=post[\"body\"]\r\n )\r\n comment.save()\r\n if post.get('auto_subscribe', 'false').lower() == 'true':\r\n user = cc.User.from_django_user(request.user)\r\n user.follow(comment.thread)\r\n if request.is_ajax():\r\n return ajax_content_response(request, course_key, comment.to_dict())\r\n else:\r\n return JsonResponse(utils.safe_content(comment.to_dict()))","def add_comment(request, listing_id):\n if request.method == \"POST\":\n try:\n listing = Listing.objects.get(pk=listing_id)\n except Listing.DoesNotExist:\n return render(request, \"auctions/errors.html\", {\"error_message\":\n \"something went wrong, the id url argument is not valid\"})\n\n CommentForm = modelform_factory(Comment, exclude=(\"commenter\",\"listing\"))\n # validate and save from the formdata to the database\n form = CommentForm(request.POST)\n try:\n comment = form.save(commit=False)\n comment.commenter = request.user\n comment.listing = listing\n comment.save()\n except:\n # if something went wrong with comment form \n return render(request, \"auctions/errors.html\", {\"error_message\":\n \"something went wrong with the submission of your comment, try again\"})\n\n return redirect(reverse(\"single_listing\", \n args=[listing.title]) +f\"?id={listing.id}\")","def post_comment(self):\n self.post_question()\n return self.client.post(\"api/v2/1/comments\", headers={\"Authorization\": \"{}\".format(self.token())}, data=json.dumps(self.comment), content_type='application/json')","def save_comment(data):\n data['comment_id'] = len(commentslist) + 1\n data['date_created'] = datetime.datetime.now()\n # save to list\n commentslist.append(data)","def add_component_comment(request):\n try:\n person = get_person(request)\n\n print(\"Add components comment. Start.\")\n print(\"Add components comment. Request: \" + str(request))\n\n if request.method == \"POST\":\n # get values from form\n assessment_id = request.POST['assessment_id']\n element_id = None\n try:\n component_id = request.POST['component_id']\n except:\n component_id = None\n try:\n subcomponent_id = request.POST['subcomponent_id']\n except:\n subcomponent_id = None\n try:\n third_component_id = request.POST['third_component_id']\n except:\n third_component_id = None\n try:\n fourth_component_id = request.POST['fourth_component_id']\n except:\n fourth_component_id = None\n try:\n fifth_component_id = request.POST['fifth_component_id']\n except:\n fifth_component_id = None\n comment = request.POST['textComments']\n\n if fifth_component_id:\n element_id = fifth_component_id\n else:\n if fourth_component_id:\n element_id = fourth_component_id\n else:\n if fifth_component_id:\n element_id = fifth_component_id\n else:\n if third_component_id:\n element_id = third_component_id\n else:\n if subcomponent_id:\n element_id = subcomponent_id\n else:\n if component_id:\n element_id = component_id\n\n # get section and assessment\n component = Component.objects.get(id=element_id)\n\n print(\"Add components comment. Component: \" + component.name)\n print(\"Add components comment. comment: \" + comment)\n\n # create comment\n my_comment = AssessmentComponentComment()\n my_comment.assessment = Assessment.objects.get(id=assessment_id)\n my_comment.element = component\n my_comment.comment = comment\n my_comment.person = person\n my_comment.save()\n\n # trace action\n trace_action(TRACE_COMMENT, person, \"User added comment in component: \" + component.name)\n\n # send mail\n try:\n send_mail = request.POST['send_mail']\n t = Thread(target=send_comments_email, args=(my_comment.comment, \"Element: \" + component.name, person))\n t.start()\n # send_comments_email(my_comment.comment, section, person)\n except:\n # checkbox not set\n pass\n\n # redirect to section page\n url_to_redirect = \"/component_2/\" + assessment_id + SLASH\n\n if component_id:\n url_to_redirect += component_id + SLASH\n if subcomponent_id:\n url_to_redirect += subcomponent_id + SLASH\n if third_component_id:\n url_to_redirect += third_component_id + SLASH\n if fourth_component_id:\n url_to_redirect += fourth_component_id + SLASH\n if fifth_component_id:\n url_to_redirect += fifth_component_id + SLASH\n\n return redirect(url_to_redirect, context_instance=RequestContext(request))\n else:\n raise Exception(\"GET call to add new section comment\")\n except:\n if debug_is_on():\n raise\n else:\n return render_to_response(TEMPLATE_ERROR, {\"error_description\": sys.exc_info(), \"crpt_url\": CRPT_URL},\n context_instance=RequestContext(request))","def problem_comments_append(self, identifier, comment, html=None):\n params = {\"text\": comment}\n if html is not None:\n params[\"html\"] = html\n \n self._post(\"problems/%d/comments\" % identifier, json=params)","def add_accomment(request, pk):\n\n actor = get_object_or_404(Actor, pk=pk)\n if request.method == \"POST\":\n form = ActorCommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.author = request.user\n comment.actor = actor\n comment.save()\n return redirect('../', pk=actor.pk)\n else:\n form = ActorCommentForm()\n return render(request, {'form': form})","def comment_added(self, event):\n import simplejson\n comment = str(event[\"comment\"])\n author_name = str(event[\"author\"][\"name\"])\n change_url = str(event[\"change\"][\"url\"])\n change_subject = str(event[\"change\"][\"subject\"])\n comment = simplejson.dumps({\n \"issue\": {\n \"notes\": self._prepare_comment_added_template(event)\n }\n })\n # get a unique list of issue IDs\n subject_issue_ids = self.__get_issue_ids(change_subject)\n comment_issue_ids = self.__get_issue_ids(comment)\n issue_ids = list(set(subject_issue_ids + comment_issue_ids))\n for issue_id in issue_ids:\n self.__add_comment(issue_id, comment)","def post_detail(request, pk):\n post = get_object_or_404(Post, pk=pk)\n comments = post.comments.all\n post.views += 1\n post.save()\n \n if request.method == \"POST\":\n comment_form = CommentForm(request.POST)\n if comment_form.is_valid() and request.user:\n new_comment = comment_form.save(commit=False)\n new_comment.post = post\n new_comment.author = request.user\n new_comment.save()\n elif request.user:\n comment_form = CommentForm()\n \n return render(request, \"details.html\", {\"post\": post, \"comments\": comments, \"comment_form\": comment_form})","def add_comment() -> str:\n if \"markdown\" in request.form:\n if \"file\" in request.form:\n comment = Comment(\n markdown=request.form[\"markdown\"],\n submission_id=Submission.query.filter(\n Submission.filepath.contains(request.form[\"file\"])\n )\n .first()\n .id,\n cell_id=request.form[\"cell_id\"] if \"cell_id\" in request.form else None,\n user=UserModel.get_by_token(session[\"token\"]),\n )\n # If not cell_id this is a general comment\n comment.save()\n else:\n return \"Missing file or cell_id\", 400\n else:\n return \"Missing markdown\", 400\n\n comment_maker = get_template_attribute(\"_macros.html\", \"comment_block\")\n return comment_maker(comment)","def customer_edit_view(h):\n global html\n html = h\n \n user_id = html.var(\"customer_id\"); #get the user id from the url query\n\n common_elements = customer_common_elements()\n \n css_list = common_elements[\"css_list\"]\n\n javascript_list = common_elements[\"javascript_list\"]\n\n all_btn = common_elements[\"all_btn\"]\n\n html.new_header(\"Edit Customers\", \"customer_management.py\", all_btn, css_list, javascript_list)\n customer_string = \"\"\"\n <div>\n <form action=\"customer_put_ajax.py\" method=\"get\" id=\"add_customer_form\" name=\"add_customer_form\" autocomplete=\"on\" >\n <div class=\"form-div\">\n <table class=\"tt-table\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n <tr>\n <th class=\"cell-title\">Edit Customer</th>\n </tr>\n </table>\n <div class=\"form-body\">\n <div class=\"row-elem\">\n <input type=\"hidden\" id=\"user_id\" name=\"user_id\" disabled='disabled' />\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"username\">Customer User Name</label>\n <input type=\"text\" id=\"user_name\" name=\"user_name\" disabled='disabled'\n title=\"Choose Unique User Name. <br/>Must be at least 5 characters.\" />\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"password\">Password</label>\n <input type=\"password\" id=\"password\" name=\"password\" title=\"Must be at least 8 characters. \"/>\n </div>\n \"\"\"\n customer_string += \"\"\"\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"groups\">Select Group</label>\n \"\"\"\n customer_string += (customer_group_customer_widget())\n customer_string += \"\"\"\n </div>\n \"\"\"\n customer_string += \"\"\"\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"first_name\">First Name</label>\n <input type=\"text\" id=\"first_name\" name=\"first_name\" title=\"Please Enter First name.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"last_name\">Last Name</label>\n <input type=\"text\" id=\"last_name\" name=\"last_name\" title=\"Please Enter Last name.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"company_name\">Company</label>\n <input type=\"text\" id=\"company_name\" name=\"company_name\" title=\"Please Enter Company Name.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"designation\">Designation</label>\n <input type=\"text\" id=\"designation\" name=\"designation\" title=\"Please Enter Designation.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"mobile_no\">Mobile Number</label>\n <input type=\"text\" id=\"mobile_no\" name=\"mobile_no\" \n title=\"Please Enter Mobile Number<br/> Don't include +91 or 0.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"telephone_no\">Telephone Number</label>\n <input type=\"text\" id=\"telephone_no\" name=\"telephone_no\" \n title=\"Please Enter Mobile Number<br/> Don't include +91 or 0.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"fax\">Fax</label>\n <input type=\"text\" id=\"fax\" name=\"fax\" \n title=\"Please Enter Mobile Number<br/> Don't include +91 or 0.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"email_id\">E-Mail ID</label>\n <input type=\"text\" id=\"email_id\" name=\"email_id\" title=\"Please Enter E-Mail ID.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"city_id\">City</label>\n <input type=\"text\" id=\"city_id\" name=\"city_id\" title=\"Please Enter City Name.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"state_id\">State</label>\n <input type=\"text\" id=\"state_id\" name=\"state_id\" title=\"Please Enter State.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"country_id\">Country</label>\n <input type=\"text\" id=\"country_id\" name=\"country_id\" title=\"Please Enter Country.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"usage\">Usage</label>\n <select id='usage' name='usage'>\n <option value=0>Personal</option>\n <option value=1>Commercial</option>\n </select>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"purpose\">Purpose</label>\n <input type=\"text\" id=\"purpose\" name=\"purpose\" title=\"Please Enter Purpose.\"/>\n </div>\n <div class=\"row-elem\">\n <label class=\"lbl lbl-big\" for=\"address\">Address</label>\n <textarea id=\"address\" name=\"address\" title=\"Please Enter own Address.\"></textarea>\n </div>\n </div>\n </div>\n <div class=\"form-div-footer\">\n <button type=\"submit\" class=\"yo-small yo-button\"><span class=\"add\">Save</span></button>\n <button type=\"reset\" class=\"yo-small yo-button\" id=\"close_add_user\"><span class=\"cancel\">Cancel</span></button>\n </div>\n </form>\n </div>\n \"\"\" \n customer_string += \"\"\"\n <script>\n put_customer_values(\"%s\");\n post_customers(action=\"put\", user_id = \"%s\");\n </script>\n \"\"\" %(user_id,user_id)\n html.write(customer_string)\n html.new_footer()","def mai_ajax_edit_news(request, id1, template_name='generic/form.html', form_class=NewsForm):\n if request.method == 'POST':\n form = form_class(data=request.POST)\n if form.is_valid():\n dictionary = form.cleaned_data\n dictionary.update({'news_id': id1})\n prep_data(('admin_clm/news/edit/', dictionary), request.session)\n\n return messages_ajax.success(_('News entry edited.'))\n\n else:\n rest_data = prep_data(('admin_clm/news/get_by_id/', {'news_id': id1}), request.session)\n\n rest_data['sticky'] = rest_data['sticky'] != 0\n form = form_class(rest_data)\n\n return messages_ajax.success(render_to_string(template_name, {'form': form,\n 'text': _('Edit news data:'),\n 'confirmation': _('Save'),\n 'id': id1},\n context_instance=RequestContext(request)),\n status=1)","def _preview(request, context_processors, extra_context, form_class=ThreadedCommentForm):\r\n _adjust_max_comment_length(form_class)\r\n form = form_class(request.POST or None)\r\n context = {\r\n 'next' : _get_next(request),\r\n 'form' : form,\r\n }\r\n if form.is_valid():\r\n new_comment = form.save(commit=False)\r\n context['comment'] = new_comment\r\n else:\r\n context['comment'] = None\r\n return render_to_response(\r\n 'threadedcomments/preview_comment.html',\r\n extra_context, \r\n context_instance = RequestContext(request, context, context_processors)\r\n )","def question_comments(request, question, form=None):\n populate_foreign_key_caches(User, (\n ((question,), ('author', 'last_edited_by', 'closed_by')),\n ),\n fields=('username', 'gravatar', 'reputation', 'gold', 'silver',\n 'bronze'))\n\n content_type = ContentType.objects.get_for_model(Question)\n comments = Comment.objects.filter(content_type=content_type,\n object_id=question.id)\n\n if form is None:\n form = CommentForm()\n\n return render_to_response('question.html', {\n 'title': u'Comments on %s' % question.title,\n 'question': question,\n 'tags': question.tags.all(),\n 'comments': comments,\n 'comment_form': form,\n }, context_instance=RequestContext(request))","def comments(self, request, pk=None):\n\n if request.method == 'GET':\n user_wall_post = self.get_object()\n post_comments = UserWallPostComment.objects.filter(user_wall_post=user_wall_post)\n post_comment_serializer = UserWallPostCommentSerializer(post_comments, many=True)\n return Response(post_comment_serializer.data)\n\n user_wall_post = self.get_object()\n post_comment_serializer = UserWallPostCommentSerializer(data=request.data)\n post_comment_serializer.is_valid(raise_exception=True)\n post_comment_serializer.save(comment_by=self.request.user, user_wall_post=user_wall_post)\n\n to_user = user_wall_post.owner\n from_user = request.user\n UserNotification.create_post_friend_comment_notification(from_user, to_user, 'Right', id=pk)\n return Response(data=post_comment_serializer.data, status=201)","def form_valid(self, form):\n post = self.get_object()\n #WAS: post.comment_add(form.cleaned_data['text'], self.request.user)\n post.add_comment(form.cleaned_data['text'], \n self.request.user,\n added_at=None, \n by_email=False\n )\n return views_support.response_success(self.request)","def post(self):\n\n # 160 characters limit\n\n if len(client_data[\"content\"]) >= 200:\n self.write_json_with_status(400,{\n 'result' : 'fail',\n 'reason' : 'content too long'\n })\n\n client_data = self.data\n now = str(time.time())\n comment_id = md5(client_data['content']+now)\n\n new_comment = self.event_comment_table.put_item(data={\n 'CommentID' : comment_id,\n 'CreatorID' : creator_id,\n 'Content' : content,\n 'EventID' : event_id,\n 'Timestamp' : now\n })\n \n\n self.write_json({\n 'comment_id' : comment_id\n })","def add_comment(request):\n \n \"\"\"\n device type\n \"\"\"\n is_Mobile = dmb.process_request(request)\n \n \"\"\"\n User validation \n \"\"\"\n \n \n if request.user.is_anonymous():\n return comm.redirect_login_path(is_Mobile, request)\n result = dayword_comment(request, 1) \n return HttpResponse(json.dumps(result), content_type='application/json')","def add_comment(article_id):\n\n if 'username' in session:\n user = mongo.db.user.find_one({'username': session['username']})\n \n if request.method == 'POST':\n articles = mongo.db.articles\n article = articles.find_one_and_update({'_id': ObjectId(article_id) },\n {'$push':\n {'comments':\n {'username': session['username'],\n 'date': datetime.utcnow(),\n 'text': request.form.get('comment')\n }\n }\n })\n \n comment = mongo.db.article_comments\n comment.insert_one({'user': user['_id'],\n 'from_user': session['username'],\n 'article': article['_id'],\n 'article_title': article['title'],\n 'date': datetime.utcnow(),\n 'to_user': article['author'],\n 'text': request.form.get('comment')\n })\n \n flash('Your comment has been added.', 'success')\n return redirect(url_for('blog'))\n \n flash('Please login to post a comment.', 'info')\n return redirect(url_for('login'))","def form_valid(self, form):\n action = self.get_object()\n #WAS: return action.comment_add(form.cleaned_data['text'], self.request.user)\n action.comment_add(form.cleaned_data['text'], self.request.user)\n return views_support.response_success(self.request)","def question_comments(request, lot_id, question_pk):\n question = get_object_or_404(Question, lot__slug=lot_id, pk=question_pk)\n question.views += 1\n question.save()\n return render(request, 'comments_on_question.html', {'question': question})","def post(self, request, slug):\n article = ArticleInst.fetch(slug)\n comment = request.data.get('comment', {})\n\n serializer = self.serializer_class(data=comment)\n serializer.is_valid(raise_exception=True)\n status_ = status.HTTP_201_CREATED\n\n try:\n Comment.objects.get(\n article=article,\n body=comment.get('body')\n )\n except Comment.DoesNotExist:\n serializer.save(author=request.user, article=article)\n resp = {'message': 'Comment created'}\n resp['data'] = serializer.data\n\n else:\n resp = {'message': \"Seems you've posted an exact comment before\"}\n status_ = status.HTTP_409_CONFLICT\n return Response(data=resp,\n status=status_\n )","def post_comment_form(request):\n try:\n comment, previous_version = get_comment(request)\n except InvalidCommentException as e:\n raise\n\n parent_comment = comment.parent\n tree_root = parent_comment.get_root()\n parent_object = tree_root.content_object\n if not user_can_post_comment(request, comment):\n raise Exception(\"User can't create comments\")\n\n if is_past_max_depth(comment):\n raise Exception(\"Max depth reached\")\n\n # If the comment object (NOT the message) hasn't been saved yet...\n if comment._state.adding == True:\n comment = add_comment(comment)\n\n # Everything has checked out, so we save the new version and return the appropriate response\n version_form, new_version = create_new_version(request, comment)\n\n return comment","def api_draft_comments(request):\n try:\n def sanitize(comment):\n patch = models.Patch.get_by_id(int(comment.patch_id),\n parent=request.patchset.key)\n assert not patch is None\n message_id = str(comment.message_id) if message_id in comment else None,\n return {\n user: request.user,\n issue: request.issue,\n patch: patch,\n lineno: int(comment.lineno),\n left: bool(comment.left),\n text: str(comment.text),\n message_id: message_id,\n }\n return [\n {message_id: _add_or_update_comment(**comment).message_id}\n for comment in map(sanitize, json.load(request.data))\n ]\n except Exception as err:\n return HttpTextResponse('An error occurred.', status=500)","def put(self):\n client_data = self.data\n comment_id = client_data['comment_id']\n\n try:\n comment = self.event_comment_table.get_item(CommentID=comment_id)\n except:\n self.write_json_with_status(400,{\n 'result' : 'fail',\n 'reason' : 'invalid comment id'\n })\n\n if self.current_userid != comment[\"CreatorID\"]:\n self.write_json_with_status(403,{\n 'result' : 'fail',\n 'reason' : 'Anthantication failed'\n })\n\n comment['Coentent'] = client_data['data']\n comment['Timestamp'] = str(time.time())\n comment.partial_save();\n\n self.write_json({\n 'comment_id' : comment_id,\n 'Timestamp' : comment['Timestamp']\n })","def detail(request, article_id):\n article = get_object_or_404(Article, pk=article_id)\n form = PartialCommentForm() #blank form\n return render_to_response('article/detail.html', locals(),\n context_instance=RequestContext(request))","def test_add_new_comment(self):\n\n result = self.client.post(\"/add_new_comment/2\",\n data={\"user_id\": 25, \"park_id\": \"2\", \"content\": \"My dog loves this park!\"},\n follow_redirects=True)\n self.assertIn(\"<h1 class=\\\"title\\\">Bark Park!</h1>\", result.data)","def comment(*args, **kwargs):\r\n kwargs['model'] = ThreadedComment\r\n kwargs['form_class'] = ThreadedCommentForm\r\n return free_comment(*args, **kwargs)","def add_comment(self):\n comment = Comment(\n title=self.title,\n comment=self.comment,\n rating=self.rating,\n user_from_id=g.user.id,\n user_to_id=self.user_to_id\n )\n db.session.add(comment)\n db.session.commit()\n return comment","def mutate(parent, info, comment_details):\n\n user = User.find_or_fail(comment_details.user_id)\n post = Post.find_or_fail(comment_details.post_id)\n\n comment = Comments()\n comment.body = comment_details.body\n\n user.comments().save(comment)\n post.comments().save(comment)\n\n return comment","def test_adds_comment_to_activity(self):\n response = self.client.get(\n reverse(\n 'crt_forms:crt-forms-show',\n kwargs={'id': self.pk}),\n )\n content = str(response.content)\n self.assertTrue(self.note in content)","def feature_comment(request, id=id):\n feature = get_object_or_404(Feature, id=id)\n comment_form = FeatureCommentForm(request.POST, request.FILES)\n if comment_form.is_valid():\n comment = comment_form.save(commit=False)\n comment.user = request.user\n comment.feature = feature\n comment_form.save()\n return redirect(feature_detail, id)","def bug(request, bugid):\n user = request.user\n if user.is_authenticated:\n if request.method == \"POST\":\n user = request.user\n comment = request.POST['comment']\n ticket = get_object_or_404(Ticket, pk=bugid)\n if comment.strip() == '':\n messages.error(request, 'Comment message is required.')\n return redirect('bug', bugid=ticket.pk)\n\n comment = Comment(user=user, comment=comment, ticket=ticket)\n comment.save()\n messages.success(request, 'Thanks for your comment.')\n return redirect('bug', bugid=ticket.pk)\n\n current_bug = get_object_or_404(Ticket, pk=bugid)\n comments = Comment.objects.all().filter(ticket=bugid)\n votes = Vote.objects.all().filter(ticket=bugid).count()\n context = {\n 'bug': current_bug,\n 'comments': comments,\n 'votes': votes\n }\n return render(request, 'bug.html', context)","def add_awcomment(request, pk):\n\n award = get_object_or_404(Award, pk=pk)\n if request.method == \"POST\":\n form = AwardCommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.author = request.user\n comment.award = award\n comment.save()\n return redirect('../', pk=award.pk)\n else:\n form = AwardCommentForm()\n return render(request, {'form': form})","def test_editing_comment(self):\n\n data = {\"comment\": \"Edited comment body.\"}\n result = self.client.post(\"/comment/1/edit.json\", data=data)\n\n self.assertEqual(result.status_code, 200)\n self.assertIn(b\"Edited comment\", result.data)","def endorse_comment(request, course_id, comment_id):\r\n comment = cc.Comment.find(comment_id)\r\n comment.endorsed = request.POST.get('endorsed', 'false').lower() == 'true'\r\n comment.save()\r\n return JsonResponse(utils.safe_content(comment.to_dict()))","def _post(self, data):\n new_comment_id = DB_COMMENT_TABLE.insert(data)\n return new_comment_id","def visit(self, node):\n self.body.append('<div id =\"discourse-comments\"></div>')","def post(self, request, *args, **kwargs):\n serializer = CommentSerializer(data=request.data)\n post_pk = self.kwargs['post_pk']\n post = Post.objects.get(pk=post_pk)\n if serializer.is_valid():\n serializer.save(author=request.user, post=post)\n return Response(serializer.data, status=status.HTTP_201_CREATED)\n return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)","def edit_accomment(request, pk):\n\n comment = get_object_or_404(ActorComment, pk=pk)\n form = ActorCommentForm()\n if request.method == \"POST\":\n form = ActorCommentForm(request.POST, instance=comment)\n\n if form.is_valid():\n form.save()\n url = '../../' + str(comment.actor.pk)\n return redirect(url)\n\n context = {\n 'form': form,\n 'comment': comment,\n }\n return render(request, context)","def post(self):\n post_id = int(self.request.get('post_id'))\n post = Posts.get_by_id(post_id)\n comment = self.request.get('comment')\n submitter_id = self.get_active_user().key().id()\n\n if submitter_id:\n comment = Comments(post_id=post_id, content=comment,\n submitter_id=submitter_id)\n comment.put()\n self.redirect('/%s' % str(post.key().id()))\n else:\n self.error(403)","def fig_comments(request,fig_id):\n try:\n figconf = FigConf.objects.get(id=fig_id)\n except:\n raise Http404\n\n context = {'figconf': figconf}\n return render(request, 'sgdata/fig_comments.html', context)","def start_comment_edit(self, comment_id):\r\n old_body = self.get_comment_body(comment_id)\r\n self._find_within(\"#comment_{} .action-edit\".format(comment_id)).first.click()\r\n EmptyPromise(\r\n lambda: (\r\n self.is_comment_editor_visible(comment_id) and\r\n not self.is_comment_visible(comment_id) and\r\n self._get_comment_editor_value(comment_id) == old_body\r\n ),\r\n \"Comment edit started\"\r\n ).fulfill()","def process_comment(request, comment, post):\n\n if request.user.is_authenticated:\n # We already set auth user's name and email in the form's inital vals.\n comment.author = request.user\n\n # Is this a threaded comment?\n if request.POST.get(\"parent_id\"):\n comment.parent = Comment.objects.get(id=request.POST.get(\"parent_id\"))\n\n # If commenter is logged in, override name and email with stored values from User object\n if request.user.is_authenticated:\n comment.name = request.user.get_full_name()\n comment.email = request.user.email\n\n # Set required relationship to Post object\n comment.post = post\n\n # Get commenter's IP and User-Agent string\n # ip = get_ip(request)\n # if ip is not None:\n # comment.ip_address = ip\n comment.user_agent = request.META.get(\"HTTP_USER_AGENT\", \"\")\n\n # Run spam check\n comment.spam = spam_check(comment)\n\n # Strip disallowed HTML tags. See tangerine docs to customize.\n comment.body = sanitize_comment(comment.body)\n\n # Call comment approval workflow\n comment.approved = get_comment_approval(comment.email, request.user.is_authenticated)\n if comment.approved:\n messages.add_message(request, messages.SUCCESS, \"Your comment has been posted.\")\n else:\n messages.add_message(request, messages.INFO, \"Your comment has been held for moderation.\")\n\n comment.save()\n\n # Alert post author that comment needs moderation, or that it's been auto-published:\n send_comment_moderation_email(comment)","def add_snippet(request):\n original_id = request.GET.get('oid', None)\n \n if request.method == 'POST':\n form = forms.AddSnippetForm(request.POST)\n if form.is_valid():\n new_snippet = form.save(commit=False)\n new_snippet.author = request.user\n if original_id:\n new_snippet.original_id = original_id\n new_snippet.save()\n return HttpResponseRedirect(new_snippet.get_absolute_url())\n else:\n form = forms.AddSnippetForm()\n return render_to_response('cab/add_snippet_form.html',\n { 'form': form },\n context_instance=RequestContext(request))","def post(self, request, slug, id):\n article = ArticleInst.fetch(slug)\n comment = request.data.get('comment', {})\n posted_comment = CommentAPIView.check_comment(\n id, article)\n\n serializer = self.serializer_class(data=comment)\n serializer.is_valid(raise_exception=True)\n status_ = status.HTTP_201_CREATED\n\n try:\n CommentReply.objects.get(\n comment_to=posted_comment,\n author=request.user,\n body=comment.get('body').strip()\n )\n except CommentReply.DoesNotExist:\n serializer.save(author=request.user,\n article=article,\n comment_to=posted_comment)\n resp = {'message': f'Replied to comment of ID {id}'}\n resp['data'] = serializer.data\n\n else:\n resp = {'message': \"Seems you've posted an exact comment before\"}\n status_ = status.HTTP_409_CONFLICT\n return Response(data=resp,\n status=status_\n )","def update_comments(self):\n self.nb_comments = self.comments.count()\n self.save()","def edit_mvcomment(request, pk):\n\n comment = get_object_or_404(MovieComment, pk=pk)\n\n if request.method == \"POST\":\n form = MovieCommentForm(request.POST, instance=comment)\n\n if form.is_valid():\n form.save()\n url = '../../' + str(comment.movie.pk)\n return redirect(url)\n else:\n form = MovieCommentForm(instance=comment)\n\n context = {\n 'form': form,\n 'comment': comment,\n }\n return render(request, context)","def add_vote():\n \n\n comment_id = request.form.get(\"comment_id\")\n voted_item = request.form.get(\"voted_item\")\n\n\n comment = Comment.query.get(int(comment_id))\n \n \n vote_check = Vote.query.filter(Vote.comment_id == int(comment_id), Vote.user_id == session['user_id']).first()\n if vote_check:\n db.session.delete(vote_check)\n db.session.commit()\n else:\n vote_added = Vote(user_id = session['user_id'], comment_id = int(comment_id), up_vote = True)\n db.session.add(vote_added)\n db.session.commit()\n\n \n \n result = {'vote': comment.vote_count(), \"comment_id\": comment_id}\n return jsonify(result)","def like_comment(request):\n\n # get data\n in_data = getRequestData(request)\n\n # increment comment score\n try:\n comment = Comment.objects.get(id=in_data.get('mycommentid'))\n comment.score += 1\n comment.save()\n except:\n return HttpResponseBadRequest('Error saving to database!')\n\n return JsonResponse(in_data)","def edit_comment(self, id, body, **args):\n args.update(id=id, body=body)\n return self.fetch(\"/comment\", post_args=args)","def post(self):\n post_id = self.request.get('post_id')\n post = Post.get_by_id(int(post_id), parent=blog_key())\n content = self.request.get('comment')\n\n if content:\n comment = Comment(parent=comment_key(),\n content=content,\n user=self.user,\n post=post)\n comment.put()\n\n time.sleep(0.1)\n self.redirect('/blog/%s' % str(post.key().id()))","def handle_free_comments(self):\r\n comments = FreeComment.objects.all()\r\n for c in comments:\r\n new = FreeThreadedComment(\r\n content_type = c.content_type,\r\n object_id = c.object_id,\r\n comment = c.comment,\r\n name = c.person_name,\r\n website = '',\r\n email = '',\r\n date_submitted = c.submit_date,\r\n date_modified = c.submit_date,\r\n date_approved = c.submit_date,\r\n is_public = c.is_public,\r\n ip_address = c.ip_address,\r\n is_approved = c.approved\r\n )\r\n new.save()","def process_comments(session, comments):\n for c in tqdm(comments, desc=\"Injecting comments into DB\"):\n db_comment = session.query(Comment).get(c['id'])\n if db_comment:\n db_comment.update(session, **c)\n else:\n Comment.create(session, **c)","def thread_comments(request, myid):\n\n try:\n\t# get comments using the thread (foreign key) id\n mycomments = Comment.objects.filter(thread__id=myid)\n except:\n return HttpResponse(status=404)\n\n if request.method == 'GET':\n serializer = CommentSerializer(mycomments, many=True)\n return drfJSONResponse(serializer.data)","def create_comment(bid, pid):\n # pylint: disable=unused-argument\n form = CommentForm(request.form)\n if request.method == 'POST':\n if form.validate():\n DB.session.add(Comment(pid, current_user.uid, form.text.data))\n DB.session.commit()\n flash('Comment successfully created!')\n else:\n flash(constants.DEFAULT_SUBMISSION_ERR)\n return redirect(request.referrer)","def community_post_create_view(request):\n task = \"Create New\"\n form = AddEditPostForm() # An unbound form\n\n if request.method == 'POST': # If the form has been submitted...\n form = AddEditPostForm(request.POST, request.FILES) # A form bound to the POST data\n if form.is_valid(): # All validation rules pass\n post = form.save(commit=False) # Create a new object from the form, but don't save it to the database\n post.author = request.user # Set the author to the current user\n post.save() # Save the object to the database\n slug_str = \"%s %s\" % (post.title, post.date_posted) # Create a slug from the title and date\n post.slug = slugify(slug_str) # Create the slug\n post.save() # Save the object to the database\n return redirect('community-home') # Redirect to the home page\n\n context = { # Pass the variables to the template\n 'task': task,\n 'form': form,\n }\n return render(request,\n 'pages/patient-community/community-create-update-post.html',\n context) # render the patient community create post page"],"string":"[\n \"def save_comments():\\n potential_deal_id = int(request.form.get(\\\"id\\\"))\\n action = request.form.get(\\\"action\\\")\\n if action.lower() == \\\"none\\\":\\n action = None\\n comments = request.form.get(\\\"comments\\\")\\n db_handler = DBHandler()\\n db_handler.update_by_id(potential_deal_id, action, comments)\\n # return redirect(url_for(\\\"home\\\"))\\n return jsonify({\\\"success\\\": True}), 200\",\n \"def on_comment(self, request, board_id):\\n error = None\\n if request.method == 'POST':\\n creator = request.form['creator']\\n comment = request.form['comment']\\n if len(creator) > 30:\\n error = 'creator name too long'\\n elif len(comment) > 50:\\n error = 'comment too long'\\n else:\\n self.insert_comment(request, board_id)\\n return redirect('/board:' + board_id)\\n return self.render_template('comment.html', error=error)\",\n \"def comments_new():\\n comment = {\\n \\\"title\\\": request.form.get(\\\"title\\\"),\\n \\\"content\\\": request.form.get(\\\"content\\\"),\\n \\\"playlist_id\\\": ObjectId(request.form.get(\\\"playlist._id\\\")),\\n }\\n print(comment)\\n comment_id = db.comments.insert_one(comment).inserted_id\\n return redirect(\\n url_for(\\\"playlists.playlists_show\\\", playlist_id=request.form.get(\\\"playlist._id\\\"))\\n )\",\n \"def add_comment(request):\\n if request.method != 'POST':\\n return HttpResponseRedirect(reverse('wainz.views.composite'))\\n else:\\n img_id = request.POST['id']\\n try:\\n img = Image.objects.get(pk=img_id)\\n except:\\n return HttpResponseRedirect(reverse('wainz.views.composite'))\\n comment_text = request.POST['comment']\\n #TODO sanitize input\\n comment = ImageComment()\\n comment.submission_date = timezone.now()\\n comment.comment_text= comment_text\\n comment.image_id = img_id\\n comment.submitter_id = int(request.POST['uid'])\\n comment.save()\\n return rest.rest_success(request, img_id)\",\n \"def add_comment(request, model, object_id):\\n obj = get_object_or_404(model, id=object_id)\\n if request.method == \\\"POST\\\":\\n form = CommentForm(request.POST)\\n if form.is_valid():\\n Comment.objects.create(\\n content_type = ContentType.objects.get_for_model(model),\\n object_id = object_id,\\n author = request.user,\\n added_at = datetime.datetime.now(),\\n comment = form.cleaned_data['comment']\\n )\\n if request.is_ajax():\\n return JsonResponse({'success': True})\\n else:\\n return HttpResponseRedirect(obj.get_absolute_url())\\n elif request.is_ajax():\\n return JsonResponse({'success': False, 'errors': form.errors})\\n else:\\n form = CommentForm()\\n\\n # Let the appropriate fallback view take care of display/redisplay\\n if model is Question:\\n return question_comments(request, obj, form=form)\\n elif model is Answer:\\n return answer_comments(request, object_id, answer=obj, form=form)\",\n \"def annonceDetailView(request, pk):\\n details = Annonce.objects.get(pk=pk)\\n details.view_annonce += 1\\n details.save()\\n\\n # comment = Comment.objects.filter(\\n # for_post=details,\\n # reply=None).order_by('-create_content')\\n # is_favorite = False\\n # if details.favorite.filter(id=request.user.id).exists():\\n # is_favorite = True\\n # else:\\n # print('favorite is now False')\\n # if request.method == \\\"POST\\\":\\n # print(request.POST)\\n # c_form = commentForm(request.POST or None)\\n # if c_form.is_valid():\\n # content = request.POST.get('content')\\n # reply_id = request.POST.get('comment-id')\\n # comment_qs = None # reply is null\\n # if reply_id:\\n # comment_qs = Comment.objects.get(id=reply_id) \\n # comment_use = Comment(\\n # commented_by=request.user,\\n # for_post=details,\\n # content=content,\\n # reply=comment_qs\\n # )\\n # comment_use.save()\\n # else:\\n # c_form = commentForm()\\n # print(f'send {is_favorite}')\\n context = {\\n # 'is_favorite': is_favorite,\\n 'details': details,\\n \\n # 'comment': comment,\\n # 'commentform': c_form,\\n }\\n # if request.is_ajax():\\n # print('Ajax is true')\\n # html = render_to_string(\\n # 'annonce/comment.html',\\n # context, request=request\\n # )\\n # return JsonResponse({'form': html})\\n return render(request, 'Annonce/detail.html', context)\",\n \"def post_comment_ajax(request, using=None):\\n if not request.is_ajax():\\n return HttpResponseBadRequest(\\\"Expecting Ajax call\\\")\\n\\n data = request.POST.copy()\\n if request.user.is_authenticated():\\n if not data.get('name', ''):\\n data[\\\"name\\\"] = request.user.get_full_name() or request.user.get_username()\\n if not data.get('email', ''):\\n data[\\\"email\\\"] = request.user.email\\n\\n # Look up the object we're trying to comment about\\n ctype = data.get(\\\"content_type\\\")\\n object_pk = data.get(\\\"object_pk\\\")\\n if ctype is None or object_pk is None:\\n return CommentPostBadRequest(\\\"Missing content_type or object_pk field.\\\")\\n try:\\n model = apps.get_model(*ctype.split(\\\".\\\", 1))\\n target = model._default_manager.using(using).get(pk=object_pk)\\n except TypeError:\\n return CommentPostBadRequest(\\n \\\"Invalid content_type value: %r\\\" % escape(ctype))\\n except AttributeError:\\n return CommentPostBadRequest(\\n \\\"The given content-type %r does not resolve to a valid model.\\\" % escape(ctype))\\n except ObjectDoesNotExist:\\n return CommentPostBadRequest(\\n \\\"No object matching content-type %r and object PK %r exists.\\\" % (\\n escape(ctype), escape(object_pk)))\\n except (ValueError, ValidationError) as e:\\n return CommentPostBadRequest(\\n \\\"Attempting go get content-type %r and object PK %r exists raised %s\\\" % (\\n escape(ctype), escape(object_pk), e.__class__.__name__))\\n\\n # Do we want to preview the comment?\\n preview = \\\"preview\\\" in data\\n\\n # Construct the comment form\\n form = django_comments.get_form()(target, data=data)\\n\\n # Check security information\\n if form.security_errors():\\n return CommentPostBadRequest(\\n \\\"The comment form failed security verification: %s\\\" % escape(str(form.security_errors())))\\n\\n # If there are errors or if we requested a preview show the comment\\n if preview:\\n comment = form.get_comment_object() if not form.errors else None\\n if comment is not None and request.user.is_authenticated():\\n comment.user = request.user\\n return _ajax_result(request, form, \\\"preview\\\", comment, object_id=object_pk)\\n if form.errors:\\n return _ajax_result(request, form, \\\"post\\\", object_id=object_pk)\\n\\n # Otherwise create the comment\\n comment = form.get_comment_object()\\n comment.ip_address = get_trusted_ip(request)\\n if request.user.is_authenticated():\\n comment.user = request.user\\n\\n # Signal that the comment is about to be saved\\n responses = signals.comment_will_be_posted.send(\\n sender=comment.__class__,\\n comment=comment,\\n request=request\\n )\\n\\n for (receiver, response) in responses:\\n if response is False:\\n return CommentPostBadRequest(\\n \\\"comment_will_be_posted receiver %r killed the comment\\\" % receiver.__name__)\\n\\n # Save the comment and signal that it was saved\\n comment.save()\\n signals.comment_was_posted.send(\\n sender=comment.__class__,\\n comment=comment,\\n request=request\\n )\\n\\n return _ajax_result(request, form, \\\"post\\\", comment, object_id=object_pk)\",\n \"def add_comment(request, pk, redirect_user):\\n\\n if request.is_ajax():\\n create_comment_and_status_notification(request, pk)\\n if redirect_user == 'profile':\\n return redirect('profile')\\n if redirect_user == 'news_feed':\\n return redirect('news_feed')\",\n \"def _comment():\\r\\n id = request.args.get('answer_id')\\r\\n per_page=current_app.config['FLASKY_ANSWERS_PER_PAGE']\\r\\n answer = Answer.query.get_or_404(id)\\r\\n page = request.args.get('page', type=int, default=1)\\r\\n comment =request.args.get('comment')\\r\\n if current_user.can(Permission.COMMENT) and comment is not None:\\r\\n comment = Comment(body=comment,\\r\\n author=current_user._get_current_object(),\\r\\n answer_id=id)\\r\\n db.session.add(comment)\\r\\n db.session.commit()\\r\\n page = -1\\r\\n if page == -1:\\r\\n page = answer.comments.count() / per_page\\r\\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\\r\\n page,per_page=per_page,error_out=False\\r\\n )\\r\\n macro_comment = get_template_attribute(\\\"_comments.html\\\", \\\"render_comments\\\")\\r\\n macro_page = get_template_attribute(\\\"_page.html\\\", \\\"render_page\\\")\\r\\n comments = pagination.items\\r\\n return jsonify({'result': True,\\r\\n 'comment_html': macro_comment(comments),\\r\\n 'page_html':macro_page(pagination),\\r\\n 'comments_timestamp':[comment.timestamp for comment in comments],\\r\\n 'comments_id':[comment.id for comment in comments]\\r\\n })\",\n \"def _add_comment():\\r\\n per_page = current_app.config['FLASKY_ANSWERS_PER_PAGE']\\r\\n id = request.args.get('answer_id')\\r\\n answer = Answer.query.get_or_404(id)\\r\\n comment =request.args.get('comment')\\r\\n answers = Answer.query.get_or_404(id)\\r\\n page = 1\\r\\n result= False\\r\\n if current_user.can(Permission.COMMENT):\\r\\n comment = Comment(body=comment,\\r\\n author=current_user._get_current_object(),\\r\\n answer_id=id)\\r\\n db.session.add(comment)\\r\\n db.session.commit()\\r\\n page = (answer.comments.count()-1)/per_page + 1\\r\\n result=True\\r\\n pagination = Comment.query.order_by(Comment.timestamp).filter_by(answer_id=id).paginate(\\r\\n page,per_page=per_page,error_out=False\\r\\n )\\r\\n macro_comment = get_template_attribute(\\\"_comments.html\\\", \\\"render_comments\\\")\\r\\n macro_page = get_template_attribute(\\\"_page.html\\\", \\\"render_page\\\")\\r\\n comments = pagination.items\\r\\n return jsonify({'result': result,\\r\\n 'comment_html': macro_comment(comments),\\r\\n 'page_html': macro_page(pagination),\\r\\n 'comments_timestamp': [comment.timestamp for comment in comments],\\r\\n 'comments_id': [comment.id for comment in comments]\\r\\n })\",\n \"def comment_add(request,comment=None, error='', message=''):\\n categories = Category.objects.all()\\n error_fields=[]\\n default_comment = Comment(date=datetime.date.today(), time=datetime.datetime.now().time, source='', detail='', category=Category.objects.filter(description='Events')[0], user_email='')\\n\\n try:\\n added = bool(request.POST['add'])\\n except:\\n added = False\\n try:\\n action = request.POST['action']\\n except:\\n action = 'add'\\n\\n if added == True:\\n try:\\n new_date = parse(request.POST['date'], dayfirst=True)\\n new_time = parse(request.POST['time'])\\n except:\\n error += ' Datetime invalid or not specified.'\\n\\n try:\\n new_detail = request.POST['detail']\\n if new_detail == '':\\n error += ' Comment text is blank.'\\n except:\\n error += ' No comment text provided.'\\n\\n try:\\n new_source = request.POST['source']\\n if new_source == '':\\n error += ' Source is blank.'\\n except:\\n error += ' No comment source provided.'\\n\\n try:\\n new_category = Category.objects.filter(pk=int(request.POST['category_id']))[0] #The [0] is OK since the fact that category_id is a primary key ensures that the array has only length 1.\\n except:\\n error += ' Category invalid or nonexistent.'\\n\\n try:\\n new_user_email = request.POST['user_email']\\n if new_user_email == '':\\n error += ' You haven\\\\'t provided your e-mail address.'\\n except:\\n error += ' No user e-mail address provided.'\\n\\n if error == '':\\n try:\\n new_comment = Comment(date=new_date, time=new_time, source=new_source, detail=new_detail, category=new_category, user_email=new_user_email)\\n new_comment.full_clean()\\n try:\\n new_comment.save()\\n message += 'Your comment was added to the database.'\\n except:\\n error += 'Failed to access the database.'\\n except ValidationError as ve:\\n for k in ve.message_dict.keys():\\n error_fields.append(k)\\n for m in ve.message_dict[k]:\\n error += m + ' '\\n default_comment = new_comment\\n\\n if action == 'saveandaddanother' or action == 'add' or error != '':\\n return render_to_response('feedback/comment_add.html',\\n {'categories': categories,\\n 'error': error,\\n 'error_fields': error_fields,\\n 'message': message,\\n 'added': added,\\n 'comment': default_comment},\\n context_instance=RequestContext(request))\\n elif action == 'save':\\n return index(request, error=error, message=message)\\n else:\\n error += 'Invalid submit action requested.'\\n return render_to_response('feedback/comment_add.html',\\n {'categories': categories,\\n 'error': error,\\n 'error_fields': error_fields,\\n 'added': added,\\n 'message': message,\\n 'comment': default_comment},\\n context_instance=RequestContext(request))\",\n \"def add_comment(request, pk, pk2):\\n template_var = base_template_vals(request)\\n p = request.POST\\n \\n if p.has_key(\\\"content\\\") and p[\\\"content\\\"]:\\n if request.user.is_authenticated():\\n comment = Comment(event=Event.objects.get(id=pk))\\n comment.user = UserProfile.objects.get(django_user=request.user)\\n comment.content = p[\\\"content\\\"]\\n comment.save()\\n\\n # Sys notification\\n from_user = UserProfile.objects.get(django_user=pk2) # Who's event that is commented on\\n to_user = Event.objects.get(id=pk).author\\n event_id = pk\\n sys_notification(to_user, \\\"add_comment\\\", from_user, event_id)\\n return single(request, pk)\",\n \"def newcomment(id):\\n\\n if g.is_logged == False:\\n flash (\\\"You need to be logged in\\\")\\n return redirect(url_for('show_place', id=id))\\n\\n if request.method == 'POST':\\n rating = request.form['rating']\\n\\n if rating.isdigit() == False:\\n flash (\\\"Rating must be between a number between 0 and 5 (inclusive)\\\")\\n elif int(rating) < 0 or int(rating) > 5:\\n flash (\\\"Rating must be between 0 and 5 (inclusive)\\\")\\n else:\\n db = get_db()\\n db.execute('''insert into reviews (rating, title, message, user_id, place_id) values (?, ?, ?,?,?)''', [rating, request.form['title'], request.form['content'], g.user_id, id])\\n db.commit()\\n\\n flash('Your comment was successfully added')\\n return redirect(url_for('show_place', id=id))\",\n \"def free_comment(request, content_type=None, object_id=None, edit_id=None, parent_id=None, add_messages=False, ajax=False, model=FreeThreadedComment, form_class=FreeThreadedCommentForm, context_processors=[], extra_context={}):\\r\\n if not edit_id and not (content_type and object_id):\\r\\n raise Http404 # Must specify either content_type and object_id or edit_id\\r\\n if \\\"preview\\\" in request.POST:\\r\\n return _preview(request, context_processors, extra_context, form_class=form_class)\\r\\n if edit_id:\\r\\n instance = get_object_or_404(model, id=edit_id)\\r\\n else:\\r\\n instance = None\\r\\n _adjust_max_comment_length(form_class)\\r\\n form = form_class(request.POST, instance=instance)\\r\\n if form.is_valid():\\r\\n new_comment = form.save(commit=False)\\r\\n if not edit_id:\\r\\n new_comment.ip_address = request.META.get('REMOTE_ADDR', None)\\r\\n new_comment.content_type = get_object_or_404(ContentType, id = int(content_type))\\r\\n new_comment.object_id = int(object_id)\\r\\n if model == ThreadedComment:\\r\\n new_comment.user = request.user\\r\\n if parent_id:\\r\\n new_comment.parent = get_object_or_404(model, id = int(parent_id))\\r\\n new_comment.save()\\r\\n if model == ThreadedComment:\\r\\n if add_messages:\\r\\n request.user.message_set.create(message=\\\"Your message has been posted successfully.\\\")\\r\\n else:\\r\\n request.session['successful_data'] = {\\r\\n 'name' : form.cleaned_data['name'],\\r\\n 'website' : form.cleaned_data['website'],\\r\\n 'email' : form.cleaned_data['email'],\\r\\n }\\r\\n if ajax == 'json':\\r\\n return JSONResponse([new_comment,])\\r\\n elif ajax == 'xml':\\r\\n return XMLResponse([new_comment,])\\r\\n else:\\r\\n return HttpResponseRedirect(_get_next(request))\\r\\n elif ajax==\\\"json\\\":\\r\\n return JSONResponse({'errors' : form.errors}, is_iterable=False)\\r\\n elif ajax==\\\"xml\\\":\\r\\n template_str = \\\"\\\"\\\"\\r\\n<errorlist>\\r\\n {% for error,name in errors %}\\r\\n <field name=\\\"{{ name }}\\\">\\r\\n {% for suberror in error %}<error>{{ suberror }}</error>{% endfor %}\\r\\n </field>\\r\\n {% endfor %}\\r\\n</errorlist>\\r\\n \\\"\\\"\\\"\\r\\n response_str = Template(template_str).render(Context({'errors' : zip(form.errors.values(), form.errors.keys())}))\\r\\n return XMLResponse(response_str, is_iterable=False)\\r\\n else:\\r\\n return _preview(request, context_processors, extra_context, form_class=form_class)\",\n \"def ajax_form_valid(self, form):\\n\\n try:\\n comment = form.save(self.request)\\n num_comments = models.CommentModel.objects.permitted().count()\\n\\n return core_utils.respond_with_json({\\n 'success': True,\\n 'comment': render_to_string(\\n self.template_name,\\n RequestContext(self.request, {'comment': comment})\\n ),\\n 'num_comments': num_comments\\n })\\n except exceptions.RapidCommentingError as e:\\n return core_utils.respond_with_json({\\n 'success': False,\\n 'reason': e.value\\n })\",\n \"def create_comment(request):\\n\\n # get data\\n in_data = getRequestData(request)\\n\\n # get the Thread associated with the comments\\n mythread = Thread.objects.get(id=in_data.get('mythreadid'))\\n\\n # save in database\\n try:\\n comment = Comment(pub_date = datetime.datetime.now(pytz.timezone('US/Eastern')), username = in_data.get('myusername'), text = in_data.get('mytext'), score = 0, thread = mythread )\\n comment.save()\\n except:\\n return HttpResponseBadRequest('Error saving to database!')\\n\\n return JsonResponse(in_data)\",\n \"def comments():\\n return render_template(\\\"/scene/comments/comments.html\\\")\",\n \"def post_comment(id):\\n \\n form = CommentForm()\\n title = 'post comment'\\n post = Post.query.filter_by(id=id).first()\\n\\n if post is None:\\n\\n abort(404)\\n\\n if form.validate_on_submit():\\n comment = form.comment.data\\n new_comment = Comments(opinion = comment, user_id = current_user.id, posts_id = post.id)\\n new_comment.save_comment()\\n return redirect(url_for('main.view_post', id = post.id))\\n\\n return render_template('comments.html', form = form, title = title)\",\n \"def update_comment(request, course_id, comment_id):\\r\\n comment = cc.Comment.find(comment_id)\\r\\n if 'body' not in request.POST or not request.POST['body'].strip():\\r\\n return JsonError(_(\\\"Body can't be empty\\\"))\\r\\n comment.body = request.POST[\\\"body\\\"]\\r\\n comment.save()\\r\\n if request.is_ajax():\\r\\n return ajax_content_response(request, SlashSeparatedCourseKey.from_deprecated_string(course_id), comment.to_dict())\\r\\n else:\\r\\n return JsonResponse(utils.safe_content(comment.to_dict()))\",\n \"def edit_comment():\\n # Implement me!\\n\\n logger.info(\\\"vars: %r\\\" % request.vars)\\n logger.info(\\\"vars_comment_text: %r\\\" % request.vars.comment_text)\\n logger.info(\\\"vars id: %r\\\" % request.vars.comment_id)\\n logger.info(\\\"comment_text: %r\\\" % db(db.Comments.id == request.vars.comment_id))\\n\\n #comment.comment_text = request.vars.comment_text\\n #comment.edited_on = datetime.datetime.utcnow()\\n db(db.Comments.id == request.vars.comment_id).update(comment_text=request.vars.comment_text, edited_on=datetime.datetime.utcnow())\\n db.commit()\\n logger.info(\\\"comment_text: %r\\\" % db(db.Comments.id == request.vars.comment_id))\\n return \\\"ok\\\"\",\n \"def add_comment_view(request, e_pk):\\n\\n element = get_object_or_404(Element, pk=e_pk)\\n group = element.tab.group\\n\\n if request.user not in group.users.all():\\n return redirect(reverse('my_groups_view'))\\n\\n if request.method == 'POST':\\n form = CreateCommentForm(request.POST)\\n if form.is_valid():\\n comment = Comment(\\n text=form.cleaned_data['text'],\\n creator=request.user,\\n element=element,\\n )\\n comment.save()\\n else:\\n return HttpResponseBadRequest()\\n\\n return redirect(reverse('element_view', args=(e_pk,)))\",\n \"def load_comments(request):\\n # TODO: Add the ability to return comment tree in JSON format.\\n # First we get the root of the comment tree being requested\\n try:\\n tree_root, parent_object = _get_or_create_tree_root(request)\\n except InvalidCommentException as e:\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': str(e),\\n })\\n\\n # Check if the user doesn't pass the appropriate permission check (on the parent_object)...\\n if not user_has_permission(request, parent_object, 'can_view_comments'):\\n return JsonResponse({\\n 'ok': False,\\n 'error_message': \\\"You do not have permission to view comments for this object.\\\",\\n })\\n\\n # Once we have our desired nodes, we tack on all of the select/prefetch related stuff\\n nodes = tree_root.get_family().select_related('deleted_user_info', 'created_by', 'parent', 'content_type')\\\\\\n .prefetch_related(Prefetch('versions', queryset=CommentVersion.objects.order_by('-date_posted')\\\\\\n .select_related('posting_user', 'deleted_user_info')))\\n\\n # The 'X_KWARGS' header is populated by settings.kwarg in comments.js\\n kwargs = json.loads(request.META.get('HTTP_X_KWARGS', {}))\\n kwargs.update({\\n 'nodes': nodes,\\n 'parent_object': parent_object,\\n 'max_depth': tree_root.max_depth\\n })\\n\\n comments_template = get_attr_val(request, parent_object, 'comments_template', 'comments/comments.html', **kwargs)\\n\\n # In the parent_object, sites can define a function called 'filter_nodes' if they wish to apply any additional filtering to the nodes queryset before it's rendered to the template.\\n # Default value is the nodes tree with the deleted comments filtered out.\\n nodes = get_attr_val(request, parent_object, \\\"filter_nodes\\\", default=nodes.filter(deleted=False), **kwargs)\\n kwargs.update({\\\"nodes\\\": nodes, 'request': request})\\n\\n # Checks/assigns permissions to each node (so the template doesn't have to)\\n _process_node_permissions(**kwargs)\\n\\n return JsonResponse({\\n 'ok': True,\\n 'html_content': loader.render_to_string(comments_template, context=kwargs, request=request),\\n 'number_of_comments': tree_root.get_descendant_count()\\n })\",\n \"def post(self):\\n comment_id = self.request.get('comment_id')\\n post_id = self.request.get('post_id')\\n comment = Comment.get_by_id(int(comment_id), parent=comment_key())\\n post = Post.get_by_id(int(post_id), parent=blog_key())\\n if comment and self.user.key().id() == comment.user.key().id():\\n comment.content = self.request.get('content')\\n\\n have_errors = False\\n\\n if not comment.content:\\n error_content = \\\"Content is required\\\"\\n have_errors = True\\n\\n if have_errors:\\n self.render(\\\"edit_comment.html\\\",\\n comment=comment,\\n error_content=error_content,\\n user=self.user)\\n else:\\n comment.put()\\n time.sleep(0.1)\\n\\n self.redirect('/blog/%s' % str(post.key().id()))\",\n \"def add_comment_to_announcement():\\n vars = request.vars\\n logger.info(\\\"vars.comment_text: %r\\\" % (vars.comment_text))\\n comment_id = db.Comments.insert(\\n comment_text = vars.comment_text,\\n score = 1,\\n ann_id= vars.ann_id,\\n )\\n comment = db.Announcements(comment_id)\\n\\n logger.info(\\\"api:add_comment_to_announcement ==> comment= %r\\\" % (comment))\\n\\n return response.json(comment)\",\n \"def createcomment(request, pk):\\n issue = get_object_or_404(Issue, pk=pk)\\n if request.method == \\\"POST\\\":\\n form = CommentCreationForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.issue = issue\\n comment.author = request.user\\n comment.created_at = timezone.now()\\n comment.save()\\n return redirect('office:issue', pk=pk)\\n else:\\n form = CommentForm()\\n return render(request, 'blog/add_comment_to_post.html', {'form': form})\",\n \"def comment(postid):\\n context = {}\\n if \\\"username\\\" not in flask.session:\\n raise InvalidUsage('Forbidden', status_code=403)\\n\\n connection = insta485.model.get_db()\\n cursor = connection.execute(\\n \\\"SELECT * FROM comments WHERE postid=:id\\\", {'id': postid})\\n comments = cursor.fetchall()\\n ''' \\n if bool(comments) is False:\\n raise InvalidUsage('Not Found', status_code=404)\\n '''\\n # User\\n logname = flask.session[\\\"username\\\"]\\n\\n if flask.request.method == 'POST':\\n data = flask.request.get_json(force=True)\\n context['text'] = data['text']\\n context['owner'] = logname\\n context['owner_show_url'] = '/u/' + logname + '/'\\n connection.execute('INSERT INTO comments (owner, postid, text) \\\\\\n VALUES (?,?,?)', (logname, postid, data['text']))\\n cursor = connection.execute('SELECT last_insert_rowid() AS id')\\n commentid_dic = cursor.fetchone()\\n context['commentid'] = commentid_dic['id']\\n context['postid'] = postid\\n return flask.jsonify(**context), 201\\n\\n # url\\n context[\\\"url\\\"] = flask.request.path\\n context['comments'] = []\\n\\n for i in comments:\\n one_comment = {}\\n one_comment['commentid'] = i['commentid']\\n one_comment['owner'] = i['owner']\\n one_comment['owner_show_url'] = '/u/' + i['owner'] + '/'\\n one_comment['postid'] = postid\\n one_comment['text'] = i['text']\\n context['comments'].append(one_comment)\\n\\n return flask.jsonify(**context)\",\n \"def about(request):\\n data = {}\\n if request.method == \\\"POST\\\":\\n about = AboutForm(request.POST)\\n if about.is_valid():\\n about.save()\\n data['success']=1\\n data['message']='Comment successfully added'\\n return JsonResponse(data)\\n else:\\n data['success']=0\\n data['message']='Error while adding comment'\\n return JsonResponse(data)\\n \\n else:\\n about = AboutForm()\\n return render(request, 'login/addcomment.html',\\n {'form':about})\",\n \"def handle_comments(self):\\r\\n comments = Comment.objects.all()\\r\\n for c in comments:\\r\\n new = ThreadedComment(\\r\\n content_type = c.content_type,\\r\\n object_id = c.object_id,\\r\\n comment = c.comment,\\r\\n user = c.user,\\r\\n date_submitted = c.submit_date,\\r\\n date_modified = c.submit_date,\\r\\n date_approved = c.submit_date,\\r\\n is_public = c.is_public,\\r\\n ip_address = c.ip_address,\\r\\n is_approved = not c.is_removed\\r\\n )\\r\\n new.save()\",\n \"def comment(request, object_id):\\n send_charob = request.user.char_ob\\n rec_charob = get_character_from_ob(object_id)\\n comment_txt = request.POST[\\\"comment\\\"]\\n roster.create_comment(send_charob, rec_charob, comment_txt)\\n return HttpResponseRedirect(reverse(\\\"character:sheet\\\", args=(object_id,)))\",\n \"def save_comment(self):\\n self.save()\",\n \"def post(self, request, pk):\\n\\n post = Blog.objects.get(pk=int(pk))\\n user_id = self.request.session.get('USER_ID')\\n\\n try:\\n user = User.objects.get(pk=user_id)\\n except:\\n pass\\n body = self.request.POST.get('body')\\n\\n if user_id is None:\\n messages.add_message(request, messages.ERROR, \\\"Please login to add comments.\\\")\\n return HttpResponseRedirect(self)\\n\\n comments = Comment.objects.create(post=post, author=user, body=body)\\n\\n d = model_to_dict(post)\\n messages.add_message(request, messages.SUCCESS, \\\"Comment added successfully.\\\")\\n return self.render_to_response(d)\",\n \"def save_comment(data):\\n data['comment_id'] = len(commentslist) + 1\\n data['message'] =\\\"message\\\"\\n data['author'] = \\\"author\\\"\\n data['date_created'] = datetime.datetime.now()\\n # save to list\\n commentslist.append(data)\",\n \"def add_comment_to_post(request, pk):\\n post = get_object_or_404(Post, pk=pk)\\n if request.method == 'POST':\\n form = CommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.post = post\\n comment.save()\\n return redirect('post_detail', pk=post.pk)\\n else:\\n form = CommentForm()\\n return render(request, 'blog/comment_form.html', {'form': form})\",\n \"def questions_collection(request):\\n if request.method == \\\"POST\\\":\\n data = json.loads(request.body)\\n task = Task.objects.get(id=data.get(\\\"taskId\\\", \\\"\\\"))\\n commenter = User.objects.get(username=data.get(\\\"commenter\\\", \\\"\\\"))\\n content = data.get(\\\"content\\\", \\\"\\\")\\n\\n question = Question(\\n task=task,\\n commenter=commenter,\\n content=content\\n )\\n question.save()\\n return JsonResponse({\\\"message\\\": \\\"Question created successfully\\\"}, status=201)\",\n \"def comments(self, request, pk=None):\\n post = self.get_object()\\n comments = Comment.objects.filter(post=post).order_by('created_at')\\n serializer = PostCommentsSerializer(comments, many=True)\\n return Response(serializer.data, status.HTTP_200_OK)\",\n \"def add_mvcomment(request, pk):\\n\\n # Getting the movie object hosting the comment\\n movie = get_object_or_404(Movie, pk=pk)\\n\\n # if POST\\n if request.method == \\\"POST\\\":\\n form = MovieCommentForm(request.POST)\\n\\n # set the author and redirect if valid form\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.author = request.user\\n comment.movie = movie\\n comment.save()\\n return redirect('../', pk=movie.pk)\\n else:\\n form = MovieCommentForm()\\n\\n # render the form through the template\\n return render(request, {'form': form})\",\n \"def post_comment(request, next=None, using=None):\\n # Fill out some initial data fields from an authenticated user, if present\\n data = request.POST.copy()\\n if request.user.is_authenticated():\\n if not data.get('name', ''):\\n data[\\\"name\\\"] = request.user.get_full_name() or request.user.username\\n if not data.get('email', ''):\\n data[\\\"email\\\"] = request.user.email\\n\\n # Check to see if the POST data overrides the view's next argument.\\n next = data.get(\\\"next\\\", next)\\n\\n # Look up the object we're trying to comment about\\n ctype = data.get(\\\"content_type\\\")\\n object_pk = data.get(\\\"object_pk\\\")\\n model = models.get_model(*ctype.split(\\\".\\\", 1))\\n target = model._default_manager.using(using).get(pk=object_pk)\\n\\n\\n # Construct the comment form\\n form = comments.get_form()(target, data=data)\\n\\n # Check security information\\n if form.security_errors():\\n return None\\n # Create the comment\\n comment = form.get_comment_object()\\n comment.ip_address = request.META.get(\\\"REMOTE_ADDR\\\", None)\\n if request.user.is_authenticated():\\n comment.user = request.user\\n\\n # Signal that the comment is about to be saved\\n responses = signals.comment_will_be_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n # Save the comment and signal that it was saved\\n comment.save()\\n message = get_object_or_404(Message, pk = object_pk)\\n message.envoyer_commentaire_notification(comment.pk, request.user.username)\\n \\n signals.comment_was_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n comment_list = [comment]\\n return render_to_response('comments/list.html', {'comment_list': comment_list},context_instance=RequestContext(request))\",\n \"def add_new_comment(request):\\n token = request.data.get('token')\\n text = request.data.get('text', '')\\n post_id = request.data.get('post_id', '')\\n permission = request.data.get('permission')\\n\\n if Token.objects.filter(key=token).exists():\\n if len(text) < 10:\\n return Response({\\\"error\\\": 24})\\n if len(text) > 1000:\\n return Response({\\\"error\\\": 25})\\n\\n if type(post_id) is int:\\n if Post.objects.filter(pk=post_id).exists():\\n token = get_object_or_404(Token, key=token)\\n post = get_object_or_404(Post, pk=post_id)\\n comment = Comment.objects.create(post=post,\\n author_id=token.user_id,\\n text=text,\\n permission=permission)\\n serializer = PostSerializer(post, context={'user_id': token.user_id})\\n UserFeed.objects.create(user=post.author,\\n action_user=token.user,\\n post_comment=comment,\\n action=\\\"PostComment\\\")\\n\\n printable = set(string.printable)\\n msg = filter(lambda x: x in printable, comment.text) \\n message = \\\"{} commented: {}\\\".format(token.user.username, msg)\\n\\n custom = {\\n \\\"post_id\\\": post.id,\\n \\\"avatar\\\": UserProfile.objects.get(user=token.user).avatar.url\\n }\\n\\n if post.author != token.user:\\n user_notification = UserNotification.objects.get(user=post.author)\\n send_notification(custom, message, user_notification)\\n\\n # check @ for users \\n for item in text.split(' '):\\n if item and item[0] == '@':\\n username = item[1:].lower()\\n user = User.objects.filter(username__iexact=username).first()\\n if not user or user == token.user:\\n continue\\n UserFeed.objects.create(user=user,\\n action_user=token.user,\\n post_comment=comment,\\n action=\\\"PostCommentComment\\\")\\n msg = filter(lambda x: x in printable, comment.text) \\n message = \\\"{} commented: {}\\\".format(token.user.username, msg)\\n user_notification = UserNotification.objects.get(user=user)\\n send_notification(custom, message, user_notification)\\n\\n return Response({\\\"success\\\": 26,\\n \\\"post\\\": serializer.data})\\n else:\\n return Response({\\\"error\\\": 27})\\n else:\\n return Response({\\\"error\\\": 17})\",\n \"def post(self):\\n modified_content = self.request.get('comment_edit')\\n comment_id = self.request.get('comment_id')\\n comment = Comments.get_by_id(int(comment_id))\\n user = self.get_active_user()\\n\\n if user.key().id() == comment.submitter_id:\\n comment.content = modified_content\\n comment.put()\\n self.redirect('/%s' % str(comment.post_id))\\n else:\\n self.error(403)\",\n \"def add_comment(request, entry_pk):\\n\\n blog = get_object_or_404(BlogEntry, pk=entry_pk)\\n\\n if not request.user.is_authenticated():\\n raise PermissionDenied\\n\\n form = BlogCommentForm(creator=request.user, blog=blog, data=request.POST)\\n\\n if form.is_valid():\\n form.save()\\n return HttpResponseRedirect(blog.get_absolute_url())\\n\\n return single(request, entry_pk=entry_pk, comment_form=form)\",\n \"def comment_added(self, event):\\n pass\",\n \"def edit(request, comment_id, next=None):\\n comment = get_object_or_404(\\n get_model(), pk=comment_id, site__pk=settings.SITE_ID\\n )\\n \\n # Make sure user has correct permissions to change the comment,\\n # or return a 401 Unauthorized error.\\n if not (request.user == comment.user and request.user.has_perm(\\\"comments.change_comment\\\")\\n or request.user.has_perm(\\\"comments.can_moderate\\\")):\\n return HttpResponse(\\\"Unauthorized\\\", status=401)\\n \\n # Populate POST data with all required initial data\\n # unless they are already in POST\\n data = request.POST.copy()\\n if not data.get(\\\"user_name\\\", \\\"\\\"):\\n data[\\\"user_name\\\"] = request.user.get_full_name() or request.user.username\\n if not data.get(\\\"user_email\\\"):\\n data[\\\"user_email\\\"] = request.user.email\\n \\n next = data.get(\\\"next\\\", next)\\n CommentEditForm = comments_extension.get_edit_form()\\n form = CommentEditForm(data, instance=comment)\\n\\n if form.security_errors():\\n # NOTE: security hash fails!\\n return CommentEditBadRequest(\\n \\\"The comment form failed security verification: %s\\\" % \\\\\\n escape(str(form.security_errors())))\\n\\n # If there are errors, or if a preview is requested\\n if form.errors or \\\"preview\\\" in data:\\n app_label, model = (form.instance.content_type.app_label, form.instance.content_type.model)\\n template_search_list = [\\n \\\"comments/%s/%s/edit-preview.html\\\" % (app_label, model),\\n \\\"comments/%s/edit-preview.html\\\" % model,\\n \\\"comments/edit-preview.html\\\"\\n ]\\n return render_to_response(\\n template_search_list, {\\n \\\"comment_obj\\\": comment,\\n \\\"comment\\\": form.data.get(\\\"comment\\\", \\\"\\\"),\\n \\\"form\\\": form,\\n \\\"next\\\": next,\\n },\\n RequestContext(request, {})\\n )\\n \\n # Otherwise, try to save the comment and emit signals\\n if form.is_valid():\\n MODERATOR_EDITED = \\\"moderator edited\\\"\\n flag, created = CommentFlag.objects.get_or_create(\\n comment = form.instance,\\n user = request.user,\\n flag = MODERATOR_EDITED\\n )\\n \\n form.instance.is_removed = False\\n form.save()\\n\\n comment_was_flagged.send(\\n sender = comment.__class__,\\n comment = comment,\\n flag = flag,\\n created = created,\\n request = request\\n )\\n \\n return utils.next_redirect(\\n request, fallback=next or 'comments-comment-done', c=comment._get_pk_val()\\n )\\n \\n else:\\n # If we got here, raise Bad Request error.\\n return CommentEditBadRequest(\\\"Could not complete request!\\\")\",\n \"def comment_modal(request, comment_id):\\n comment = Comment.objects.get(id=comment_id)\\n tags = Tag.objects.all()\\n return render_to_response('feedback/tagmodal.html', {\\n 'object': comment, 'type': 'comment', 'tags': tags,\\n }, context_instance=RequestContext(request))\",\n \"def _create_comment(request, course_key, thread_id=None, parent_id=None):\\r\\n assert isinstance(course_key, CourseKey)\\r\\n post = request.POST\\r\\n\\r\\n if 'body' not in post or not post['body'].strip():\\r\\n return JsonError(_(\\\"Body can't be empty\\\"))\\r\\n\\r\\n course = get_course_with_access(request.user, 'load', course_key)\\r\\n if course.allow_anonymous:\\r\\n anonymous = post.get('anonymous', 'false').lower() == 'true'\\r\\n else:\\r\\n anonymous = False\\r\\n\\r\\n if course.allow_anonymous_to_peers:\\r\\n anonymous_to_peers = post.get('anonymous_to_peers', 'false').lower() == 'true'\\r\\n else:\\r\\n anonymous_to_peers = False\\r\\n\\r\\n comment = cc.Comment(\\r\\n anonymous=anonymous,\\r\\n anonymous_to_peers=anonymous_to_peers,\\r\\n user_id=request.user.id,\\r\\n course_id=course_key.to_deprecated_string(),\\r\\n thread_id=thread_id,\\r\\n parent_id=parent_id,\\r\\n body=post[\\\"body\\\"]\\r\\n )\\r\\n comment.save()\\r\\n if post.get('auto_subscribe', 'false').lower() == 'true':\\r\\n user = cc.User.from_django_user(request.user)\\r\\n user.follow(comment.thread)\\r\\n if request.is_ajax():\\r\\n return ajax_content_response(request, course_key, comment.to_dict())\\r\\n else:\\r\\n return JsonResponse(utils.safe_content(comment.to_dict()))\",\n \"def add_comment(request, listing_id):\\n if request.method == \\\"POST\\\":\\n try:\\n listing = Listing.objects.get(pk=listing_id)\\n except Listing.DoesNotExist:\\n return render(request, \\\"auctions/errors.html\\\", {\\\"error_message\\\":\\n \\\"something went wrong, the id url argument is not valid\\\"})\\n\\n CommentForm = modelform_factory(Comment, exclude=(\\\"commenter\\\",\\\"listing\\\"))\\n # validate and save from the formdata to the database\\n form = CommentForm(request.POST)\\n try:\\n comment = form.save(commit=False)\\n comment.commenter = request.user\\n comment.listing = listing\\n comment.save()\\n except:\\n # if something went wrong with comment form \\n return render(request, \\\"auctions/errors.html\\\", {\\\"error_message\\\":\\n \\\"something went wrong with the submission of your comment, try again\\\"})\\n\\n return redirect(reverse(\\\"single_listing\\\", \\n args=[listing.title]) +f\\\"?id={listing.id}\\\")\",\n \"def post_comment(self):\\n self.post_question()\\n return self.client.post(\\\"api/v2/1/comments\\\", headers={\\\"Authorization\\\": \\\"{}\\\".format(self.token())}, data=json.dumps(self.comment), content_type='application/json')\",\n \"def save_comment(data):\\n data['comment_id'] = len(commentslist) + 1\\n data['date_created'] = datetime.datetime.now()\\n # save to list\\n commentslist.append(data)\",\n \"def add_component_comment(request):\\n try:\\n person = get_person(request)\\n\\n print(\\\"Add components comment. Start.\\\")\\n print(\\\"Add components comment. Request: \\\" + str(request))\\n\\n if request.method == \\\"POST\\\":\\n # get values from form\\n assessment_id = request.POST['assessment_id']\\n element_id = None\\n try:\\n component_id = request.POST['component_id']\\n except:\\n component_id = None\\n try:\\n subcomponent_id = request.POST['subcomponent_id']\\n except:\\n subcomponent_id = None\\n try:\\n third_component_id = request.POST['third_component_id']\\n except:\\n third_component_id = None\\n try:\\n fourth_component_id = request.POST['fourth_component_id']\\n except:\\n fourth_component_id = None\\n try:\\n fifth_component_id = request.POST['fifth_component_id']\\n except:\\n fifth_component_id = None\\n comment = request.POST['textComments']\\n\\n if fifth_component_id:\\n element_id = fifth_component_id\\n else:\\n if fourth_component_id:\\n element_id = fourth_component_id\\n else:\\n if fifth_component_id:\\n element_id = fifth_component_id\\n else:\\n if third_component_id:\\n element_id = third_component_id\\n else:\\n if subcomponent_id:\\n element_id = subcomponent_id\\n else:\\n if component_id:\\n element_id = component_id\\n\\n # get section and assessment\\n component = Component.objects.get(id=element_id)\\n\\n print(\\\"Add components comment. Component: \\\" + component.name)\\n print(\\\"Add components comment. comment: \\\" + comment)\\n\\n # create comment\\n my_comment = AssessmentComponentComment()\\n my_comment.assessment = Assessment.objects.get(id=assessment_id)\\n my_comment.element = component\\n my_comment.comment = comment\\n my_comment.person = person\\n my_comment.save()\\n\\n # trace action\\n trace_action(TRACE_COMMENT, person, \\\"User added comment in component: \\\" + component.name)\\n\\n # send mail\\n try:\\n send_mail = request.POST['send_mail']\\n t = Thread(target=send_comments_email, args=(my_comment.comment, \\\"Element: \\\" + component.name, person))\\n t.start()\\n # send_comments_email(my_comment.comment, section, person)\\n except:\\n # checkbox not set\\n pass\\n\\n # redirect to section page\\n url_to_redirect = \\\"/component_2/\\\" + assessment_id + SLASH\\n\\n if component_id:\\n url_to_redirect += component_id + SLASH\\n if subcomponent_id:\\n url_to_redirect += subcomponent_id + SLASH\\n if third_component_id:\\n url_to_redirect += third_component_id + SLASH\\n if fourth_component_id:\\n url_to_redirect += fourth_component_id + SLASH\\n if fifth_component_id:\\n url_to_redirect += fifth_component_id + SLASH\\n\\n return redirect(url_to_redirect, context_instance=RequestContext(request))\\n else:\\n raise Exception(\\\"GET call to add new section comment\\\")\\n except:\\n if debug_is_on():\\n raise\\n else:\\n return render_to_response(TEMPLATE_ERROR, {\\\"error_description\\\": sys.exc_info(), \\\"crpt_url\\\": CRPT_URL},\\n context_instance=RequestContext(request))\",\n \"def problem_comments_append(self, identifier, comment, html=None):\\n params = {\\\"text\\\": comment}\\n if html is not None:\\n params[\\\"html\\\"] = html\\n \\n self._post(\\\"problems/%d/comments\\\" % identifier, json=params)\",\n \"def add_accomment(request, pk):\\n\\n actor = get_object_or_404(Actor, pk=pk)\\n if request.method == \\\"POST\\\":\\n form = ActorCommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.author = request.user\\n comment.actor = actor\\n comment.save()\\n return redirect('../', pk=actor.pk)\\n else:\\n form = ActorCommentForm()\\n return render(request, {'form': form})\",\n \"def comment_added(self, event):\\n import simplejson\\n comment = str(event[\\\"comment\\\"])\\n author_name = str(event[\\\"author\\\"][\\\"name\\\"])\\n change_url = str(event[\\\"change\\\"][\\\"url\\\"])\\n change_subject = str(event[\\\"change\\\"][\\\"subject\\\"])\\n comment = simplejson.dumps({\\n \\\"issue\\\": {\\n \\\"notes\\\": self._prepare_comment_added_template(event)\\n }\\n })\\n # get a unique list of issue IDs\\n subject_issue_ids = self.__get_issue_ids(change_subject)\\n comment_issue_ids = self.__get_issue_ids(comment)\\n issue_ids = list(set(subject_issue_ids + comment_issue_ids))\\n for issue_id in issue_ids:\\n self.__add_comment(issue_id, comment)\",\n \"def post_detail(request, pk):\\n post = get_object_or_404(Post, pk=pk)\\n comments = post.comments.all\\n post.views += 1\\n post.save()\\n \\n if request.method == \\\"POST\\\":\\n comment_form = CommentForm(request.POST)\\n if comment_form.is_valid() and request.user:\\n new_comment = comment_form.save(commit=False)\\n new_comment.post = post\\n new_comment.author = request.user\\n new_comment.save()\\n elif request.user:\\n comment_form = CommentForm()\\n \\n return render(request, \\\"details.html\\\", {\\\"post\\\": post, \\\"comments\\\": comments, \\\"comment_form\\\": comment_form})\",\n \"def add_comment() -> str:\\n if \\\"markdown\\\" in request.form:\\n if \\\"file\\\" in request.form:\\n comment = Comment(\\n markdown=request.form[\\\"markdown\\\"],\\n submission_id=Submission.query.filter(\\n Submission.filepath.contains(request.form[\\\"file\\\"])\\n )\\n .first()\\n .id,\\n cell_id=request.form[\\\"cell_id\\\"] if \\\"cell_id\\\" in request.form else None,\\n user=UserModel.get_by_token(session[\\\"token\\\"]),\\n )\\n # If not cell_id this is a general comment\\n comment.save()\\n else:\\n return \\\"Missing file or cell_id\\\", 400\\n else:\\n return \\\"Missing markdown\\\", 400\\n\\n comment_maker = get_template_attribute(\\\"_macros.html\\\", \\\"comment_block\\\")\\n return comment_maker(comment)\",\n \"def customer_edit_view(h):\\n global html\\n html = h\\n \\n user_id = html.var(\\\"customer_id\\\"); #get the user id from the url query\\n\\n common_elements = customer_common_elements()\\n \\n css_list = common_elements[\\\"css_list\\\"]\\n\\n javascript_list = common_elements[\\\"javascript_list\\\"]\\n\\n all_btn = common_elements[\\\"all_btn\\\"]\\n\\n html.new_header(\\\"Edit Customers\\\", \\\"customer_management.py\\\", all_btn, css_list, javascript_list)\\n customer_string = \\\"\\\"\\\"\\n <div>\\n <form action=\\\"customer_put_ajax.py\\\" method=\\\"get\\\" id=\\\"add_customer_form\\\" name=\\\"add_customer_form\\\" autocomplete=\\\"on\\\" >\\n <div class=\\\"form-div\\\">\\n <table class=\\\"tt-table\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"100%\\\">\\n <tr>\\n <th class=\\\"cell-title\\\">Edit Customer</th>\\n </tr>\\n </table>\\n <div class=\\\"form-body\\\">\\n <div class=\\\"row-elem\\\">\\n <input type=\\\"hidden\\\" id=\\\"user_id\\\" name=\\\"user_id\\\" disabled='disabled' />\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"username\\\">Customer User Name</label>\\n <input type=\\\"text\\\" id=\\\"user_name\\\" name=\\\"user_name\\\" disabled='disabled'\\n title=\\\"Choose Unique User Name. <br/>Must be at least 5 characters.\\\" />\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"password\\\">Password</label>\\n <input type=\\\"password\\\" id=\\\"password\\\" name=\\\"password\\\" title=\\\"Must be at least 8 characters. \\\"/>\\n </div>\\n \\\"\\\"\\\"\\n customer_string += \\\"\\\"\\\"\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"groups\\\">Select Group</label>\\n \\\"\\\"\\\"\\n customer_string += (customer_group_customer_widget())\\n customer_string += \\\"\\\"\\\"\\n </div>\\n \\\"\\\"\\\"\\n customer_string += \\\"\\\"\\\"\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"first_name\\\">First Name</label>\\n <input type=\\\"text\\\" id=\\\"first_name\\\" name=\\\"first_name\\\" title=\\\"Please Enter First name.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"last_name\\\">Last Name</label>\\n <input type=\\\"text\\\" id=\\\"last_name\\\" name=\\\"last_name\\\" title=\\\"Please Enter Last name.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"company_name\\\">Company</label>\\n <input type=\\\"text\\\" id=\\\"company_name\\\" name=\\\"company_name\\\" title=\\\"Please Enter Company Name.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"designation\\\">Designation</label>\\n <input type=\\\"text\\\" id=\\\"designation\\\" name=\\\"designation\\\" title=\\\"Please Enter Designation.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"mobile_no\\\">Mobile Number</label>\\n <input type=\\\"text\\\" id=\\\"mobile_no\\\" name=\\\"mobile_no\\\" \\n title=\\\"Please Enter Mobile Number<br/> Don't include +91 or 0.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"telephone_no\\\">Telephone Number</label>\\n <input type=\\\"text\\\" id=\\\"telephone_no\\\" name=\\\"telephone_no\\\" \\n title=\\\"Please Enter Mobile Number<br/> Don't include +91 or 0.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"fax\\\">Fax</label>\\n <input type=\\\"text\\\" id=\\\"fax\\\" name=\\\"fax\\\" \\n title=\\\"Please Enter Mobile Number<br/> Don't include +91 or 0.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"email_id\\\">E-Mail ID</label>\\n <input type=\\\"text\\\" id=\\\"email_id\\\" name=\\\"email_id\\\" title=\\\"Please Enter E-Mail ID.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"city_id\\\">City</label>\\n <input type=\\\"text\\\" id=\\\"city_id\\\" name=\\\"city_id\\\" title=\\\"Please Enter City Name.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"state_id\\\">State</label>\\n <input type=\\\"text\\\" id=\\\"state_id\\\" name=\\\"state_id\\\" title=\\\"Please Enter State.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"country_id\\\">Country</label>\\n <input type=\\\"text\\\" id=\\\"country_id\\\" name=\\\"country_id\\\" title=\\\"Please Enter Country.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"usage\\\">Usage</label>\\n <select id='usage' name='usage'>\\n <option value=0>Personal</option>\\n <option value=1>Commercial</option>\\n </select>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"purpose\\\">Purpose</label>\\n <input type=\\\"text\\\" id=\\\"purpose\\\" name=\\\"purpose\\\" title=\\\"Please Enter Purpose.\\\"/>\\n </div>\\n <div class=\\\"row-elem\\\">\\n <label class=\\\"lbl lbl-big\\\" for=\\\"address\\\">Address</label>\\n <textarea id=\\\"address\\\" name=\\\"address\\\" title=\\\"Please Enter own Address.\\\"></textarea>\\n </div>\\n </div>\\n </div>\\n <div class=\\\"form-div-footer\\\">\\n <button type=\\\"submit\\\" class=\\\"yo-small yo-button\\\"><span class=\\\"add\\\">Save</span></button>\\n <button type=\\\"reset\\\" class=\\\"yo-small yo-button\\\" id=\\\"close_add_user\\\"><span class=\\\"cancel\\\">Cancel</span></button>\\n </div>\\n </form>\\n </div>\\n \\\"\\\"\\\" \\n customer_string += \\\"\\\"\\\"\\n <script>\\n put_customer_values(\\\"%s\\\");\\n post_customers(action=\\\"put\\\", user_id = \\\"%s\\\");\\n </script>\\n \\\"\\\"\\\" %(user_id,user_id)\\n html.write(customer_string)\\n html.new_footer()\",\n \"def mai_ajax_edit_news(request, id1, template_name='generic/form.html', form_class=NewsForm):\\n if request.method == 'POST':\\n form = form_class(data=request.POST)\\n if form.is_valid():\\n dictionary = form.cleaned_data\\n dictionary.update({'news_id': id1})\\n prep_data(('admin_clm/news/edit/', dictionary), request.session)\\n\\n return messages_ajax.success(_('News entry edited.'))\\n\\n else:\\n rest_data = prep_data(('admin_clm/news/get_by_id/', {'news_id': id1}), request.session)\\n\\n rest_data['sticky'] = rest_data['sticky'] != 0\\n form = form_class(rest_data)\\n\\n return messages_ajax.success(render_to_string(template_name, {'form': form,\\n 'text': _('Edit news data:'),\\n 'confirmation': _('Save'),\\n 'id': id1},\\n context_instance=RequestContext(request)),\\n status=1)\",\n \"def _preview(request, context_processors, extra_context, form_class=ThreadedCommentForm):\\r\\n _adjust_max_comment_length(form_class)\\r\\n form = form_class(request.POST or None)\\r\\n context = {\\r\\n 'next' : _get_next(request),\\r\\n 'form' : form,\\r\\n }\\r\\n if form.is_valid():\\r\\n new_comment = form.save(commit=False)\\r\\n context['comment'] = new_comment\\r\\n else:\\r\\n context['comment'] = None\\r\\n return render_to_response(\\r\\n 'threadedcomments/preview_comment.html',\\r\\n extra_context, \\r\\n context_instance = RequestContext(request, context, context_processors)\\r\\n )\",\n \"def question_comments(request, question, form=None):\\n populate_foreign_key_caches(User, (\\n ((question,), ('author', 'last_edited_by', 'closed_by')),\\n ),\\n fields=('username', 'gravatar', 'reputation', 'gold', 'silver',\\n 'bronze'))\\n\\n content_type = ContentType.objects.get_for_model(Question)\\n comments = Comment.objects.filter(content_type=content_type,\\n object_id=question.id)\\n\\n if form is None:\\n form = CommentForm()\\n\\n return render_to_response('question.html', {\\n 'title': u'Comments on %s' % question.title,\\n 'question': question,\\n 'tags': question.tags.all(),\\n 'comments': comments,\\n 'comment_form': form,\\n }, context_instance=RequestContext(request))\",\n \"def comments(self, request, pk=None):\\n\\n if request.method == 'GET':\\n user_wall_post = self.get_object()\\n post_comments = UserWallPostComment.objects.filter(user_wall_post=user_wall_post)\\n post_comment_serializer = UserWallPostCommentSerializer(post_comments, many=True)\\n return Response(post_comment_serializer.data)\\n\\n user_wall_post = self.get_object()\\n post_comment_serializer = UserWallPostCommentSerializer(data=request.data)\\n post_comment_serializer.is_valid(raise_exception=True)\\n post_comment_serializer.save(comment_by=self.request.user, user_wall_post=user_wall_post)\\n\\n to_user = user_wall_post.owner\\n from_user = request.user\\n UserNotification.create_post_friend_comment_notification(from_user, to_user, 'Right', id=pk)\\n return Response(data=post_comment_serializer.data, status=201)\",\n \"def form_valid(self, form):\\n post = self.get_object()\\n #WAS: post.comment_add(form.cleaned_data['text'], self.request.user)\\n post.add_comment(form.cleaned_data['text'], \\n self.request.user,\\n added_at=None, \\n by_email=False\\n )\\n return views_support.response_success(self.request)\",\n \"def post(self):\\n\\n # 160 characters limit\\n\\n if len(client_data[\\\"content\\\"]) >= 200:\\n self.write_json_with_status(400,{\\n 'result' : 'fail',\\n 'reason' : 'content too long'\\n })\\n\\n client_data = self.data\\n now = str(time.time())\\n comment_id = md5(client_data['content']+now)\\n\\n new_comment = self.event_comment_table.put_item(data={\\n 'CommentID' : comment_id,\\n 'CreatorID' : creator_id,\\n 'Content' : content,\\n 'EventID' : event_id,\\n 'Timestamp' : now\\n })\\n \\n\\n self.write_json({\\n 'comment_id' : comment_id\\n })\",\n \"def add_comment(request):\\n \\n \\\"\\\"\\\"\\n device type\\n \\\"\\\"\\\"\\n is_Mobile = dmb.process_request(request)\\n \\n \\\"\\\"\\\"\\n User validation \\n \\\"\\\"\\\"\\n \\n \\n if request.user.is_anonymous():\\n return comm.redirect_login_path(is_Mobile, request)\\n result = dayword_comment(request, 1) \\n return HttpResponse(json.dumps(result), content_type='application/json')\",\n \"def add_comment(article_id):\\n\\n if 'username' in session:\\n user = mongo.db.user.find_one({'username': session['username']})\\n \\n if request.method == 'POST':\\n articles = mongo.db.articles\\n article = articles.find_one_and_update({'_id': ObjectId(article_id) },\\n {'$push':\\n {'comments':\\n {'username': session['username'],\\n 'date': datetime.utcnow(),\\n 'text': request.form.get('comment')\\n }\\n }\\n })\\n \\n comment = mongo.db.article_comments\\n comment.insert_one({'user': user['_id'],\\n 'from_user': session['username'],\\n 'article': article['_id'],\\n 'article_title': article['title'],\\n 'date': datetime.utcnow(),\\n 'to_user': article['author'],\\n 'text': request.form.get('comment')\\n })\\n \\n flash('Your comment has been added.', 'success')\\n return redirect(url_for('blog'))\\n \\n flash('Please login to post a comment.', 'info')\\n return redirect(url_for('login'))\",\n \"def form_valid(self, form):\\n action = self.get_object()\\n #WAS: return action.comment_add(form.cleaned_data['text'], self.request.user)\\n action.comment_add(form.cleaned_data['text'], self.request.user)\\n return views_support.response_success(self.request)\",\n \"def question_comments(request, lot_id, question_pk):\\n question = get_object_or_404(Question, lot__slug=lot_id, pk=question_pk)\\n question.views += 1\\n question.save()\\n return render(request, 'comments_on_question.html', {'question': question})\",\n \"def post(self, request, slug):\\n article = ArticleInst.fetch(slug)\\n comment = request.data.get('comment', {})\\n\\n serializer = self.serializer_class(data=comment)\\n serializer.is_valid(raise_exception=True)\\n status_ = status.HTTP_201_CREATED\\n\\n try:\\n Comment.objects.get(\\n article=article,\\n body=comment.get('body')\\n )\\n except Comment.DoesNotExist:\\n serializer.save(author=request.user, article=article)\\n resp = {'message': 'Comment created'}\\n resp['data'] = serializer.data\\n\\n else:\\n resp = {'message': \\\"Seems you've posted an exact comment before\\\"}\\n status_ = status.HTTP_409_CONFLICT\\n return Response(data=resp,\\n status=status_\\n )\",\n \"def post_comment_form(request):\\n try:\\n comment, previous_version = get_comment(request)\\n except InvalidCommentException as e:\\n raise\\n\\n parent_comment = comment.parent\\n tree_root = parent_comment.get_root()\\n parent_object = tree_root.content_object\\n if not user_can_post_comment(request, comment):\\n raise Exception(\\\"User can't create comments\\\")\\n\\n if is_past_max_depth(comment):\\n raise Exception(\\\"Max depth reached\\\")\\n\\n # If the comment object (NOT the message) hasn't been saved yet...\\n if comment._state.adding == True:\\n comment = add_comment(comment)\\n\\n # Everything has checked out, so we save the new version and return the appropriate response\\n version_form, new_version = create_new_version(request, comment)\\n\\n return comment\",\n \"def api_draft_comments(request):\\n try:\\n def sanitize(comment):\\n patch = models.Patch.get_by_id(int(comment.patch_id),\\n parent=request.patchset.key)\\n assert not patch is None\\n message_id = str(comment.message_id) if message_id in comment else None,\\n return {\\n user: request.user,\\n issue: request.issue,\\n patch: patch,\\n lineno: int(comment.lineno),\\n left: bool(comment.left),\\n text: str(comment.text),\\n message_id: message_id,\\n }\\n return [\\n {message_id: _add_or_update_comment(**comment).message_id}\\n for comment in map(sanitize, json.load(request.data))\\n ]\\n except Exception as err:\\n return HttpTextResponse('An error occurred.', status=500)\",\n \"def put(self):\\n client_data = self.data\\n comment_id = client_data['comment_id']\\n\\n try:\\n comment = self.event_comment_table.get_item(CommentID=comment_id)\\n except:\\n self.write_json_with_status(400,{\\n 'result' : 'fail',\\n 'reason' : 'invalid comment id'\\n })\\n\\n if self.current_userid != comment[\\\"CreatorID\\\"]:\\n self.write_json_with_status(403,{\\n 'result' : 'fail',\\n 'reason' : 'Anthantication failed'\\n })\\n\\n comment['Coentent'] = client_data['data']\\n comment['Timestamp'] = str(time.time())\\n comment.partial_save();\\n\\n self.write_json({\\n 'comment_id' : comment_id,\\n 'Timestamp' : comment['Timestamp']\\n })\",\n \"def detail(request, article_id):\\n article = get_object_or_404(Article, pk=article_id)\\n form = PartialCommentForm() #blank form\\n return render_to_response('article/detail.html', locals(),\\n context_instance=RequestContext(request))\",\n \"def test_add_new_comment(self):\\n\\n result = self.client.post(\\\"/add_new_comment/2\\\",\\n data={\\\"user_id\\\": 25, \\\"park_id\\\": \\\"2\\\", \\\"content\\\": \\\"My dog loves this park!\\\"},\\n follow_redirects=True)\\n self.assertIn(\\\"<h1 class=\\\\\\\"title\\\\\\\">Bark Park!</h1>\\\", result.data)\",\n \"def comment(*args, **kwargs):\\r\\n kwargs['model'] = ThreadedComment\\r\\n kwargs['form_class'] = ThreadedCommentForm\\r\\n return free_comment(*args, **kwargs)\",\n \"def add_comment(self):\\n comment = Comment(\\n title=self.title,\\n comment=self.comment,\\n rating=self.rating,\\n user_from_id=g.user.id,\\n user_to_id=self.user_to_id\\n )\\n db.session.add(comment)\\n db.session.commit()\\n return comment\",\n \"def mutate(parent, info, comment_details):\\n\\n user = User.find_or_fail(comment_details.user_id)\\n post = Post.find_or_fail(comment_details.post_id)\\n\\n comment = Comments()\\n comment.body = comment_details.body\\n\\n user.comments().save(comment)\\n post.comments().save(comment)\\n\\n return comment\",\n \"def test_adds_comment_to_activity(self):\\n response = self.client.get(\\n reverse(\\n 'crt_forms:crt-forms-show',\\n kwargs={'id': self.pk}),\\n )\\n content = str(response.content)\\n self.assertTrue(self.note in content)\",\n \"def feature_comment(request, id=id):\\n feature = get_object_or_404(Feature, id=id)\\n comment_form = FeatureCommentForm(request.POST, request.FILES)\\n if comment_form.is_valid():\\n comment = comment_form.save(commit=False)\\n comment.user = request.user\\n comment.feature = feature\\n comment_form.save()\\n return redirect(feature_detail, id)\",\n \"def bug(request, bugid):\\n user = request.user\\n if user.is_authenticated:\\n if request.method == \\\"POST\\\":\\n user = request.user\\n comment = request.POST['comment']\\n ticket = get_object_or_404(Ticket, pk=bugid)\\n if comment.strip() == '':\\n messages.error(request, 'Comment message is required.')\\n return redirect('bug', bugid=ticket.pk)\\n\\n comment = Comment(user=user, comment=comment, ticket=ticket)\\n comment.save()\\n messages.success(request, 'Thanks for your comment.')\\n return redirect('bug', bugid=ticket.pk)\\n\\n current_bug = get_object_or_404(Ticket, pk=bugid)\\n comments = Comment.objects.all().filter(ticket=bugid)\\n votes = Vote.objects.all().filter(ticket=bugid).count()\\n context = {\\n 'bug': current_bug,\\n 'comments': comments,\\n 'votes': votes\\n }\\n return render(request, 'bug.html', context)\",\n \"def add_awcomment(request, pk):\\n\\n award = get_object_or_404(Award, pk=pk)\\n if request.method == \\\"POST\\\":\\n form = AwardCommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.author = request.user\\n comment.award = award\\n comment.save()\\n return redirect('../', pk=award.pk)\\n else:\\n form = AwardCommentForm()\\n return render(request, {'form': form})\",\n \"def test_editing_comment(self):\\n\\n data = {\\\"comment\\\": \\\"Edited comment body.\\\"}\\n result = self.client.post(\\\"/comment/1/edit.json\\\", data=data)\\n\\n self.assertEqual(result.status_code, 200)\\n self.assertIn(b\\\"Edited comment\\\", result.data)\",\n \"def endorse_comment(request, course_id, comment_id):\\r\\n comment = cc.Comment.find(comment_id)\\r\\n comment.endorsed = request.POST.get('endorsed', 'false').lower() == 'true'\\r\\n comment.save()\\r\\n return JsonResponse(utils.safe_content(comment.to_dict()))\",\n \"def _post(self, data):\\n new_comment_id = DB_COMMENT_TABLE.insert(data)\\n return new_comment_id\",\n \"def visit(self, node):\\n self.body.append('<div id =\\\"discourse-comments\\\"></div>')\",\n \"def post(self, request, *args, **kwargs):\\n serializer = CommentSerializer(data=request.data)\\n post_pk = self.kwargs['post_pk']\\n post = Post.objects.get(pk=post_pk)\\n if serializer.is_valid():\\n serializer.save(author=request.user, post=post)\\n return Response(serializer.data, status=status.HTTP_201_CREATED)\\n return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)\",\n \"def edit_accomment(request, pk):\\n\\n comment = get_object_or_404(ActorComment, pk=pk)\\n form = ActorCommentForm()\\n if request.method == \\\"POST\\\":\\n form = ActorCommentForm(request.POST, instance=comment)\\n\\n if form.is_valid():\\n form.save()\\n url = '../../' + str(comment.actor.pk)\\n return redirect(url)\\n\\n context = {\\n 'form': form,\\n 'comment': comment,\\n }\\n return render(request, context)\",\n \"def post(self):\\n post_id = int(self.request.get('post_id'))\\n post = Posts.get_by_id(post_id)\\n comment = self.request.get('comment')\\n submitter_id = self.get_active_user().key().id()\\n\\n if submitter_id:\\n comment = Comments(post_id=post_id, content=comment,\\n submitter_id=submitter_id)\\n comment.put()\\n self.redirect('/%s' % str(post.key().id()))\\n else:\\n self.error(403)\",\n \"def fig_comments(request,fig_id):\\n try:\\n figconf = FigConf.objects.get(id=fig_id)\\n except:\\n raise Http404\\n\\n context = {'figconf': figconf}\\n return render(request, 'sgdata/fig_comments.html', context)\",\n \"def start_comment_edit(self, comment_id):\\r\\n old_body = self.get_comment_body(comment_id)\\r\\n self._find_within(\\\"#comment_{} .action-edit\\\".format(comment_id)).first.click()\\r\\n EmptyPromise(\\r\\n lambda: (\\r\\n self.is_comment_editor_visible(comment_id) and\\r\\n not self.is_comment_visible(comment_id) and\\r\\n self._get_comment_editor_value(comment_id) == old_body\\r\\n ),\\r\\n \\\"Comment edit started\\\"\\r\\n ).fulfill()\",\n \"def process_comment(request, comment, post):\\n\\n if request.user.is_authenticated:\\n # We already set auth user's name and email in the form's inital vals.\\n comment.author = request.user\\n\\n # Is this a threaded comment?\\n if request.POST.get(\\\"parent_id\\\"):\\n comment.parent = Comment.objects.get(id=request.POST.get(\\\"parent_id\\\"))\\n\\n # If commenter is logged in, override name and email with stored values from User object\\n if request.user.is_authenticated:\\n comment.name = request.user.get_full_name()\\n comment.email = request.user.email\\n\\n # Set required relationship to Post object\\n comment.post = post\\n\\n # Get commenter's IP and User-Agent string\\n # ip = get_ip(request)\\n # if ip is not None:\\n # comment.ip_address = ip\\n comment.user_agent = request.META.get(\\\"HTTP_USER_AGENT\\\", \\\"\\\")\\n\\n # Run spam check\\n comment.spam = spam_check(comment)\\n\\n # Strip disallowed HTML tags. See tangerine docs to customize.\\n comment.body = sanitize_comment(comment.body)\\n\\n # Call comment approval workflow\\n comment.approved = get_comment_approval(comment.email, request.user.is_authenticated)\\n if comment.approved:\\n messages.add_message(request, messages.SUCCESS, \\\"Your comment has been posted.\\\")\\n else:\\n messages.add_message(request, messages.INFO, \\\"Your comment has been held for moderation.\\\")\\n\\n comment.save()\\n\\n # Alert post author that comment needs moderation, or that it's been auto-published:\\n send_comment_moderation_email(comment)\",\n \"def add_snippet(request):\\n original_id = request.GET.get('oid', None)\\n \\n if request.method == 'POST':\\n form = forms.AddSnippetForm(request.POST)\\n if form.is_valid():\\n new_snippet = form.save(commit=False)\\n new_snippet.author = request.user\\n if original_id:\\n new_snippet.original_id = original_id\\n new_snippet.save()\\n return HttpResponseRedirect(new_snippet.get_absolute_url())\\n else:\\n form = forms.AddSnippetForm()\\n return render_to_response('cab/add_snippet_form.html',\\n { 'form': form },\\n context_instance=RequestContext(request))\",\n \"def post(self, request, slug, id):\\n article = ArticleInst.fetch(slug)\\n comment = request.data.get('comment', {})\\n posted_comment = CommentAPIView.check_comment(\\n id, article)\\n\\n serializer = self.serializer_class(data=comment)\\n serializer.is_valid(raise_exception=True)\\n status_ = status.HTTP_201_CREATED\\n\\n try:\\n CommentReply.objects.get(\\n comment_to=posted_comment,\\n author=request.user,\\n body=comment.get('body').strip()\\n )\\n except CommentReply.DoesNotExist:\\n serializer.save(author=request.user,\\n article=article,\\n comment_to=posted_comment)\\n resp = {'message': f'Replied to comment of ID {id}'}\\n resp['data'] = serializer.data\\n\\n else:\\n resp = {'message': \\\"Seems you've posted an exact comment before\\\"}\\n status_ = status.HTTP_409_CONFLICT\\n return Response(data=resp,\\n status=status_\\n )\",\n \"def update_comments(self):\\n self.nb_comments = self.comments.count()\\n self.save()\",\n \"def edit_mvcomment(request, pk):\\n\\n comment = get_object_or_404(MovieComment, pk=pk)\\n\\n if request.method == \\\"POST\\\":\\n form = MovieCommentForm(request.POST, instance=comment)\\n\\n if form.is_valid():\\n form.save()\\n url = '../../' + str(comment.movie.pk)\\n return redirect(url)\\n else:\\n form = MovieCommentForm(instance=comment)\\n\\n context = {\\n 'form': form,\\n 'comment': comment,\\n }\\n return render(request, context)\",\n \"def add_vote():\\n \\n\\n comment_id = request.form.get(\\\"comment_id\\\")\\n voted_item = request.form.get(\\\"voted_item\\\")\\n\\n\\n comment = Comment.query.get(int(comment_id))\\n \\n \\n vote_check = Vote.query.filter(Vote.comment_id == int(comment_id), Vote.user_id == session['user_id']).first()\\n if vote_check:\\n db.session.delete(vote_check)\\n db.session.commit()\\n else:\\n vote_added = Vote(user_id = session['user_id'], comment_id = int(comment_id), up_vote = True)\\n db.session.add(vote_added)\\n db.session.commit()\\n\\n \\n \\n result = {'vote': comment.vote_count(), \\\"comment_id\\\": comment_id}\\n return jsonify(result)\",\n \"def like_comment(request):\\n\\n # get data\\n in_data = getRequestData(request)\\n\\n # increment comment score\\n try:\\n comment = Comment.objects.get(id=in_data.get('mycommentid'))\\n comment.score += 1\\n comment.save()\\n except:\\n return HttpResponseBadRequest('Error saving to database!')\\n\\n return JsonResponse(in_data)\",\n \"def edit_comment(self, id, body, **args):\\n args.update(id=id, body=body)\\n return self.fetch(\\\"/comment\\\", post_args=args)\",\n \"def post(self):\\n post_id = self.request.get('post_id')\\n post = Post.get_by_id(int(post_id), parent=blog_key())\\n content = self.request.get('comment')\\n\\n if content:\\n comment = Comment(parent=comment_key(),\\n content=content,\\n user=self.user,\\n post=post)\\n comment.put()\\n\\n time.sleep(0.1)\\n self.redirect('/blog/%s' % str(post.key().id()))\",\n \"def handle_free_comments(self):\\r\\n comments = FreeComment.objects.all()\\r\\n for c in comments:\\r\\n new = FreeThreadedComment(\\r\\n content_type = c.content_type,\\r\\n object_id = c.object_id,\\r\\n comment = c.comment,\\r\\n name = c.person_name,\\r\\n website = '',\\r\\n email = '',\\r\\n date_submitted = c.submit_date,\\r\\n date_modified = c.submit_date,\\r\\n date_approved = c.submit_date,\\r\\n is_public = c.is_public,\\r\\n ip_address = c.ip_address,\\r\\n is_approved = c.approved\\r\\n )\\r\\n new.save()\",\n \"def process_comments(session, comments):\\n for c in tqdm(comments, desc=\\\"Injecting comments into DB\\\"):\\n db_comment = session.query(Comment).get(c['id'])\\n if db_comment:\\n db_comment.update(session, **c)\\n else:\\n Comment.create(session, **c)\",\n \"def thread_comments(request, myid):\\n\\n try:\\n\\t# get comments using the thread (foreign key) id\\n mycomments = Comment.objects.filter(thread__id=myid)\\n except:\\n return HttpResponse(status=404)\\n\\n if request.method == 'GET':\\n serializer = CommentSerializer(mycomments, many=True)\\n return drfJSONResponse(serializer.data)\",\n \"def create_comment(bid, pid):\\n # pylint: disable=unused-argument\\n form = CommentForm(request.form)\\n if request.method == 'POST':\\n if form.validate():\\n DB.session.add(Comment(pid, current_user.uid, form.text.data))\\n DB.session.commit()\\n flash('Comment successfully created!')\\n else:\\n flash(constants.DEFAULT_SUBMISSION_ERR)\\n return redirect(request.referrer)\",\n \"def community_post_create_view(request):\\n task = \\\"Create New\\\"\\n form = AddEditPostForm() # An unbound form\\n\\n if request.method == 'POST': # If the form has been submitted...\\n form = AddEditPostForm(request.POST, request.FILES) # A form bound to the POST data\\n if form.is_valid(): # All validation rules pass\\n post = form.save(commit=False) # Create a new object from the form, but don't save it to the database\\n post.author = request.user # Set the author to the current user\\n post.save() # Save the object to the database\\n slug_str = \\\"%s %s\\\" % (post.title, post.date_posted) # Create a slug from the title and date\\n post.slug = slugify(slug_str) # Create the slug\\n post.save() # Save the object to the database\\n return redirect('community-home') # Redirect to the home page\\n\\n context = { # Pass the variables to the template\\n 'task': task,\\n 'form': form,\\n }\\n return render(request,\\n 'pages/patient-community/community-create-update-post.html',\\n context) # render the patient community create post page\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67972344","0.6647041","0.663194","0.66208017","0.65695584","0.6565645","0.6551287","0.65155035","0.6482362","0.6476776","0.6422695","0.6392417","0.6366266","0.6361407","0.63019305","0.6271926","0.6269781","0.6195616","0.61950845","0.61534417","0.61481893","0.6133915","0.6068977","0.6055021","0.6047715","0.6018806","0.6007634","0.59891266","0.59636855","0.59418595","0.5923893","0.59204197","0.5912901","0.5903977","0.5891716","0.58888763","0.5875274","0.5867666","0.58551806","0.5854555","0.58514994","0.584737","0.5833851","0.5833368","0.582483","0.5811046","0.5809055","0.5768143","0.57428527","0.57402086","0.5731248","0.571119","0.5709281","0.56822777","0.56713784","0.5658102","0.5651685","0.56411266","0.56252265","0.56248486","0.56127256","0.56085235","0.56051594","0.55994487","0.55970085","0.558299","0.55344003","0.5523614","0.55220056","0.5519018","0.550611","0.55019873","0.54991096","0.5484717","0.54765564","0.5458783","0.54375726","0.54203475","0.54121155","0.5409582","0.5409345","0.5391747","0.5390299","0.5390108","0.53791136","0.53765523","0.5342886","0.5338847","0.5337659","0.53329486","0.5329789","0.53165454","0.53129256","0.5312698","0.5307602","0.53064066","0.5304","0.5301681","0.52971876","0.52938384"],"string":"[\n \"0.67972344\",\n \"0.6647041\",\n \"0.663194\",\n \"0.66208017\",\n \"0.65695584\",\n \"0.6565645\",\n \"0.6551287\",\n \"0.65155035\",\n \"0.6482362\",\n \"0.6476776\",\n \"0.6422695\",\n \"0.6392417\",\n \"0.6366266\",\n \"0.6361407\",\n \"0.63019305\",\n \"0.6271926\",\n \"0.6269781\",\n \"0.6195616\",\n \"0.61950845\",\n \"0.61534417\",\n \"0.61481893\",\n \"0.6133915\",\n \"0.6068977\",\n \"0.6055021\",\n \"0.6047715\",\n \"0.6018806\",\n \"0.6007634\",\n \"0.59891266\",\n \"0.59636855\",\n \"0.59418595\",\n \"0.5923893\",\n \"0.59204197\",\n \"0.5912901\",\n \"0.5903977\",\n \"0.5891716\",\n \"0.58888763\",\n \"0.5875274\",\n \"0.5867666\",\n \"0.58551806\",\n \"0.5854555\",\n \"0.58514994\",\n \"0.584737\",\n \"0.5833851\",\n \"0.5833368\",\n \"0.582483\",\n \"0.5811046\",\n \"0.5809055\",\n \"0.5768143\",\n \"0.57428527\",\n \"0.57402086\",\n \"0.5731248\",\n \"0.571119\",\n \"0.5709281\",\n \"0.56822777\",\n \"0.56713784\",\n \"0.5658102\",\n \"0.5651685\",\n \"0.56411266\",\n \"0.56252265\",\n \"0.56248486\",\n \"0.56127256\",\n \"0.56085235\",\n \"0.56051594\",\n \"0.55994487\",\n \"0.55970085\",\n \"0.558299\",\n \"0.55344003\",\n \"0.5523614\",\n \"0.55220056\",\n \"0.5519018\",\n \"0.550611\",\n \"0.55019873\",\n \"0.54991096\",\n \"0.5484717\",\n \"0.54765564\",\n \"0.5458783\",\n \"0.54375726\",\n \"0.54203475\",\n \"0.54121155\",\n \"0.5409582\",\n \"0.5409345\",\n \"0.5391747\",\n \"0.5390299\",\n \"0.5390108\",\n \"0.53791136\",\n \"0.53765523\",\n \"0.5342886\",\n \"0.5338847\",\n \"0.5337659\",\n \"0.53329486\",\n \"0.5329789\",\n \"0.53165454\",\n \"0.53129256\",\n \"0.5312698\",\n \"0.5307602\",\n \"0.53064066\",\n \"0.5304\",\n \"0.5301681\",\n \"0.52971876\",\n \"0.52938384\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6193762"},"document_rank":{"kind":"string","value":"19"}}},{"rowIdx":1395,"cells":{"query":{"kind":"string","value":"View function that returns the comment tree for the desired parent object."},"document":{"kind":"string","value":"def load_comments(request):\n # TODO: Add the ability to return comment tree in JSON format.\n # First we get the root of the comment tree being requested\n try:\n tree_root, parent_object = _get_or_create_tree_root(request)\n except InvalidCommentException as e:\n return JsonResponse({\n 'ok': False,\n 'error_message': str(e),\n })\n\n # Check if the user doesn't pass the appropriate permission check (on the parent_object)...\n if not user_has_permission(request, parent_object, 'can_view_comments'):\n return JsonResponse({\n 'ok': False,\n 'error_message': \"You do not have permission to view comments for this object.\",\n })\n\n # Once we have our desired nodes, we tack on all of the select/prefetch related stuff\n nodes = tree_root.get_family().select_related('deleted_user_info', 'created_by', 'parent', 'content_type')\\\n .prefetch_related(Prefetch('versions', queryset=CommentVersion.objects.order_by('-date_posted')\\\n .select_related('posting_user', 'deleted_user_info')))\n\n # The 'X_KWARGS' header is populated by settings.kwarg in comments.js\n kwargs = json.loads(request.META.get('HTTP_X_KWARGS', {}))\n kwargs.update({\n 'nodes': nodes,\n 'parent_object': parent_object,\n 'max_depth': tree_root.max_depth\n })\n\n comments_template = get_attr_val(request, parent_object, 'comments_template', 'comments/comments.html', **kwargs)\n\n # In the parent_object, sites can define a function called 'filter_nodes' if they wish to apply any additional filtering to the nodes queryset before it's rendered to the template.\n # Default value is the nodes tree with the deleted comments filtered out.\n nodes = get_attr_val(request, parent_object, \"filter_nodes\", default=nodes.filter(deleted=False), **kwargs)\n kwargs.update({\"nodes\": nodes, 'request': request})\n\n # Checks/assigns permissions to each node (so the template doesn't have to)\n _process_node_permissions(**kwargs)\n\n return JsonResponse({\n 'ok': True,\n 'html_content': loader.render_to_string(comments_template, context=kwargs, request=request),\n 'number_of_comments': tree_root.get_descendant_count()\n })"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_by_parent(parent_id):\n return CommentsTreeDAO(root_id=parent_id)","def parent(self) -> Comment | praw.models.Submission:\n # pylint: disable=no-member\n if self.parent_id == self.submission.fullname:\n return self.submission\n\n if self.parent_id in self.submission._comments_by_id:\n # The Comment already exists, so simply return it\n return self.submission._comments_by_id[self.parent_id]\n # pylint: enable=no-member\n\n parent = Comment(self._reddit, self.parent_id.split(\"_\", 1)[1])\n parent._submission = self.submission\n return parent","def parent(self, parent_object, limit_parent_language=True):\n return self.all().parent(parent_object, limit_parent_language)","def children(self):\n return Comment.objects.filter(parent=self)","def get_comments_from_parent(doc):\n\ttry:\n\t\tif is_virtual_doctype(doc.reference_doctype):\n\t\t\t_comments = \"[]\"\n\t\telse:\n\t\t\t_comments = frappe.db.get_value(doc.reference_doctype, doc.reference_name, \"_comments\") or \"[]\"\n\n\texcept Exception as e:\n\t\tif frappe.db.is_missing_table_or_column(e):\n\t\t\t_comments = \"[]\"\n\n\t\telse:\n\t\t\traise\n\n\ttry:\n\t\treturn json.loads(_comments)\n\texcept ValueError:\n\t\treturn []","def get_parent(self) :\n return self.parent","def parent_comments_in_reverse_order(self):\n return self.exclude(parent__isnull=False).order_by(\"-created_at\")\\\n .select_related(\"user\")","def comments(self):\r\n return RepoCommitsComments(self.parent)","def get_parent(self): # real signature unknown; restored from __doc__\n pass","def get_parent(self):\n return self.parent","def get_parent(self):\n return self.parent","def get_parent(self):\n return self.parent","def get_comments_by_parent_genus_type(self, comment_genus_type):\n # Implemented from template for\n # osid.resource.ResourceLookupSession.get_resources_by_parent_genus_type\n # STILL NEED TO IMPLEMENT!!!\n return objects.CommentList([])","def get_parent(self):\n return self.__parent","def get_parent(self):\n return self.__parent","def getParent():","def parent(self):\n return None","def parent(self):\n return None","def parent(self):\n return None","def parent(self):\n return None","def getParent(obj):","def get_parent(self):\n return self._parent","def parent(self):\n\t\treturn self._parent","def parent(self):\n return self.get_parent().specific","def parent(self, node):\r\n return self.find_node(node).parent.content","def comment(self, comment_id):\r\n return RepoCommitsComment(self.parent, comment_id)","def modify_comment_tree(self, comment_tree):\n return comment_tree","def find_parent(self):\n pass","def parent(self):\r\n return self._parent","def get_parent(self):\n if self.parent:\n return self.parent()\n else:\n return None","def parent(self):\n \n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._parent","def parent(self):\n return self._collection.parent(self)","def parent(self, n):\n return n._parent","def comments(self):\r\n return Comments(self)","def comments(self):\r\n return Comments(self)","def comments(self):\r\n return Comments(self)","def parent(self):\n if self._parent is not None:\n return self._parent()\n else:\n return None","def getParents(obj):","def parent(self):\n address = self.parent_address\n try:\n parent = Page.objects.get(address=address)\n except Page.DoesNotExist:\n parent = None\n\n return parent","def parent(self) -> Union[\"ExpressionNode\", None]:\n return self.__parent","def get_comment_url(content_object, parent=None):\r\n kwargs = get_contenttype_kwargs(content_object)\r\n if parent:\r\n if not isinstance(parent, ThreadedComment):\r\n raise template.TemplateSyntaxError, \"get_comment_url requires its parent object to be of type ThreadedComment\"\r\n kwargs.update({'parent_id' : getattr(parent, 'pk', getattr(parent, 'id'))})\r\n return reverse('tc_comment_parent', kwargs=kwargs)\r\n else:\r\n return reverse('tc_comment', kwargs=kwargs)","def parent(self):\n if self.__parent is None:\n return None\n parent = self.__parent()\n if parent is None:\n self.__parent = parent\n return parent","def _get_parent_record(self) -> Link:\n rel = \"parent\"\n href = self.api_endpoint\n return Link(href=href, rel=rel)","def get_parent(self):\n return BinaryNode.or_none(self.parent)","def get_post_comments_recur(comment, comments, parent_comment_id, parent_post_id):\n if 'data' in comment:\n comment_data = comment['data']\n\n new_comment = None\n\n # a new comment exists at this layer, add it to the total list of comments\n if 'body' in comment_data:\n new_comment = {\n \"score\": comment_data['score'],\n \"body\": comment_data['body'],\n \"subreddit\": comment_data['subreddit'],\n \"author\": comment_data['author'],\n \"parent_comment_id\": parent_comment_id,\n \"parent_post_id\": parent_post_id,\n \"created\": comment_data['created'],\n \"comment_id\": comment_data['id']\n }\n comments.append(new_comment)\n\n next_parent_comment_id = parent_comment_id if new_comment is None else new_comment['comment_id']\n\n # recurse on children\n if 'children' in comment_data:\n for child in comment_data['children']:\n comments = get_post_comments_recur(child, comments, next_parent_comment_id, parent_post_id)\n\n # recurse on replies\n if 'replies' in comment_data:\n comments = get_post_comments_recur(comment_data['replies'], comments, next_parent_comment_id, parent_post_id)\n\n return comments","def parent(self) -> Optional[DictionaryObject]:\n return self.get(\"/Parent\")","async def get_comments_tree(request):\n\n comment_id = request.match_info.get('comment_id')\n if comment_id:\n # valitation was in route (\\d+)\n comment_id = int(comment_id)\n tree = CommentsTreeDAO.create_by_parent(comment_id)\n\n else:\n entity_type = request.match_info.get('entity_type')\n if not entity_type:\n return web.HTTPBadRequest(reason=\"Entity params error!\")\n # valitation was in route (\\d+)\n entity_id = int(request.match_info.get('entity_id'))\n tree = CommentsTreeDAO.create_by_entity(entity_type, entity_id)\n\n await tree.fetch(request['conn'])\n\n return web.json_response(await tree.rows)","def get_parent(self):\n return self.lodgeit.get_paste_by_id(self.parent_id)","def comments(self):\r\n return c.Comments(self)","def comments(self):\r\n return c.Comments(self)","def comments(self):\r\n return c.Comments(self)","def parent(self):\r\n if not self._meta.parent:\r\n return None\r\n\r\n if not self.__parent__:\r\n self.__parent__ = self._meta.parent()\r\n\r\n return self.__parent__","def generate_discreet_comment_tree(tribe):\n\n p1 = generate_random_post(tribe, user=get_random_user())\n p2 = generate_random_post(tribe, user=get_random_user(), parent_comment=p1)\n p3 = generate_random_post(tribe, user=get_random_user(), parent_comment=p1)\n p4 = generate_random_post(tribe, user=get_random_user())\n p5 = generate_random_post(tribe, user=get_random_user(), parent_comment=p4)\n p6 = generate_random_post(tribe, user=get_random_user(), parent_comment=p5)\n\n posts = [p1, p2, p3, p4, p5, p6]\n for post in posts:\n post.save()\n\n return posts","def _get_comment_order(self):\n\n comment_tuples = CommentOrdererBase.get_comment_order(self)\n if not comment_tuples:\n return comment_tuples\n elif isinstance(comment_tuples[-1], MissingChildrenTuple):\n missing_children_tuple = comment_tuples.pop()\n else:\n missing_children_tuple = None\n\n special_responder_ids = self.link.responder_ids\n\n # unfortunately we need to look up all the Comments for QA\n comment_ids = {ct.comment_id for ct in comment_tuples}\n comments_by_id = Comment._byID(comment_ids, data=True)\n\n # figure out which comments will be kept (all others are discarded)\n kept_comment_ids = set()\n for comment_tuple in comment_tuples:\n if comment_tuple.depth == 0:\n kept_comment_ids.add(comment_tuple.comment_id)\n continue\n\n comment = comments_by_id[comment_tuple.comment_id]\n parent = comments_by_id[comment.parent_id] if comment.parent_id else None\n\n if comment.author_id in special_responder_ids:\n kept_comment_ids.add(comment_tuple.comment_id)\n continue\n\n if parent and parent.author_id in special_responder_ids:\n kept_comment_ids.add(comment_tuple.comment_id)\n continue\n\n if hasattr(comment, \"distinguished\") and comment.distinguished != \"no\":\n kept_comment_ids.add(comment_tuple.comment_id)\n continue\n\n # add all ancestors to kept_comment_ids\n for comment_id in sorted(kept_comment_ids):\n # sort the comments so we start with the most root level comments\n comment = comments_by_id[comment_id]\n parent_id = comment.parent_id\n\n counter = 0\n while (parent_id and\n parent_id not in kept_comment_ids and\n counter < g.max_comment_parent_walk):\n kept_comment_ids.add(parent_id)\n counter += 1\n\n comment = comments_by_id[parent_id]\n parent_id = comment.parent_id\n\n # remove all comment tuples that aren't in kept_comment_ids\n comment_tuples = [comment_tuple for comment_tuple in comment_tuples\n if comment_tuple.comment_id in kept_comment_ids\n ]\n\n if missing_children_tuple:\n comment_tuples.append(missing_children_tuple)\n\n return comment_tuples","def get_tree_json(self):\n title = self.name\n if self.abbreviation:\n title = title + '(' + self.abbreviation + ')'\n result = {\"title\": title,\n \"key\": self.pk,\n \"tooltip\": self.description,\n \"extraClasses\": 'tag',\n \"lazy\": True,\n \"data\": {\"parentId\": None,\n \"name\": self.name,\n \"abbreviation\": self.abbreviation,\n \"description\": self.description\n }\n }\n parent = self.get_parent()\n if parent:\n result['data']['parentId'] = parent.pk\n return result","def parent(self):\n return getattr(self, \"parent_%s\" % self.discriminator)","def parent(self):\n return self if self.is_root else self.__parent","def get_queryset(self, *args, **kwargs):\n return CommentQuerySet(self.model, using=self._db).order_by(\n self.tree_id_attr,\n self.left_attr\n )","def comments(self):\r\n return comments.Comments(self)","def parent(self):\n raise NotImplemented","def get_parent():\n\n data = list(request.files.values())[0].file.read() if len(request.files) else request.body.read()\n return getParentView(data, request.params)","def make_comment_data(self, comment_id, parent_id=None, children=[]): # pylint: disable=W0102\n return make_minimal_cs_comment({\n \"id\": comment_id,\n \"parent_id\": parent_id,\n \"course_id\": str(self.course.id),\n \"thread_id\": self.thread_id,\n \"thread_type\": \"discussion\",\n \"username\": self.user.username,\n \"user_id\": str(self.user.id),\n \"created_at\": \"2015-06-03T00:00:00Z\",\n \"updated_at\": \"2015-06-03T00:00:00Z\",\n \"body\": \"Original body\",\n \"children\": children,\n })","def parent_model(self):\n return self.prop.parent.class_","def get_parent(self):\n if not self._parent:\n self._parent = yield self.parent_resource.get(self.parent_id)\n\n raise Return(self._parent)","def parent(self):\n other = self\n while True:\n for rev in other._hgmo['parents']:\n parent = Push(rev)\n if parent.id != self.id:\n return parent\n other = parent","def get_parent_model(self):\n return self._model","def get_comment_model(self):\n return get_model()","def GetParent(self):\n return self.parent","def get_question(self):\n if self.is_question:\n return self\n elif self.is_answer or self.is_comment and self.parent.is_question:\n return self.parent\n elif self.is_comment and self.parent.is_answer:\n return self.parent.parent\n raise IntegrityError('Content object {} is orphan.'.format(self.pk))","def parent(self) -> Optional[Heirarchical]:\n return None","def get_parents(self):\n return self.parents","def child_comments_in_order(self):\n return self.order_by(\"created_at\").select_related(\"user\")","def parent(self, p):\n node = self._validate(p)\n return self._make_position(node._parent)","def get_outer(self):\n return self.parent","def parent_document(cls):\n return cls.parent_resources()[0]","def comments(self):\r\n return GistComments(self)","def test_post_matches_parent_when_parent_is_comment(self):\n post = create_a_post()\n parent = Comment.create(body=\"I'm a parent comment\", post=post)\n comment = Comment.create(body=\"I'm a child comment\", parent=parent)\n self.assertIs(comment.post, parent.post)","def get_parent(self):\n return self._find_by_locator().parent","def get_comment_url_json(content_object, parent=None):\r\n try:\r\n return get_comment_url_ajax(content_object, parent, ajax_type=\"json\")\r\n except template.TemplateSyntaxError:\r\n raise template.TemplateSyntaxError, \"get_comment_url_json requires its parent object to be of type ThreadedComment\"\r\n return ''","def get_comment(self, object_id):\n return self.get_object(\"comment\", object_id)","def __str__(self):\n\t\treturn str(self.__parent)","def comments(self):\n return comments.Comments(self)","def outer(self):\n if self.parent is not None:\n self.parent.lines += self.lines\n # print (f\"{self.name} -> {self.parent.name}\")\n return self.parent","def GetParent(self):\r\n\r\n return self._parent","def parent(self):\n raise NotImplementedError()","def parent(self):\n return self.key().parent()","def parentItem(self):\n return None","def viewer(self):\n return self.parent","def parent(self, parent_object):\n lookup = get_parent_lookup_kwargs(parent_object)\n return self.filter(**lookup)"],"string":"[\n \"def create_by_parent(parent_id):\\n return CommentsTreeDAO(root_id=parent_id)\",\n \"def parent(self) -> Comment | praw.models.Submission:\\n # pylint: disable=no-member\\n if self.parent_id == self.submission.fullname:\\n return self.submission\\n\\n if self.parent_id in self.submission._comments_by_id:\\n # The Comment already exists, so simply return it\\n return self.submission._comments_by_id[self.parent_id]\\n # pylint: enable=no-member\\n\\n parent = Comment(self._reddit, self.parent_id.split(\\\"_\\\", 1)[1])\\n parent._submission = self.submission\\n return parent\",\n \"def parent(self, parent_object, limit_parent_language=True):\\n return self.all().parent(parent_object, limit_parent_language)\",\n \"def children(self):\\n return Comment.objects.filter(parent=self)\",\n \"def get_comments_from_parent(doc):\\n\\ttry:\\n\\t\\tif is_virtual_doctype(doc.reference_doctype):\\n\\t\\t\\t_comments = \\\"[]\\\"\\n\\t\\telse:\\n\\t\\t\\t_comments = frappe.db.get_value(doc.reference_doctype, doc.reference_name, \\\"_comments\\\") or \\\"[]\\\"\\n\\n\\texcept Exception as e:\\n\\t\\tif frappe.db.is_missing_table_or_column(e):\\n\\t\\t\\t_comments = \\\"[]\\\"\\n\\n\\t\\telse:\\n\\t\\t\\traise\\n\\n\\ttry:\\n\\t\\treturn json.loads(_comments)\\n\\texcept ValueError:\\n\\t\\treturn []\",\n \"def get_parent(self) :\\n return self.parent\",\n \"def parent_comments_in_reverse_order(self):\\n return self.exclude(parent__isnull=False).order_by(\\\"-created_at\\\")\\\\\\n .select_related(\\\"user\\\")\",\n \"def comments(self):\\r\\n return RepoCommitsComments(self.parent)\",\n \"def get_parent(self): # real signature unknown; restored from __doc__\\n pass\",\n \"def get_parent(self):\\n return self.parent\",\n \"def get_parent(self):\\n return self.parent\",\n \"def get_parent(self):\\n return self.parent\",\n \"def get_comments_by_parent_genus_type(self, comment_genus_type):\\n # Implemented from template for\\n # osid.resource.ResourceLookupSession.get_resources_by_parent_genus_type\\n # STILL NEED TO IMPLEMENT!!!\\n return objects.CommentList([])\",\n \"def get_parent(self):\\n return self.__parent\",\n \"def get_parent(self):\\n return self.__parent\",\n \"def getParent():\",\n \"def parent(self):\\n return None\",\n \"def parent(self):\\n return None\",\n \"def parent(self):\\n return None\",\n \"def parent(self):\\n return None\",\n \"def getParent(obj):\",\n \"def get_parent(self):\\n return self._parent\",\n \"def parent(self):\\n\\t\\treturn self._parent\",\n \"def parent(self):\\n return self.get_parent().specific\",\n \"def parent(self, node):\\r\\n return self.find_node(node).parent.content\",\n \"def comment(self, comment_id):\\r\\n return RepoCommitsComment(self.parent, comment_id)\",\n \"def modify_comment_tree(self, comment_tree):\\n return comment_tree\",\n \"def find_parent(self):\\n pass\",\n \"def parent(self):\\r\\n return self._parent\",\n \"def get_parent(self):\\n if self.parent:\\n return self.parent()\\n else:\\n return None\",\n \"def parent(self):\\n \\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._parent\",\n \"def parent(self):\\n return self._collection.parent(self)\",\n \"def parent(self, n):\\n return n._parent\",\n \"def comments(self):\\r\\n return Comments(self)\",\n \"def comments(self):\\r\\n return Comments(self)\",\n \"def comments(self):\\r\\n return Comments(self)\",\n \"def parent(self):\\n if self._parent is not None:\\n return self._parent()\\n else:\\n return None\",\n \"def getParents(obj):\",\n \"def parent(self):\\n address = self.parent_address\\n try:\\n parent = Page.objects.get(address=address)\\n except Page.DoesNotExist:\\n parent = None\\n\\n return parent\",\n \"def parent(self) -> Union[\\\"ExpressionNode\\\", None]:\\n return self.__parent\",\n \"def get_comment_url(content_object, parent=None):\\r\\n kwargs = get_contenttype_kwargs(content_object)\\r\\n if parent:\\r\\n if not isinstance(parent, ThreadedComment):\\r\\n raise template.TemplateSyntaxError, \\\"get_comment_url requires its parent object to be of type ThreadedComment\\\"\\r\\n kwargs.update({'parent_id' : getattr(parent, 'pk', getattr(parent, 'id'))})\\r\\n return reverse('tc_comment_parent', kwargs=kwargs)\\r\\n else:\\r\\n return reverse('tc_comment', kwargs=kwargs)\",\n \"def parent(self):\\n if self.__parent is None:\\n return None\\n parent = self.__parent()\\n if parent is None:\\n self.__parent = parent\\n return parent\",\n \"def _get_parent_record(self) -> Link:\\n rel = \\\"parent\\\"\\n href = self.api_endpoint\\n return Link(href=href, rel=rel)\",\n \"def get_parent(self):\\n return BinaryNode.or_none(self.parent)\",\n \"def get_post_comments_recur(comment, comments, parent_comment_id, parent_post_id):\\n if 'data' in comment:\\n comment_data = comment['data']\\n\\n new_comment = None\\n\\n # a new comment exists at this layer, add it to the total list of comments\\n if 'body' in comment_data:\\n new_comment = {\\n \\\"score\\\": comment_data['score'],\\n \\\"body\\\": comment_data['body'],\\n \\\"subreddit\\\": comment_data['subreddit'],\\n \\\"author\\\": comment_data['author'],\\n \\\"parent_comment_id\\\": parent_comment_id,\\n \\\"parent_post_id\\\": parent_post_id,\\n \\\"created\\\": comment_data['created'],\\n \\\"comment_id\\\": comment_data['id']\\n }\\n comments.append(new_comment)\\n\\n next_parent_comment_id = parent_comment_id if new_comment is None else new_comment['comment_id']\\n\\n # recurse on children\\n if 'children' in comment_data:\\n for child in comment_data['children']:\\n comments = get_post_comments_recur(child, comments, next_parent_comment_id, parent_post_id)\\n\\n # recurse on replies\\n if 'replies' in comment_data:\\n comments = get_post_comments_recur(comment_data['replies'], comments, next_parent_comment_id, parent_post_id)\\n\\n return comments\",\n \"def parent(self) -> Optional[DictionaryObject]:\\n return self.get(\\\"/Parent\\\")\",\n \"async def get_comments_tree(request):\\n\\n comment_id = request.match_info.get('comment_id')\\n if comment_id:\\n # valitation was in route (\\\\d+)\\n comment_id = int(comment_id)\\n tree = CommentsTreeDAO.create_by_parent(comment_id)\\n\\n else:\\n entity_type = request.match_info.get('entity_type')\\n if not entity_type:\\n return web.HTTPBadRequest(reason=\\\"Entity params error!\\\")\\n # valitation was in route (\\\\d+)\\n entity_id = int(request.match_info.get('entity_id'))\\n tree = CommentsTreeDAO.create_by_entity(entity_type, entity_id)\\n\\n await tree.fetch(request['conn'])\\n\\n return web.json_response(await tree.rows)\",\n \"def get_parent(self):\\n return self.lodgeit.get_paste_by_id(self.parent_id)\",\n \"def comments(self):\\r\\n return c.Comments(self)\",\n \"def comments(self):\\r\\n return c.Comments(self)\",\n \"def comments(self):\\r\\n return c.Comments(self)\",\n \"def parent(self):\\r\\n if not self._meta.parent:\\r\\n return None\\r\\n\\r\\n if not self.__parent__:\\r\\n self.__parent__ = self._meta.parent()\\r\\n\\r\\n return self.__parent__\",\n \"def generate_discreet_comment_tree(tribe):\\n\\n p1 = generate_random_post(tribe, user=get_random_user())\\n p2 = generate_random_post(tribe, user=get_random_user(), parent_comment=p1)\\n p3 = generate_random_post(tribe, user=get_random_user(), parent_comment=p1)\\n p4 = generate_random_post(tribe, user=get_random_user())\\n p5 = generate_random_post(tribe, user=get_random_user(), parent_comment=p4)\\n p6 = generate_random_post(tribe, user=get_random_user(), parent_comment=p5)\\n\\n posts = [p1, p2, p3, p4, p5, p6]\\n for post in posts:\\n post.save()\\n\\n return posts\",\n \"def _get_comment_order(self):\\n\\n comment_tuples = CommentOrdererBase.get_comment_order(self)\\n if not comment_tuples:\\n return comment_tuples\\n elif isinstance(comment_tuples[-1], MissingChildrenTuple):\\n missing_children_tuple = comment_tuples.pop()\\n else:\\n missing_children_tuple = None\\n\\n special_responder_ids = self.link.responder_ids\\n\\n # unfortunately we need to look up all the Comments for QA\\n comment_ids = {ct.comment_id for ct in comment_tuples}\\n comments_by_id = Comment._byID(comment_ids, data=True)\\n\\n # figure out which comments will be kept (all others are discarded)\\n kept_comment_ids = set()\\n for comment_tuple in comment_tuples:\\n if comment_tuple.depth == 0:\\n kept_comment_ids.add(comment_tuple.comment_id)\\n continue\\n\\n comment = comments_by_id[comment_tuple.comment_id]\\n parent = comments_by_id[comment.parent_id] if comment.parent_id else None\\n\\n if comment.author_id in special_responder_ids:\\n kept_comment_ids.add(comment_tuple.comment_id)\\n continue\\n\\n if parent and parent.author_id in special_responder_ids:\\n kept_comment_ids.add(comment_tuple.comment_id)\\n continue\\n\\n if hasattr(comment, \\\"distinguished\\\") and comment.distinguished != \\\"no\\\":\\n kept_comment_ids.add(comment_tuple.comment_id)\\n continue\\n\\n # add all ancestors to kept_comment_ids\\n for comment_id in sorted(kept_comment_ids):\\n # sort the comments so we start with the most root level comments\\n comment = comments_by_id[comment_id]\\n parent_id = comment.parent_id\\n\\n counter = 0\\n while (parent_id and\\n parent_id not in kept_comment_ids and\\n counter < g.max_comment_parent_walk):\\n kept_comment_ids.add(parent_id)\\n counter += 1\\n\\n comment = comments_by_id[parent_id]\\n parent_id = comment.parent_id\\n\\n # remove all comment tuples that aren't in kept_comment_ids\\n comment_tuples = [comment_tuple for comment_tuple in comment_tuples\\n if comment_tuple.comment_id in kept_comment_ids\\n ]\\n\\n if missing_children_tuple:\\n comment_tuples.append(missing_children_tuple)\\n\\n return comment_tuples\",\n \"def get_tree_json(self):\\n title = self.name\\n if self.abbreviation:\\n title = title + '(' + self.abbreviation + ')'\\n result = {\\\"title\\\": title,\\n \\\"key\\\": self.pk,\\n \\\"tooltip\\\": self.description,\\n \\\"extraClasses\\\": 'tag',\\n \\\"lazy\\\": True,\\n \\\"data\\\": {\\\"parentId\\\": None,\\n \\\"name\\\": self.name,\\n \\\"abbreviation\\\": self.abbreviation,\\n \\\"description\\\": self.description\\n }\\n }\\n parent = self.get_parent()\\n if parent:\\n result['data']['parentId'] = parent.pk\\n return result\",\n \"def parent(self):\\n return getattr(self, \\\"parent_%s\\\" % self.discriminator)\",\n \"def parent(self):\\n return self if self.is_root else self.__parent\",\n \"def get_queryset(self, *args, **kwargs):\\n return CommentQuerySet(self.model, using=self._db).order_by(\\n self.tree_id_attr,\\n self.left_attr\\n )\",\n \"def comments(self):\\r\\n return comments.Comments(self)\",\n \"def parent(self):\\n raise NotImplemented\",\n \"def get_parent():\\n\\n data = list(request.files.values())[0].file.read() if len(request.files) else request.body.read()\\n return getParentView(data, request.params)\",\n \"def make_comment_data(self, comment_id, parent_id=None, children=[]): # pylint: disable=W0102\\n return make_minimal_cs_comment({\\n \\\"id\\\": comment_id,\\n \\\"parent_id\\\": parent_id,\\n \\\"course_id\\\": str(self.course.id),\\n \\\"thread_id\\\": self.thread_id,\\n \\\"thread_type\\\": \\\"discussion\\\",\\n \\\"username\\\": self.user.username,\\n \\\"user_id\\\": str(self.user.id),\\n \\\"created_at\\\": \\\"2015-06-03T00:00:00Z\\\",\\n \\\"updated_at\\\": \\\"2015-06-03T00:00:00Z\\\",\\n \\\"body\\\": \\\"Original body\\\",\\n \\\"children\\\": children,\\n })\",\n \"def parent_model(self):\\n return self.prop.parent.class_\",\n \"def get_parent(self):\\n if not self._parent:\\n self._parent = yield self.parent_resource.get(self.parent_id)\\n\\n raise Return(self._parent)\",\n \"def parent(self):\\n other = self\\n while True:\\n for rev in other._hgmo['parents']:\\n parent = Push(rev)\\n if parent.id != self.id:\\n return parent\\n other = parent\",\n \"def get_parent_model(self):\\n return self._model\",\n \"def get_comment_model(self):\\n return get_model()\",\n \"def GetParent(self):\\n return self.parent\",\n \"def get_question(self):\\n if self.is_question:\\n return self\\n elif self.is_answer or self.is_comment and self.parent.is_question:\\n return self.parent\\n elif self.is_comment and self.parent.is_answer:\\n return self.parent.parent\\n raise IntegrityError('Content object {} is orphan.'.format(self.pk))\",\n \"def parent(self) -> Optional[Heirarchical]:\\n return None\",\n \"def get_parents(self):\\n return self.parents\",\n \"def child_comments_in_order(self):\\n return self.order_by(\\\"created_at\\\").select_related(\\\"user\\\")\",\n \"def parent(self, p):\\n node = self._validate(p)\\n return self._make_position(node._parent)\",\n \"def get_outer(self):\\n return self.parent\",\n \"def parent_document(cls):\\n return cls.parent_resources()[0]\",\n \"def comments(self):\\r\\n return GistComments(self)\",\n \"def test_post_matches_parent_when_parent_is_comment(self):\\n post = create_a_post()\\n parent = Comment.create(body=\\\"I'm a parent comment\\\", post=post)\\n comment = Comment.create(body=\\\"I'm a child comment\\\", parent=parent)\\n self.assertIs(comment.post, parent.post)\",\n \"def get_parent(self):\\n return self._find_by_locator().parent\",\n \"def get_comment_url_json(content_object, parent=None):\\r\\n try:\\r\\n return get_comment_url_ajax(content_object, parent, ajax_type=\\\"json\\\")\\r\\n except template.TemplateSyntaxError:\\r\\n raise template.TemplateSyntaxError, \\\"get_comment_url_json requires its parent object to be of type ThreadedComment\\\"\\r\\n return ''\",\n \"def get_comment(self, object_id):\\n return self.get_object(\\\"comment\\\", object_id)\",\n \"def __str__(self):\\n\\t\\treturn str(self.__parent)\",\n \"def comments(self):\\n return comments.Comments(self)\",\n \"def outer(self):\\n if self.parent is not None:\\n self.parent.lines += self.lines\\n # print (f\\\"{self.name} -> {self.parent.name}\\\")\\n return self.parent\",\n \"def GetParent(self):\\r\\n\\r\\n return self._parent\",\n \"def parent(self):\\n raise NotImplementedError()\",\n \"def parent(self):\\n return self.key().parent()\",\n \"def parentItem(self):\\n return None\",\n \"def viewer(self):\\n return self.parent\",\n \"def parent(self, parent_object):\\n lookup = get_parent_lookup_kwargs(parent_object)\\n return self.filter(**lookup)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69411963","0.67797315","0.6721547","0.66233695","0.65036964","0.64508355","0.63603806","0.63551664","0.6318134","0.6311694","0.6311694","0.6311694","0.6236535","0.6184287","0.6184287","0.61701477","0.6166827","0.6166827","0.6166827","0.6166827","0.6165333","0.6122415","0.6119646","0.6116784","0.6099386","0.60552555","0.6053595","0.60477865","0.60151964","0.60133815","0.60016525","0.59930086","0.59930086","0.59930086","0.59930086","0.59930086","0.59930086","0.59930086","0.59930086","0.59930086","0.59930086","0.59930086","0.599175","0.5979098","0.59737754","0.59737754","0.59737754","0.59599745","0.594734","0.5923973","0.5920671","0.5917566","0.59098625","0.5889549","0.58767724","0.58754504","0.58668315","0.585592","0.5855254","0.5849559","0.5849559","0.5849559","0.5841959","0.5820543","0.58045244","0.5804151","0.5803902","0.57974595","0.5776215","0.5773311","0.5760429","0.57603866","0.57519686","0.57499284","0.5742533","0.57390153","0.57383746","0.57308424","0.57247543","0.5722535","0.5707429","0.5698502","0.5689061","0.56888366","0.5669979","0.5655717","0.5651006","0.5646798","0.5645619","0.56276083","0.5614676","0.5612813","0.561213","0.5603199","0.5601433","0.5587246","0.558158","0.5578278","0.5578196","0.5578142"],"string":"[\n \"0.69411963\",\n \"0.67797315\",\n \"0.6721547\",\n \"0.66233695\",\n \"0.65036964\",\n \"0.64508355\",\n \"0.63603806\",\n \"0.63551664\",\n \"0.6318134\",\n \"0.6311694\",\n \"0.6311694\",\n \"0.6311694\",\n \"0.6236535\",\n \"0.6184287\",\n \"0.6184287\",\n \"0.61701477\",\n \"0.6166827\",\n \"0.6166827\",\n \"0.6166827\",\n \"0.6166827\",\n \"0.6165333\",\n \"0.6122415\",\n \"0.6119646\",\n \"0.6116784\",\n \"0.6099386\",\n \"0.60552555\",\n \"0.6053595\",\n \"0.60477865\",\n \"0.60151964\",\n \"0.60133815\",\n \"0.60016525\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.59930086\",\n \"0.599175\",\n \"0.5979098\",\n \"0.59737754\",\n \"0.59737754\",\n \"0.59737754\",\n \"0.59599745\",\n \"0.594734\",\n \"0.5923973\",\n \"0.5920671\",\n \"0.5917566\",\n \"0.59098625\",\n \"0.5889549\",\n \"0.58767724\",\n \"0.58754504\",\n \"0.58668315\",\n \"0.585592\",\n \"0.5855254\",\n \"0.5849559\",\n \"0.5849559\",\n \"0.5849559\",\n \"0.5841959\",\n \"0.5820543\",\n \"0.58045244\",\n \"0.5804151\",\n \"0.5803902\",\n \"0.57974595\",\n \"0.5776215\",\n \"0.5773311\",\n \"0.5760429\",\n \"0.57603866\",\n \"0.57519686\",\n \"0.57499284\",\n \"0.5742533\",\n \"0.57390153\",\n \"0.57383746\",\n \"0.57308424\",\n \"0.57247543\",\n \"0.5722535\",\n \"0.5707429\",\n \"0.5698502\",\n \"0.5689061\",\n \"0.56888366\",\n \"0.5669979\",\n \"0.5655717\",\n \"0.5651006\",\n \"0.5646798\",\n \"0.5645619\",\n \"0.56276083\",\n \"0.5614676\",\n \"0.5612813\",\n \"0.561213\",\n \"0.5603199\",\n \"0.5601433\",\n \"0.5587246\",\n \"0.558158\",\n \"0.5578278\",\n \"0.5578196\",\n \"0.5578142\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5738746"},"document_rank":{"kind":"string","value":"76"}}},{"rowIdx":1396,"cells":{"query":{"kind":"string","value":"Interpret and store the decoded json dictionary from the handshake header file. Start an empty data tracking dictionary, according to data_labels."},"document":{"kind":"string","value":"def __init__(self, sock, header_dict):\n super().__init__(header_dict)\n self.sock = sock"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _read_header(\n self, header, filename, run_check_acceptability=True, background_lsts=True\n ):\n # get telescope information\n latitude = header[\"latitude\"][()]\n longitude = header[\"longitude\"][()]\n altitude = header[\"altitude\"][()]\n self.telescope_location_lat_lon_alt_degrees = (latitude, longitude, altitude)\n self.instrument = header[\"instrument\"][()].tobytes().decode(\"utf8\")\n self.telescope_name = header[\"telescope_name\"][()].tobytes().decode(\"utf8\")\n\n # get source information\n self.object_name = header[\"object_name\"][()].tobytes().decode(\"utf8\")\n\n # set history appropriately\n self.history = header[\"history\"][()].tobytes().decode(\"utf8\")\n if not uvutils._check_history_version(self.history, self.pyuvdata_version_str):\n self.history += self.pyuvdata_version_str\n\n # check for vis_units\n if \"vis_units\" in header:\n self.vis_units = header[\"vis_units\"][()].tobytes().decode(\"utf8\")\n else:\n # default to uncalibrated data\n self.vis_units = \"UNCALIB\"\n\n # check for optional values\n if \"dut1\" in header:\n self.dut1 = float(header[\"dut1\"][()])\n if \"earth_omega\" in header:\n self.earth_omega = float(header[\"earth_omega\"][()])\n if \"gst0\" in header:\n self.gst0 = float(header[\"gst0\"][()])\n if \"rdate\" in header:\n self.rdate = header[\"rdate\"][()].tobytes().decode(\"utf8\")\n if \"timesys\" in header:\n self.timesys = header[\"timesys\"][()].tobytes().decode(\"utf8\")\n if \"x_orientation\" in header:\n self.x_orientation = header[\"x_orientation\"][()].tobytes().decode(\"utf8\")\n if \"blt_order\" in header:\n blt_order_str = header[\"blt_order\"][()].tobytes().decode(\"utf8\")\n self.blt_order = tuple(blt_order_str.split(\", \"))\n if self.blt_order == (\"bda\",):\n self._blt_order.form = (1,)\n\n if \"antenna_diameters\" in header:\n self.antenna_diameters = header[\"antenna_diameters\"][()]\n if \"uvplane_reference_time\" in header:\n self.uvplane_reference_time = int(header[\"uvplane_reference_time\"][()])\n if \"eq_coeffs\" in header:\n self.eq_coeffs = header[\"eq_coeffs\"][()]\n if \"eq_coeffs_convention\" in header:\n self.eq_coeffs_convention = (\n header[\"eq_coeffs_convention\"][()].tobytes().decode(\"utf8\")\n )\n\n # check for phasing information\n self.phase_type = header[\"phase_type\"][()].tobytes().decode(\"utf8\")\n if self.phase_type == \"phased\":\n self._set_phased()\n self.phase_center_ra = float(header[\"phase_center_ra\"][()])\n self.phase_center_dec = float(header[\"phase_center_dec\"][()])\n self.phase_center_epoch = float(header[\"phase_center_epoch\"][()])\n if \"phase_center_frame\" in header:\n self.phase_center_frame = (\n header[\"phase_center_frame\"][()].tobytes().decode(\"utf8\")\n )\n elif self.phase_type == \"drift\":\n self._set_drift()\n else:\n self._set_unknown_phase_type()\n\n # get antenna arrays\n # cast to native python int type\n self.Nants_data = int(header[\"Nants_data\"][()])\n self.Nants_telescope = int(header[\"Nants_telescope\"][()])\n self.ant_1_array = header[\"ant_1_array\"][:]\n self.ant_2_array = header[\"ant_2_array\"][:]\n self.antenna_names = [\n n.tobytes().decode(\"utf8\") for n in header[\"antenna_names\"][:]\n ]\n self.antenna_numbers = header[\"antenna_numbers\"][:]\n self.antenna_positions = header[\"antenna_positions\"][:]\n\n # set telescope params\n try:\n self.set_telescope_params()\n except ValueError as ve:\n warnings.warn(str(ve))\n\n # get baseline array\n self.baseline_array = self.antnums_to_baseline(\n self.ant_1_array, self.ant_2_array\n )\n self.Nbls = len(np.unique(self.baseline_array))\n\n # get uvw array\n self.uvw_array = header[\"uvw_array\"][:, :]\n\n # get time information\n self.time_array = header[\"time_array\"][:]\n integration_time = header[\"integration_time\"]\n self.integration_time = integration_time[:]\n proc = None\n if \"lst_array\" in header:\n self.lst_array = header[\"lst_array\"][:]\n # check that lst_array in file is self-consistent\n if run_check_acceptability:\n (\n latitude,\n longitude,\n altitude,\n ) = self.telescope_location_lat_lon_alt_degrees\n lst_array = uvutils.get_lst_for_time(\n self.time_array, latitude, longitude, altitude\n )\n if not np.all(\n np.isclose(\n self.lst_array,\n lst_array,\n rtol=self._lst_array.tols[0],\n atol=self._lst_array.tols[1],\n )\n ):\n warnings.warn(\n \"LST values stored in {file} are not self-consistent \"\n \"with time_array and telescope location. Consider \"\n \"recomputing with utils.get_lst_for_time.\".format(file=filename)\n )\n else:\n # compute lst_array from time_array and telescope location\n proc = self.set_lsts_from_time_array(background=background_lsts)\n\n # get frequency information\n self.freq_array = header[\"freq_array\"][:, :]\n self.channel_width = float(header[\"channel_width\"][()])\n self.spw_array = header[\"spw_array\"][:]\n\n # get polarization information\n self.polarization_array = header[\"polarization_array\"][:]\n\n # get data shapes\n self.Nfreqs = int(header[\"Nfreqs\"][()])\n self.Npols = int(header[\"Npols\"][()])\n self.Ntimes = int(header[\"Ntimes\"][()])\n self.Nblts = int(header[\"Nblts\"][()])\n self.Nspws = int(header[\"Nspws\"][()])\n\n # get extra_keywords\n if \"extra_keywords\" in header:\n self.extra_keywords = {}\n for key in header[\"extra_keywords\"].keys():\n if header[\"extra_keywords\"][key].dtype.type in (np.string_, np.object_):\n self.extra_keywords[key] = (\n header[\"extra_keywords\"][key][()].tobytes().decode(\"utf8\")\n )\n else:\n self.extra_keywords[key] = header[\"extra_keywords\"][key][()]\n\n if proc is not None:\n # if lsts are in the background wait for them to return\n proc.join()\n\n return","def _main_header(self, hdr):\n d = {}\n # Called readDefAnalysis in OpenMIMS\n d['sample type'], d['data included'], d['sample x'], d['sample y'], \\\n d['analysis type'], d['user name'], d['sample z'], date, time = \\\n unpack(self._bo + '4i 32s 16s i 12x 16s 16s', hdr.read(112))\n\n d['data included'] = bool(d['data included'])\n d['user name'] = self._cleanup_string(d['user name'])\n d['analysis type'] = self._cleanup_string(d['analysis type']).lower()\n date = self._cleanup_string(date)\n time = self._cleanup_string(time)\n d['date'] = self._cleanup_date(date + ' ' + time)\n\n if self.header['file type'] in (27, 29, 39):\n # Called MaskImage/readMaskIm in OpenMIMS\n d['original filename'], d['analysis duration'], d['frames'], \\\n d['scan type'], d['magnification'], d['size type'], \\\n d['size detector'], d['beam blanking'], d['presputtering'], \\\n d['presputtering duration'] = \\\n unpack(self._bo + '16s 3i 3h 2x 3i', hdr.read(48))\n\n d['AutoCal'] = self._autocal(hdr)\n d['HVControl'] = {}\n d['HVControl']['hvcontrol enabled'] = False\n\n elif self.header['file type'] in (22, 41):\n # Called MaskSampleStageImage/readMaskIss in OpenMIMS\n d['original filename'], d['analysis duration'], d['scan type'], \\\n d['steps'], d['step size x'], d['step size y'], d['step size?'], \\\n d['step waittime'], d['frames'], d['beam blanking'], \\\n d['presputtering'], d['presputtering duration'] = \\\n unpack(self._bo + '16s 6i d 4i', hdr.read(64))\n\n d['scan type'] = _stage_scan_types.get(d['scan type'], str(d['scan type']))\n\n d['AutoCal'] = self._autocal(hdr)\n d['HVControl'] = self._hvcontrol(hdr)\n # Don't know if this unused byte needs to go after HVControl or after SigRef.\n hdr.seek(4, 1)\n\n elif self.header['file type'] in (21, 26):\n # Not in OpenMIMS\n # this bit same as image, 1 extra unused/unknown\n d['original filename'], d['analysis duration'], d['frames'], \\\n d['scan type'], d['magnification'], d['size type'], \\\n d['size detector'], d['beam blanking'], d['presputtering'], \\\n d['presputtering duration'] = \\\n unpack(self._bo + '16s 4x 3i 3h 2x 3i', hdr.read(52))\n\n # this bit same as stage scan\n d['AutoCal'] = self._autocal(hdr)\n d['HVControl'] = self._hvcontrol(hdr)\n\n # 24 bytes unknown, not sure if they go here or before AutoCal\n hdr.seek(24, 1)\n\n elif self.header['file type'] == 31:\n # Don't know if this is correct, all 0s anyway\n d['original filename'], d['scan type'], \\\n d['beam blanking'], d['presputtering'] = \\\n unpack(self._bo + '16s 3i 4x', hdr.read(32))\n\n elif self.header['file type'] == 35:\n d['original filename'], d['scan type'], d['analysis duration'], \\\n d['frames'], d['beam blanking'], d['presputtering'] = \\\n unpack(self._bo + '16s 5i 40x', hdr.read(76))\n\n d['AutoCal'] = self._autocal(hdr)\n d['HVControl'] = self._hvcontrol(hdr)\n\n else:\n raise TypeError('What type of image are you? {}'.format(self.header['file type']))\n\n # Continue main header for all types\n d['SigRef'] = self._sigref(hdr)\n d['masses'] = unpack(self._bo + 'i', hdr.read(4))[0]\n\n # scan type is set for stage scan analysis, set others\n if isinstance(d['scan type'], int):\n if d['scan type'] == 0:\n d['scan type'] = ''\n else:\n d['scan type'] = str(d['scan type'])\n\n d['beam blanking'] = bool(d['beam blanking'])\n d['presputtering'] = bool(d['presputtering'])\n d['original filename'] = self._cleanup_string(d['original filename'])\n\n if self.header['file type'] in (21, 26, 27, 29, 35, 39):\n if self.header['file version'] >= 4108:\n n = 60\n else:\n n = 10\n elif self.header['file type'] in (22, 31, 40, 41):\n n = 20\n else:\n n = 0\n\n # Not sure what this is, memory pointers? Not needed.\n # d['mass table ptr'] = unpack(self._bo + 2*n*'h', hdr.read(n*4))\n hdr.seek(n*4, 1)\n\n if self.header['file type'] in (21, 22, 26, 40, 41, 35):\n hdr.seek(4, 1) # 4 bytes unused\n\n # Mass table, dict by species label.\n d['MassTable'] = collections.OrderedDict()\n for m in range(d['masses']):\n mi = {}\n mi['trolley index'], unknown, mi['mass'], mi['matrix or trace'], \\\n mi['detector'], mi['wait time'], mi['frame count time'] = \\\n unpack(self._bo + '2i d 2i 2d', hdr.read(40))\n\n if self.header['file type'] == 31:\n if d['analysis type'].endswith('trolley step scan'):\n # start and end are in mm, step is in μm; convert to mm\n mi['radius start'], mi['radius end'], \\\n mi['radius step'], mi['b field bits'] = \\\n unpack(self._bo + '3d i', hdr.read(28))\n mi['radius step'] /= 1000\n else:\n mi['voltage start'], mi['voltage end'], \\\n mi['voltage step'], mi['b field bits'] = \\\n unpack(self._bo + '3d i', hdr.read(28))\n else:\n mi['offset'], mi['b field bits'] = unpack(self._bo + '2i', hdr.read(8))\n\n mi.update(self._species(hdr))\n\n if self.header['file type'] == 31:\n hdr.seek(4, 1)\n\n # Add correction controls, my own addition.\n mi['background corrected'] = False\n mi['deadtime corrected'] = False\n mi['yield corrected'] = False\n\n label = mi.pop('label')\n # This is true for NS50L and file version 4108.\n # Anywhere else different?\n # Maybe confirm this with the Trolleys dict,\n # there is an Esi trolley.\n if mi['trolley index'] == 8:\n label = 'SE'\n\n d['MassTable'][label] = mi\n\n # Create a few convenient lists\n d['label list'] = tuple(d['MassTable'].keys())\n d['label list fmt'] = tuple(format_species(m) for m in d['label list'])\n d['mass list'] = tuple(d['MassTable'][m]['mass'] for m in d['label list'])\n\n return d","def _read_data(self) -> None:\n raw_data = self.__mmap[:].decode('ascii').rstrip('\\0')\n self.__data = json.loads(raw_data)","def _parseData(self, payload):\n out=[]\n bytesParsed = 0\n while bytesParsed < len(payload):\n\n #check for the extended Code Level, code and length\n #count the number of EXCODE_BYTE\n #extendedCodeLevel = sum([1 for x in data if x == EXCODE_BYTE] )\n #bytesParsed += extendedCodeLevel\n\n #identify the length of the expected bytes in the payload\n code = payload[bytesParsed]\n bytesParsed +=1\n if code > 0x7F:\n # multi-byte code, length > 1\n length = payload[bytesParsed]\n bytesParsed +=1\n else:\n length = 1\n\n if code == SENSOR_STATUS:\n # value of 0==no contact, 200==contact\n #print \"leadoff: %i\" % payload[bytesParsed]\n out.append( {'timestamp': self.curtime, 'leadoff': payload[bytesParsed] } )\n bytesParsed +=1\n\n elif code == HEART_RATE:\n #print \"HR: %i\" % payload[bytesParsed]\n out.append( {'timestamp': self.curtime, 'HR': payload[bytesParsed:] } )\n bytesParsed +=1\n\n elif code == CONFIG_BYTE:\n #print \"config: %i\" % payload[bytesParsed]\n out.append( {'timestamp': self.curtime, 'config': payload[bytesParsed:] } )\n bytesParsed +=1\n\n elif code == RAW_ECG:\n # raw value is between -32768 and 32767, in twos compliment form\n # if the raw value is higher than 32768, it should be rolled around to allow for negative values\n raw = payload[bytesParsed]*256 + payload[bytesParsed]\n if raw >= 32768: \n raw = raw - 65536\n #print \"ecg: %i\" % ecg\n\n # create the timestamp on each ECG sample, starting from the first\n if self.starttime is None:\n self.starttime = time.time()\n self.curtime = self.starttime\n else:\n self.curtime = self.curtime + 1./self.Fs\n\n out.append( {'timestamp': self.curtime, 'ecg_raw': raw } )\n bytesParsed += length\n\n elif code == DEBUG_1:\n #print \"debug1: \" + str(payload[bytesParsed:]).strip('[]')\n out.append( {'timestamp': self.curtime, 'debug1': payload[bytesParsed:] } )\n bytesParsed += length\n\n elif code == DEBUG_2:\n #print \"debug2: \" + str(payload[bytesParsed:]).strip('[]')\n out.append( {'timestamp': self.curtime, 'debug2': payload[bytesParsed:] } )\n bytesParsed += length\n\n else:\n print \"unknown code: %i\" % code\n\n return out","def parse_data(self, frame, header_structure):\n raise NotImplementedError()","def read_metadata_record(raw_features_string):\n full_metadata = json.loads(raw_features_string)\n return {\"sha256\": full_metadata[\"sha256\"], \"appeared\": full_metadata[\"appeared\"], \"label\": full_metadata[\"label\"]}","def record() -> Dict[str, int]:\n data: Dict[str, List[str]] = json.loads(request.json)\n\n mac: str = data['mac']\n letters: List[str] = data['keys_pressed']\n\n if not Path(f'.{os.sep}data').exists():\n Path(f'.{os.sep}data').mkdir()\n\n data_file: str = \"data/keylog.json\"\n if os.path.exists(data_file):\n with open(data_file, \"r\") as fp:\n data = json.load(fp)\n else:\n data = {}\n\n previous_string: str = ''\n if mac in data.keys():\n previous_string = data[mac]['string']\n\n previous_string += process_key_string(letters)\n data[mac] = {}\n data[mac][\"string\"] = previous_string\n data[mac][\"frequency_map\"] = generate_frequency_map(previous_string)\n\n with open(data_file, \"w+\") as fp:\n json.dump(data, fp)\n\n return {\"response\": 0}","def _decode_next_layer(self, dict_, length=None):\n # make next layer protocol name\n proto = str(self._prot or 'Raw').lower()\n\n # make BytesIO from frame package data\n bytes_ = io.BytesIO(self._file.read(dict_['len']))\n info, protochain = self._import_next_layer(bytes_, length)\n\n # write info and protocol chain into dict\n self._protos = ProtoChain(self._prot, protochain)\n dict_[proto] = info\n dict_['protocols'] = self._protos.chain\n return dict_","def parse_handshake(self, data):\n\n if (data[0] != len(PSTR) or data[1:20] != PSTR\n or data[28:48] != self.factory.torrent.info_hash):\n\n self.transport.loseConnection()\n else:\n self.handshaked = True\n\n reserved = data[20:28]\n if reserved[7] & ord('\\x04'):\n self.fast_extension = True\n\n if reserved[7] & ord('\\x01'):\n self.dht = True","def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\n super().__init__(header, raw_data)\n self.status, *self.values = unpack_from(f'<{self.header.params_count}I', raw_data)","def load_data_file(self):\n with open(self.files['data'], 'r') as infile:\n data = json.load(infile)\n self.boundary_nodes = data['boundary_nodes']\n self.nodes = {int(k): v for k, v in data['nodes'].items()}\n self.levels = data['levels']\n infile.close()","def deserialise_hs01(buffer):\n check_schema_identifier(buffer, FILE_IDENTIFIER)\n event_hist = EventHistogram.EventHistogram.GetRootAsEventHistogram(buffer, 0)\n\n dims = []\n for i in range(event_hist.DimMetadataLength()):\n bins_fb = _create_array_object_for_type(\n event_hist.DimMetadata(i).BinBoundariesType()\n )\n\n # Get bins\n bins_offset = event_hist.DimMetadata(i).BinBoundaries()\n bins_fb.Init(bins_offset.Bytes, bins_offset.Pos)\n bin_boundaries = bins_fb.ValueAsNumpy()\n\n hist_info = {\n \"length\": event_hist.DimMetadata(i).Length(),\n \"bin_boundaries\": bin_boundaries,\n \"unit\": event_hist.DimMetadata(i).Unit().decode(\"utf-8\")\n if event_hist.DimMetadata(i).Unit()\n else \"\",\n \"label\": event_hist.DimMetadata(i).Label().decode(\"utf-8\")\n if event_hist.DimMetadata(i).Label()\n else \"\",\n }\n dims.append(hist_info)\n\n metadata_timestamp = event_hist.LastMetadataTimestamp()\n\n data_fb = _create_array_object_for_type(event_hist.DataType())\n data_offset = event_hist.Data()\n data_fb.Init(data_offset.Bytes, data_offset.Pos)\n shape = event_hist.CurrentShapeAsNumpy().tolist()\n data = data_fb.ValueAsNumpy().reshape(shape)\n\n # Get the errors\n errors_offset = event_hist.Errors()\n if errors_offset:\n errors_fb = _create_array_object_for_type(event_hist.ErrorsType())\n errors_fb.Init(errors_offset.Bytes, errors_offset.Pos)\n errors = errors_fb.ValueAsNumpy().reshape(shape)\n else:\n errors = []\n\n hist = {\n \"source\": event_hist.Source().decode(\"utf-8\") if event_hist.Source() else \"\",\n \"timestamp\": event_hist.Timestamp(),\n \"current_shape\": shape,\n \"dim_metadata\": dims,\n \"data\": data,\n \"errors\": errors,\n \"last_metadata_timestamp\": metadata_timestamp,\n \"info\": event_hist.Info().decode(\"utf-8\") if event_hist.Info() else \"\",\n }\n return hist","def load_payload(self, server_payload) -> None:","def data_dict0():\n\n # 0- Sample from detectron2 -> 5 different sections.\n info_val0 = [{\"date_created\": \"2020-03-15 04:59:45.442988\",\n \"description\": \"Automatically generated COCO json file for Detectron2.\"}]\n images0 = [{\"id\": \"image\", \"width\": 100,\n \"height\": 100, \"file_name\": \"image.png\"}]\n annotations0 = [{\"id\": 1, \"image_id\": \"image\", \"bbox\": [70.0, 30.0, 30.0, 40.0],\n \"area\": 1200.0, \"iscrowd\": 0, \"category_id\": 0}]\n categories0 = [{\"id\": 0, \"name\": \"first\"}]\n licence0 = 'null'\n\n return [{\"info\": info_val0,\n \"images\": images0,\n \"annotations\": annotations0,\n \"categories\": categories0,\n \"licenses\": licence0}]","def decode(data): #@NoSelf","def processReadback(resp):\n a = np.fromstring(resp, dtype='<u1')\n return {\n 'build': a[51],\n 'serDAC': a[56],\n 'noPllLatch': bool((a[58] & 0x80) > 0),\n 'ackoutI2C': a[61],\n 'I2Cbytes': a[69:61:-1],\n 'executionCounter': (a[53] << 8) + a[52]\n }","def _readheader(lines):\n hdrdict = {}\n #input list of 26 lines of header\n #station and channel\n line = lines[5]\n parts = line.strip().split()\n fname = parts[1]\n fparts = fname.split('_')\n hdrdict['station'] = fparts[-2]+'_'+fparts[-1]\n\n #the \"Component\" lines look like either: Component S00W, Component S90E, Component Up\n compstr = lines[12].strip().split()[1]\n hdrdict['channel'] = get_comp_name(compstr)\n\n #instrument\n hdrdict['instrument'] = lines[3].split()[1].strip()\n \n #location string\n line = lines[6]\n hdrdict['location'] = line.strip()\n #event origin, buffer start year/month\n line = lines[16]\n parts = line.strip().split()\n bufyear = int(parts[8])\n bufmonth = int(parts[9])\n #epicentral location, buffer start day/hour\n line = lines[17]\n parts = line.strip().split()\n bufday = int(parts[8])\n bufhour = int(parts[9])\n #numpoints, buffer start min/sec\n line = lines[19]\n parts = line.strip().split()\n hdrdict['npts'] = int(parts[0])\n bufmin = int(parts[8])\n millisec = int(parts[9])\n bufsec = int(millisec/1000)\n bufmicrosec = int(np.round(millisec/1000.0 - bufsec))\n hdrdict['starttime'] = UTCDateTime(datetime(bufyear,bufmonth,bufday,bufhour,bufmin,bufsec,bufmicrosec))\n #part C\n #frequency, calibration value and some other stuff we don't care about\n line = lines[20]\n parts = line.strip().split()\n hdrdict['sampling_rate'] = float(parts[0])\n hdrdict['delta'] = 1.0/hdrdict['sampling_rate']\n hdrdict['calib'] = float(parts[7])\n #site location info, this time in dd\n line = lines[21]\n parts = line.strip().split()\n hdrdict['lat'] = float(parts[0]) * -1\n hdrdict['lon'] = float(parts[1])\n hdrdict['height'] = 0.0\n #duration\n line = lines[22]\n parts = line.strip().split()\n hdrdict['duration'] = float(parts[0])\n hdrdict['endtime'] = hdrdict['starttime'] + hdrdict['duration']\n #max acceleration - good for sanity check\n line = lines[23]\n parts = line.strip().split()\n hdrdict['maxacc'] = float(parts[0])\n hdrdict['network'] = 'NZ'\n hdrdict['units'] = 'acc'\n return hdrdict","def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\n super().__init__(header, raw_data)\n self.status, self.length, *self.values = unpack_from(f'<{self.header.params_count}I', raw_data)\n self.data = raw_data[8:8 + self.length] if self.length > 0 else b''","def readHead(self):\n filesize = self.rhd.tell()\n \n #the order in which all of this is called is critcal\n self.header_identifier = hex(np.uint32(struct.unpack('<I', self.rhd.read(4))))\n v = np.int8(struct.unpack('BBBB', self.rhd.read(4)))\n\n #read each property of the header\n self.version = str(v[0]) + '.' + str(v[2])\n self.sample_rate = np.float32(struct.unpack('f', self.rhd.read(4)))[0] \n self.dsp_enabled = np.int8(struct.unpack('BB', self.rhd.read(2)))[0]\n self.actual_dsp_cutoff_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n self.actual_lower_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n self.actual_upper_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n self.desired_dsp_cutoff_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n self.desired_lower_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n self.desired_upper_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n self.notch_cutoff_mode = np.int8(struct.unpack('BB', self.rhd.read(2)))[0]\n self.desired_impedance_test_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n self.actual_impedance_test_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\n #list of 3 notes\n self.note = [_qstring(self.rhd),_qstring(self.rhd),_qstring(self.rhd)]\n self.number_of_temperature_sensors = np.int16(struct.unpack('h', self.rhd.read(2)))[0]\n self._TEMP_SENSORS = self.number_of_temperature_sensors\n self.board_mode = np.int16(struct.unpack('h', self.rhd.read(2)))[0]\n self.number_of_signal_groups = np.int16(struct.unpack('h', self.rhd.read(2)))[0]\n\n #dict of signal groups\n self.signal_groups = {} \n for i in range(self.number_of_signal_groups):\n sg = Signal_Group(self)\n self.signal_groups[sg.signal_group_name] = sg\n \n #dict of channels\n self.channels = {}\n for key, group in self.signal_groups.iteritems():\n self.channels.update(group.channels)","def test_serialises_and_deserialises_hs00_message_correctly_for_full_1d_data(self):\n original_hist = {\n \"source\": \"some_source\",\n \"timestamp\": 123456,\n \"current_shape\": [5],\n \"dim_metadata\": [\n {\n \"length\": 5,\n \"unit\": \"m\",\n \"label\": \"some_label\",\n \"bin_boundaries\": np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0]),\n }\n ],\n \"last_metadata_timestamp\": 123456,\n \"data\": np.array([1.0, 2.0, 3.0, 4.0, 5.0]),\n \"errors\": np.array([5.0, 4.0, 3.0, 2.0, 1.0]),\n \"info\": \"info_string\",\n }\n\n buf = serialise_hs00(original_hist)\n hist = deserialise_hs00(buf)\n\n assert hist[\"source\"] == original_hist[\"source\"]\n assert hist[\"timestamp\"] == original_hist[\"timestamp\"]\n assert hist[\"current_shape\"] == original_hist[\"current_shape\"]\n self._check_metadata_for_one_dimension(\n hist[\"dim_metadata\"][0], original_hist[\"dim_metadata\"][0]\n )\n assert np.array_equal(hist[\"data\"], original_hist[\"data\"])\n assert np.array_equal(hist[\"errors\"], original_hist[\"errors\"])\n assert hist[\"info\"] == original_hist[\"info\"]\n assert (\n hist[\"last_metadata_timestamp\"] == original_hist[\"last_metadata_timestamp\"]\n )","def read_metadata_record(raw_features_string):\n all_data = json.loads(raw_features_string)\n metadata_keys = {\"sha256\", \"appeared\", \"label\", \"avclass\"}\n return {k: all_data[k] for k in all_data.keys() & metadata_keys}","def test_serialises_and_deserialises_hs00_message_correctly_for_minimal_1d_data(\n self,\n ):\n original_hist = {\n \"timestamp\": 123456,\n \"current_shape\": [5],\n \"dim_metadata\": [\n {\n \"length\": 5,\n \"unit\": \"m\",\n \"label\": \"some_label\",\n \"bin_boundaries\": np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0]),\n }\n ],\n \"data\": np.array([1.0, 2.0, 3.0, 4.0, 5.0]),\n }\n buf = serialise_hs00(original_hist)\n\n hist = deserialise_hs00(buf)\n assert hist[\"source\"] == \"\"\n assert hist[\"timestamp\"] == original_hist[\"timestamp\"]\n assert hist[\"current_shape\"] == original_hist[\"current_shape\"]\n self._check_metadata_for_one_dimension(\n hist[\"dim_metadata\"][0], original_hist[\"dim_metadata\"][0]\n )\n assert np.array_equal(hist[\"data\"], original_hist[\"data\"])\n assert len(hist[\"errors\"]) == 0\n assert hist[\"info\"] == \"\"","def _read_new_header(self, raw):\n\n byte_count = 0\n\n data_size = 4\n self.label = struct.unpack('<4s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.version = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.revision = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 28\n self.date = struct.unpack('<28s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.file_format = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.file_type = struct.unpack('<4s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.original_file_name = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.reference_file_name = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.related_file_name_a = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.related_file_name_b = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.related_file_name_c = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 84\n self.annotate = struct.unpack('<84s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 36\n self.instrument_model = struct.unpack('<36s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 36\n self.instrument_serial_number = struct.unpack('<36s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 36\n self.software_version_number = struct.unpack('<36s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 36\n self.crystal_material = struct.unpack('<36s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.laser_wavelength_microns = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.laser_null_doubling = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.padding = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.dispersion_constant_xc = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.dispersion_constant_xm = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.dispersion_constant_xb = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.num_chan = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.interferogram_size = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.scan_direction = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.acquire_mode = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.emissivity = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.apodization = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.zero_fill = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.run_time_math = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.fft_size = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.number_of_coadds = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.single_sided = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.chan_display = struct.unpack('<l',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.amb_temperature = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.inst_temperature = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.wbb_temperature = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.cbb_temperature = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.temperature_dwr = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.emissivity_dwr = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 8\n self.laser_temperature = struct.unpack('<d',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 40\n self.spare_i = struct.unpack('<llllllllll',\n raw[byte_count:byte_count+data_size])\n byte_count += data_size\n\n data_size = 80\n self.spare_f = struct.unpack('<dddddddddd',\n raw[byte_count:byte_count+data_size])\n byte_count += data_size\n\n data_size = 68\n self.spare_na = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.spare_nb = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.spare_nc = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.spare_nd = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 68\n self.spare_ne = struct.unpack('<68s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.header_end = struct.unpack('<4s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size","def load_data(filename) :\n data_dict = None\n with open(filename, 'r') as infile :\n data_dict = json.load(infile)\n\n# Reset Counters\n for counter in data_dict['counters'] :\n data_dict['counters'][counter] = 0\n\n return data_dict","def process_data():\n with open('configClear_v2.json') as config:\n json_config = json.load(config)\n cisco_ios_xe_native = json_config.get('frinx-uniconfig-topology:configuration').get('Cisco-IOS-XE-native:native')\n\n config_container = {\n \"BDI\" : cisco_ios_xe_native.get('interface').get('BDI'),\n \"Loopback\" : cisco_ios_xe_native.get('interface').get('Loopback'),\n \"Port-channel\" : cisco_ios_xe_native.get('interface').get('Port-channel'),\n \"TenGigabitEthernet\" : cisco_ios_xe_native.get('interface').get('TenGigabitEthernet'),\n \"GigabitEthernet\" : cisco_ios_xe_native.get( 'interface' ).get( 'GigabitEthernet' )\n }\n\n\n with create_connection() as conn:\n for k,v in config_container.items():\n for i in v:\n cur = conn.cursor()\n cur.execute(\"\"\"\n INSERT INTO device_interface_config( name, description, config, port_channel_id, max_frame_size )\n VALUES( %s, %s, %s, %s, %s);\n \"\"\", (f\"{k}{i.get('name')}\",\n i.get('description'),\n json.dumps(i),\n i.get( 'Cisco-IOS-XE-ethernet:channel-group' ),\n i.get('mtu')\n )\n )","def get_protocol_init_data(self):\n\t\tcontents = self.archive.read_file('replay.initData')\n\t\treturn self.protocol.decode_replay_initdata(contents)","def _parse_cookie_data() -> dict:\n\n with open('Data/cookies.json') as cookie_data_file:\n cookie_data_dict = json.load(cookie_data_file)\n\n # Cast the necessary data\n for cookie_type in cookie_data_dict:\n cookie_type['weight'] = float(cookie_type['weight'])\n cookie_type['target'] = CookieHuntTarget(cookie_type['target'])\n\n return cookie_data_dict","def load(self) -> None:\n data = get_dictionary()\n if 'error' in data:\n quit()\n self.data = data","def __init__(self, data: RawData, HDDO_version: int=0,\r\n compatibility_limit: int=0):\r\n\r\n self.__data = data\r\n self.__version = HDDO_version\r\n self.__compatibility_limit = compatibility_limit\r\n self.__script = []\r\n self.__series_signature = ''\r\n self.__pha = ''\r\n self.__identity_info = {}\r\n self.__message = ''\r\n self.__is_closed = False\r\n self.__hash_base = ''\r\n self.__inner_hash = ''\r\n self.__is_transmitted = False\r\n self.__outer_hash = ''","def parse_dict(self, data):\n self.public_key = VerifyingKey(data['public_key'])\n self.signature = base58.b58decode(data['signature']) if data['signature'] else None","def decode_faceshift_datastream(self, data):\n \n #block_id = struct.unpack_from('H', data)\n #print(\"Received block id \" + str(block_id)) ;\n\n offset = 0\n block_id, version, block_size = struct.unpack_from('HHI', data, offset)\n \n #print(\"ID, v, size = \" + str(block_id) + \",\" + str(version) + \",\" + str(block_size) )\n \n offset += 8\n\n if(block_id == BLOCK_ID_TRACKING_STATE):\n n_blocks, = struct.unpack_from('H', data, offset)\n #print(\"n_blocks = \" + str(n_blocks))\n offset += 2\n\n track_ok = 0 # Will be a byte: 1 if tracking ok, 0 otherwise.\n head_rotation_quat = None # Will be filled with the rotation using mathutils.Quaternion\n blend_shape_values = [] # Will be a list of float in the range 0-1\n #eyes_values = None # Will be a sequence of 4 angle values\n markers_position = [] # Will be a list of mathutils.Vector\n \n curr_block = 0\n while(curr_block < n_blocks):\n block_id, version, block_size = struct.unpack_from('HHI', data, offset)\n #print(\"ID, v, size = \" + str(block_id) + \",\" + str(version) + \",\" + str(block_size) )\n \n # put the offset at the beginning of the block\n offset += 8\n \n if(block_id == 101): # Frame Information blobk (timestamp and tracking status)\n ts, track_ok = struct.unpack_from('dB', data, offset)\n #print(\"timestamp, track_ok \" + str(ts) + \", \" + str(track_ok) )\n #offset += 9\n elif(block_id == 102): # Pose block (head rotation and position)\n x,y,z,w = struct.unpack_from('ffff', data, offset)\n #head_rotation_quat = mathutils.Quaternion((w,x,y,z))\n elif(block_id == 103): # Blendshapes block (blendshape values)\n n_coefficients, = struct.unpack_from('I', data, offset)\n #print(\"Blend shapes count=\"+ str(n_coefficients) )\n i = 0\n coeff_list = \"\"\n while(i < n_coefficients):\n # Offset of the block, plus the 4 bytes for int n_coefficients, plus 4 bytes per float\n val, = struct.unpack_from('f', data, offset + 4 + (i*4))\n blend_shape_values.append(val)\n coeff_list += repr(val) + \" \"\n i += 1\n print(\"Values: \" + coeff_list)\n elif(block_id == 104): # Eyes block (eyes gaze)\n leye_theta, leye_phi, reye_theta, reye_phi = struct.unpack_from('ffff', data, offset)\n elif(block_id == 105): # Markers block (absolute position of mark points)\n n_markers, = struct.unpack_from('H', data, offset)\n #print(\"n markers=\"+str(n_markers))\n i = 0\n while(i < n_markers):\n # Offset of the block, plus the 2 bytes for int n_markers, plus 4 bytes for each x,y,z floats\n x, y, z = struct.unpack_from('fff', data, offset + 2 + (i*4*3))\n #print(\"m\" + str(i) + \" \" + str(x) + \"\\t\" + str(y) + \"\\t\" + str(z))\n markers_position.append(mathutils.Vector((x,y,z)))\n i += 1\n \n curr_block += 1\n offset += block_size\n \n msg = fsMsgTrackingState()\n\n msg.m_timestamp = ts\n\n self.pub.publish(msg)\n\n # end -- while on blocks. Track State scan complete","def data():\n print (\"&\")\n res = {}\n\t\n # Load Data\n with open(DATA_PATH_TRAIN, 'rb') as f:\n data = pickle.load(f)\n\t\t\n for d in data:\n for j in range(len(d)):\n if not d[j][\"addinfo\"][\"path\"] in res:\n res[d[j][\"addinfo\"][\"path\"]] = {}\n d[j][\"environment\"][\"text\"] = d[j][\"addinfo\"][\"text\"]\n res[d[j][\"addinfo\"][\"path\"]][d[j][\"addinfo\"][\"line\"]] = d[j][\"environment\"]\n\t \t\n with open(DATA_PATH_TEST, 'rb') as f:\n data = pickle.load(f)\n\t\t\n for d in data:\n for j in range(len(d)):\n if not d[j][\"addinfo\"][\"path\"] in res:\n res[d[j][\"addinfo\"][\"path\"]] = {}\n d[j][\"environment\"][\"text\"] = d[j][\"addinfo\"][\"text\"]\n res[d[j][\"addinfo\"][\"path\"]][d[j][\"addinfo\"][\"line\"]] = d[j][\"environment\"]\n\t\t\t\n with open('tasks/env/data/data.json', 'w') as outfile:\n json.dump(res, outfile)","def build_header_2_40(self):\n self.header_2 = b'\\x0e\\x00\\x00\\x00AssignmentList\\x01\\x00\\x00\\x000' + \\\n (b'\\x0c\\x00\\x00\\x00ComputerName' + len(self.agent_hostname).to_bytes(4, 'little') + self.agent_hostname) + \\\n (b'\\n\\x00\\x00\\x00DomainName\\t\\x00\\x00\\x00WORKGROUP'\n b'\\x12\\x00\\x00\\x00EventFilterVersion\\x01\\x00\\x00\\x000'\n b'\\x19\\x00\\x00\\x00GuidRegenerationSupported\\x01\\x00\\x00\\x001'\n b'\\t\\x00\\x00\\x00IPAddress\\x0f\\x00\\x00\\x00192.168.236.199') + \\\n b'\\n\\x00\\x00\\x00NETAddress' + len(self.agent_mac_address).to_bytes(4, 'little') +self.agent_mac_address + \\\n (b'\\x0b\\x00\\x00\\x00PackageType\\x0b\\x00\\x00\\x00AgentPubKey'\n b'\\n\\x00\\x00\\x00PlatformID\\n\\x00\\x00\\x00W2KW:5:0:4'\n b'\\r\\x00\\x00\\x00PolicyVersion\\x01\\x00\\x00\\x000'\n b'\\x0c\\x00\\x00\\x00PropsVersion\\x0e\\x00\\x00\\x0020170724000500'\n b'\\x0e\\x00\\x00\\x00SequenceNumber\\x01\\x00\\x00\\x003') + \\\n b'\\r\\x00\\x00\\x00ServerKeyHash' + len(self.serverkeyhash).to_bytes(4, 'little') + self.serverkeyhash + \\\n (b'\\x0f\\x00\\x00\\x00SiteinfoVersion\\x01\\x00\\x00\\x000'\n b'\\x15\\x00\\x00\\x00SupportedSPIPEVersion\\x0b\\x00\\x00\\x003.0;4.0;5.0'\n b'\\x0b\\x00\\x00\\x00TaskVersion\\x01\\x00\\x00\\x000') + \\\n b'\\x0f\\x00\\x00\\x00TransactionGUID' + len(self.transaction_guid).to_bytes(4, 'little') + self.transaction_guid\n return self.header_2","def _unpack(self, headerBytes):\n xtraH = struct.unpack(self.PACKAGING_FORMAT, headerBytes)\n\n self.qubit_id = xtraH[0]\n self.remote_app_id = xtraH[1]\n self.remote_node = xtraH[2]\n self.datetime = xtraH[3]\n self.remote_port = xtraH[4]\n self.outcome = xtraH[5]","def _load_data(self, save_temp=False):\n # directly read processed data and encode\n print ('Start tokenizing data...')\n self.data = json.loads(\n open(self.cfg.data_path+self.cfg.data_file, 'r', encoding='utf-8').read().lower())\n self.train, self.dev, self.test = [], [], []\n print ('Start encoding data...')\n p = progressbar.ProgressBar(len(self.data))\n p.start()\n p_idx = 0\n for fn, dial in self.data.items():\n p.update(p_idx)\n p_idx += 1\n if '.json' in fn:\n fn = fn.replace('.json', '')\n if 'all' in self.cfg.exp_domains or self.exp_files.get(fn):\n if self.dev_files.get(fn):\n self.dev.append(self._get_encoded_data(fn, dial))\n elif self.test_files.get(fn):\n self.test.append(self._get_encoded_data(fn, dial))\n else:\n if self.data_mode == 'train':\n self.train.append(self._get_encoded_data(fn, dial))\n elif self.data_mode == 'test':\n pass\n else:\n raise Exception('Wrong Reader Data Mode!!!')\n p.finish()","def load_and_fix(self):\n # Read in json\n self.read_json()\n\n if self.size_to_load:\n self.data = self.data[:self.size_to_load]\n\n # Add names from database given _bsn:\n self.extend_dataframe_with_personnames()\n\n # Clean rows in the data_frame where the names column is empty - > thus no response from the database\n self.clean_none_response()\n\n # Fix path from A09.pdf to A09.json\n self.fix_path()\n\n # Get the correct names from the database response\n self.parse_names_from_response()\n\n print(\" --- Final Shape Data ---\")\n print(self.data.shape)\n print(list(self.data))\n\n # Save pickled object in ./data map\n self.save_obj(self.data, self.file_name_to_save)","def _load_data(self):\n self.mapper = Mapper()\n self.mapper.generate_vocabulary(self.review_summary_file)\n self.X_fwd, self.X_bwd, self.Y = self.mapper.get_tensor(reverseflag=True)\n # Store all the mapper values in a dict for later recovery\n self.mapper_dict = dict()\n self.mapper_dict['seq_length'] = self.mapper.get_seq_length()\n self.mapper_dict['vocab_size'] = self.mapper.get_vocabulary_size()\n self.mapper_dict['rev_map'] = self.mapper.get_reverse_map()\n # Split into test and train data\n self._split_train_tst()","def test_serialises_and_deserialises_hs00_message_correctly_for_full_2d_data(self):\n original_hist = {\n \"source\": \"some_source\",\n \"timestamp\": 123456,\n \"current_shape\": [2, 5],\n \"dim_metadata\": [\n {\n \"length\": 2,\n \"unit\": \"b\",\n \"label\": \"y\",\n \"bin_boundaries\": np.array([10.0, 11.0, 12.0]),\n },\n {\n \"length\": 5,\n \"unit\": \"m\",\n \"label\": \"x\",\n \"bin_boundaries\": np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0]),\n },\n ],\n \"last_metadata_timestamp\": 123456,\n \"data\": np.array([[1.0, 2.0, 3.0, 4.0, 5.0], [6.0, 7.0, 8.0, 9.0, 10.0]]),\n \"errors\": np.array([[5.0, 4.0, 3.0, 2.0, 1.0], [10.0, 9.0, 8.0, 7.0, 6.0]]),\n \"info\": \"info_string\",\n }\n buf = serialise_hs00(original_hist)\n\n hist = deserialise_hs00(buf)\n assert hist[\"source\"] == original_hist[\"source\"]\n assert hist[\"timestamp\"] == original_hist[\"timestamp\"]\n assert hist[\"current_shape\"] == original_hist[\"current_shape\"]\n self._check_metadata_for_one_dimension(\n hist[\"dim_metadata\"][0], original_hist[\"dim_metadata\"][0]\n )\n self._check_metadata_for_one_dimension(\n hist[\"dim_metadata\"][1], original_hist[\"dim_metadata\"][1]\n )\n assert np.array_equal(hist[\"data\"], original_hist[\"data\"])\n assert np.array_equal(hist[\"errors\"], original_hist[\"errors\"])\n assert hist[\"info\"] == original_hist[\"info\"]\n assert (\n hist[\"last_metadata_timestamp\"] == original_hist[\"last_metadata_timestamp\"]\n )","def getInitialData(nsmapi):\r\n # Done 6-1-2020\r\n # TODO extract ids not using the regex?\r\n initData = {}\r\n\r\n url = f\"/healthcheck\"\r\n print(\"Running basic healthcheck\")\r\n healthcheckData = nsmapi.call(url, method=\"PUT\", message='{\"id\":[\"default\"]}')\r\n initData[\"healthcheck\"] = healthcheckData\r\n\r\n for i in range(20):\r\n print(f\".\", end=\"\", flush=True)\r\n time.sleep(.5)\r\n print(\"\")\r\n\r\n print(\"Getting initial sensor data\")\r\n url = \"/sensors\"\r\n basicData = json.dumps(nsmapi.call(url))\r\n dataType = url[1:].replace(\"/\", \"_\")\r\n initData[dataType] = []\r\n for id in re.findall(\"\\\"sensorId\\\":.*?, \\\"name\\\":.*?,\", basicData):\r\n if id[-1] == \",\":\r\n id = id[:-1]\r\n id = id.replace(\"\\\"\", \"\")\r\n id = id.replace(\": \", \":\")\r\n num, name = id.split(\",\")\r\n num = num.split(\":\")[-1]\r\n name = name.split(\":\")[-1]\r\n idName = f\"{num},{name}\"\r\n initData[dataType].append(idName)\r\n\r\n print(\"Getting initial domain data\")\r\n url = \"/domain\"\r\n basicData = json.dumps(nsmapi.call(url))\r\n dataType = url[1:].replace(\"/\", \"_\")\r\n initData[dataType] = []\r\n for id in re.findall(\"\\\"id\\\":.*?, \\\"name\\\":.*?,\", basicData):\r\n if id[-1] == \",\":\r\n id = id[:-1]\r\n id = id.replace(\"\\\"\", \"\")\r\n id = id.replace(\": \", \":\")\r\n num, name = id.split(\",\")\r\n num = num.split(\":\")[-1]\r\n name = name.split(\":\")[-1]\r\n idName = f\"{num},{name}\"\r\n initData[dataType].append(idName)\r\n\r\n policyURLs = [\r\n \"/domain/{domainId}/ipspolicies\",\r\n \"/domain/{domainId}/firewallpolicy\",\r\n \"/domain/{domainId}/connectionlimitingpolicies\",\r\n \"/domain/{domainId}/qospolicy\",\r\n \"/protectionoptionspolicy\",\r\n \"/domain/{domainId}/malwarepolicy\",\r\n \"/domain/{domainId}/policygroups\"\r\n ]\r\n\r\n print(\"Getting initial policy data\")\r\n initData[\"policy\"] = {}\r\n for domain in initData[\"domain\"]:\r\n domainId, domainName = domain.split(\",\")\r\n initData[\"policy\"][domainId] = {}\r\n for url in policyURLs:\r\n url = url.replace(\"{domainId}\", domainId)\r\n policyData = nsmapi.call(url)\r\n key = list(policyData.keys())[0]\r\n policyType = url.split(\"/\")[-1].replace(\"policy\", \"\").replace(\"policies\", \"\")\r\n initData[\"policy\"][domainId][policyType] = []\r\n for policy in policyData[key]:\r\n policy = json.dumps(policy)\r\n # pattern = \"\\\"([^\\\"]*?)(id|ID|iD|Id){0,1}(name){0,1}\\\": (.*?),\" - don't seem to work\r\n # extracted = re.findall(pattern, policy) - don'tens seem to works\r\n # initData[\"policy\"][domainId][policyType][\"full\"] = policy\r\n for polK, polV in json.loads(policy).items():\r\n if \"omain\" not in polK.lower():\r\n if \"name\" in polK.lower():\r\n name = polV\r\n elif \"id\" in polK.lower():\r\n id = polV\r\n initData[\"policy\"][domainId][policyType].append((id,name))\r\n\r\n print(\"Got Initial Data\")\r\n\r\n return initData","def _get_gedi1b_main_data_dict(self) -> dict:\n data = {\n # General identifiable data\n \"granule_name\": [self.parent_granule.filename] * self.n_shots,\n \"shot_number\": self[\"shot_number\"][:],\n \"beam_type\": [self.beam_type] * self.n_shots,\n \"beam_name\": [self.name] * self.n_shots,\n # Temporal data\n \"delta_time\": self[\"delta_time\"][:],\n # Quality data\n \"degrade\": self[\"geolocation/degrade\"][:],\n \"stale_return_flag\": self[\"stale_return_flag\"][:],\n \"solar_elevation\": self[\"geolocation/solar_elevation\"][:],\n \"solar_azimuth\": self[\"geolocation/solar_elevation\"][:],\n \"rx_energy\": self[\"rx_energy\"][:],\n # DEM\n \"dem_tandemx\": self[\"geolocation/digital_elevation_model\"][:],\n \"dem_srtm\": self[\"geolocation/digital_elevation_model_srtm\"][:],\n # geolocation bin0\n \"latitude_bin0\": self[\"geolocation/latitude_bin0\"][:],\n \"latitude_bin0_error\": self[\"geolocation/latitude_bin0_error\"][:],\n \"longitude_bin0\": self[\"geolocation/longitude_bin0\"][:],\n \"longitude_bin0_error\": self[\"geolocation/longitude_bin0_error\"][:],\n \"elevation_bin0\": self[\"geolocation/elevation_bin0\"][:],\n \"elevation_bin0_error\": self[\"geolocation/elevation_bin0_error\"][:],\n # geolocation lastbin\n \"latitude_lastbin\": self[\"geolocation/latitude_lastbin\"][:],\n \"latitude_lastbin_error\": self[\"geolocation/latitude_lastbin_error\"][:],\n \"longitude_lastbin\": self[\"geolocation/longitude_lastbin\"][:],\n \"longitude_lastbin_error\": self[\"geolocation/longitude_lastbin_error\"][:],\n \"elevation_lastbin\": self[\"geolocation/elevation_lastbin\"][:],\n \"elevation_lastbin_error\": self[\"geolocation/elevation_lastbin_error\"][:],\n # relative waveform position info in beam and ssub-granule\n \"waveform_start\": self[\"rx_sample_start_index\"][:] - 1,\n \"waveform_count\": self[\"rx_sample_count\"][:],\n }\n return data","def __init__(self, autoload=True):\n self.header_size = 20\n self.messages = {}\n self.message_hashes = {}\n self.message_rhashes = {}\n self.handlers = {}\n self.remainder = \"\"\n if autoload:\n self.load_definitions()","def __init__(self, data):\n\t\tself.protocol_version, self.le_state, self.playback_state, \\\n\t\t self.source, self.le_flags, self.playback_flags, \\\n\t\t self.source_flags, self.fullness, self.point_rate, \\\n\t\t self.point_count = \\\n\t\t\tstruct.unpack(\"<BBBBHHHHII\", data)","def dataio_prep(hparams):\n\n # Define audio pipeline\n @sb.utils.data_pipeline.takes(\"wav\")\n @sb.utils.data_pipeline.provides(\"sig\")\n def audio_pipeline(wav):\n \"\"\"Load the signal, and pass it and its length to the corruption class.\n This is done on the CPU in the `collate_fn`.\"\"\"\n sig = sb.dataio.dataio.read_audio(wav)\n return sig\n\n # Initialization of the label encoder. The label encoder assignes to each\n # of the observed label a unique index (e.g, 'spk01': 0, 'spk02': 1, ..)\n label_encoder = sb.dataio.encoder.CategoricalEncoder()\n\n # Define label pipeline:\n @sb.utils.data_pipeline.takes(\"emo\")\n @sb.utils.data_pipeline.provides(\"emo\", \"emo_encoded\")\n def label_pipeline(emo):\n yield emo\n emo_encoded = label_encoder.encode_label_torch(emo)\n yield emo_encoded\n\n # Define datasets. We also connect the dataset with the data processing\n # functions defined above.\n datasets = {}\n for dataset in [\"train\", \"valid\", \"test\"]:\n datasets[dataset] = sb.dataio.dataset.DynamicItemDataset.from_json(\n json_path=hparams[f\"{dataset}_annotation\"],\n replacements={\"data_root\": hparams[\"data_folder\"]},\n dynamic_items=[audio_pipeline, label_pipeline],\n output_keys=[\"id\", \"sig\", \"emo_encoded\"],\n )\n # Load or compute the label encoder (with multi-GPU DDP support)\n # Please, take a look into the lab_enc_file to see the label to index\n # mappinng.\n\n lab_enc_file = os.path.join(hparams[\"save_folder\"], \"label_encoder.txt\")\n label_encoder.load_or_create(\n path=lab_enc_file,\n from_didatasets=[datasets[\"train\"]],\n output_key=\"emo\",\n )\n\n return datasets","def _readFixedHeader(self):\n # Init empty fixed header dictionary. Use an ordered dictionary to\n # achieve the same order as in the Mini-SEED manual.\n self.fixed_header = SimpleOrderedDict()\n # Read and unpack.\n self.file.seek(self.record_offset, 0)\n fixed_header = self.file.read(48)\n encoding = ('%s20c2H3Bx4H4Bl2H' % self.endian)\n header_item = unpack(encoding, fixed_header)\n # Write values to dictionary.\n self.fixed_header['Sequence number'] = int(''.join(header_item[:6]))\n self.fixed_header['Data header/quality indicator'] = header_item[6]\n self.fixed_header['Station identifier code'] = \\\n ''.join(header_item[8:13]).strip()\n self.fixed_header['Location identifier'] = \\\n ''.join(header_item[13:15]).strip()\n self.fixed_header['Channel identifier'] = \\\n ''.join(header_item[15:18]).strip()\n self.fixed_header['Network code'] = \\\n ''.join(header_item[18:20]).strip()\n # Construct the starttime. This is only the starttime in the fixed\n # header without any offset. See page 31 of the SEED manual for the\n # time definition.\n self.fixed_header['Record start time'] = \\\n UTCDateTime(year=header_item[20], julday=header_item[21],\n hour=header_item[22], minute=header_item[23],\n second=header_item[24], microsecond=header_item[25] * 100)\n self.fixed_header['Number of samples'] = int(header_item[26])\n self.fixed_header['Sample rate factor'] = int(header_item[27])\n self.fixed_header['Sample rate multiplier'] = int(header_item[28])\n self.fixed_header['Activity flags'] = int(header_item[29])\n self.fixed_header['I/O and clock flags'] = int(header_item[30])\n self.fixed_header['Data quality flags'] = int(header_item[31])\n self.fixed_header['Number of blockettes that follow'] = \\\n int(header_item[32])\n self.fixed_header['Time correction'] = int(header_item[33])\n self.fixed_header['Beginning of data'] = int(header_item[34])\n self.fixed_header['First blockette'] = int(header_item[35])","def _unpack(self, headerBytes):\n pass","def __init__(self, buff):\n fmt = 'hiSSS[SY ]'\n response = struct_helpers.unpack_from(fmt, buff, 0)\n\n self.error_code = response[0]\n self.generation_id = response[1]\n self.group_protocol = response[2]\n self.leader_id = response[3]\n self.member_id = response[4]\n # TODO - parse metadata bytestring into ConsumerGroupProtocolMetadata?\n self.members = {_id: meta for _id, meta in response[5]}","def parse_header_dict(self, header_dict=None):\n if header_dict is not None:\n self.header_dict = header_dict\n\n assert isinstance(self.header_dict, dict)\n\n for key, value in self.header_dict.items():\n if \"wire\" in key:\n if key.find(\"n\") == 0:\n self.ex_length = float(value.split()[0])\n self.ex_azimuth = float(value.split()[1])\n elif key.find(\"e\") == 0:\n self.ey_length = float(value.split()[0])\n self.ey_azimuth = float(value.split()[1])\n elif \"system\" in key:\n self.box_id = value.split(\";\")[0].strip()\n self.mag_id = value.split(\";\")[1].strip()\n elif \"gps\" in key:\n gps_list = value.split()\n self.header_gps_stamp = MTime(\n dateutil.parser.parse(\n \" \".join(gps_list[0:2]), dayfirst=True\n )\n )\n self.header_gps_latitude = self._get_latitude(\n gps_list[2], gps_list[3]\n )\n self.header_gps_longitude = self._get_longitude(\n gps_list[4], gps_list[5]\n )\n self.header_gps_elevation = float(gps_list[6])\n elif \"run\" in key:\n self.run_id = value.replace('\"', \"\")\n else:\n setattr(self, key.replace(\" \", \"_\").replace(\"/\", \"_\"), value)","def _load_data(self):\n if self._api_response.status_code == 200:\n self._dataset = self._api_response.json()\n self._fill_day_dicts()","def _detectors1(self, hdr):\n d = {}\n d['FCs'] = self._exit_slits(hdr)\n\n for n in range(1, 6):\n det = 'Detector {}'.format(n)\n d[det] = self._exit_slits(hdr)\n\n d['LD'] = {}\n d['LD']['exit slit width'], d['LD']['exit slit coeff a'], \\\n d['LD']['exit slit coeff b'], d['E0S'], \\\n d['pressure multicollection chamber'], \\\n d['FCs']['fc background setup positive'], \\\n d['FCs']['fc background setup negative'] = \\\n unpack(self._bo + '4d 32s 2i', hdr.read(72))\n\n d['pressure multicollection chamber'] = \\\n self._cleanup_string(d['pressure multicollection chamber'])\n\n for n in range(1, 6):\n det = 'Detector {}'.format(n)\n d[det].update(self._electron_multiplier(hdr))\n\n d['LD'].update(self._electron_multiplier(hdr))\n\n d['EMBig'] = self._exit_slits(hdr)\n d['EMBig'].update(self._electron_multiplier(hdr))\n\n # 8 bytes unused\n hdr.seek(8, 1)\n return d","def main() -> Dict[int, int]:\n # DOCUMENTS DIRECTORY\n # Path of the directory that contains the .txt documents. One .txt document by company. IT NEEDS TO BE \"/data\" when you upload it in data challenge platform. For test in local, you can modifiy to match your data path.\n if dev:\n documents_directory = \"../example_dataset/data\"\n else: \n documents_directory = \"/data\"\n\n path_to_files: List[str] = [os.path.join(documents_directory, file) for file in os.listdir(documents_directory)]\n assert len(path_to_files) == 10 # 10 files in documents directory\n path_to_files.sort() # Sort list of path file by alphabetical order to match ground truth annotations order : IT IS ESSENTIAL.\n\n # INITIALIZATION OF YOUR OBJECTS\n data_model = FormDataModel.from_json_file(\n os.path.join(os.path.dirname(__file__), \"resources\", \"data-model.json\")\n )\n country_referential = CountryReferential.from_csv(\n os.path.join(os.path.dirname(__file__), \"resources\", \"countries_code.csv\")\n )\n form_company_filling = FormCompanyFilling([\n BasicExtractor(\n question_ids=NOT_COUNTRY_QUESTIONS_NUMBERS,\n form_data_model=data_model,\n ),\n BasicCountryExtractor(\n question_ids=COUNTRY_QUESTIONS_NUMBERS,\n form_data_model=data_model,\n country_code_referential=country_referential,\n\n )\n ])\n\n # COMPUTE PREDICTION BY FILE (ie company)\n print(\"##################################\")\n print(\"RUNNING PREDICTION\")\n results: Dict[int, int] = {}\n start_time = time.time()\n for i, path in enumerate(path_to_files):\n start = time.time()\n print(f\"File : {path}\")\n with open(path, \"r\") as input_file:\n text = input_file.read()\n print(\"... Encoding ...\")\n start_encoding = time.time()\n embeddings = model.encode(prepare_sentences(text))\n # embeddings = []\n print(\"Successfully encoded\")\n print(\"Encoding time : \", time.time() - start_encoding)\n\n form_company_response = form_company_filling.fill(text, embeddings, model)\n form_company_response.sort_by_question_id() # ESSENTIAL : Sort the response by question number for each company\n for answer in form_company_response.answers:\n question_number = answer.question_id + i * 22 # ESSENTIAL : each company has 22 questions. Each question_number in results should be unique\n results[question_number] = answer.answer_id\n # gc.collect()\n print(\"File time :\", time.time()-start, '\\n')\n # CHECK FORMAT RESULTS IS DATACHALLENGE PLATFORM COMPATIBLE\n assert len(results) == len(path_to_files) * (len(COUNTRY_QUESTIONS_NUMBERS) + len(NOT_COUNTRY_QUESTIONS_NUMBERS))\n assert set(list(results.keys())) == {i for i in range(1,221)}\n print(\"Full Time\", time.time()-start_time)\n return results","def __init__(self, data: bytes):\n super().__init__()\n self._expected_packet_type = MessageType.MAIN\n self._expected_data_size = 34\n self._data_raw = b''\n self._packet_type = MessageType.UNDEFINED\n self._packet_number = 0\n self.time_stamp_1MHz = 0\n self.accelerometer_x = 0\n self.accelerometer_y = 0\n self.accelerometer_z = 0\n self.magnetometer_x = 0\n self.magnetometer_y = 0\n self.magnetometer_z = 0\n self.gyroscope_x = 0\n self.gyroscope_y = 0\n self.gyroscope_z = 0\n self.quaternion_q0 = 0\n self.quaternion_q1 = 0\n self.quaternion_q2 = 0\n self.quaternion_q3 = 0\n self.flags = 0\n self.shield_and_kinetis_byte = 0\n self._is_valid = False\n self._parse_data(data)","def __record(self, data={}):\n # Create a config file\n if not self.config_file:\n self.config_file = \"./default.config\"\n\n # Create empty config json file if not there\n if not os.path.isfile(self.config_file):\n with open(self.config_file, 'w') as f:\n d = json.dumps({})\n f.write(d)\n\n # This structure ensures that for different servers, there can exist\n # multiple licenses (`license_key`), which contains one `device_token`\n # each and multiple users (identified by `user_email`), each with its\n # own `user_token`.\n\n # Overwrite values with current values\n if not data or data == {}:\n with open(self.config_file, 'r') as f:\n data = json.load(f)\n data[self.server] = {}\n if self.license_key != '':\n data[self.server][self.license_key] = {}\n if self.device_token != '':\n data[self.server][self.license_key][\"device_token\"] = self.device_token\n if self.user.email != '':\n data[self.server][self.license_key][self.user.email] = {}\n if self.user_token != '':\n data[self.server][self.license_key][self.user.email][\"user_token\"] = self.user_token\n else:\n data = data\n\n # Clean up the remaining values (i.e. get rid of it if it's empty)\n copied = copy.deepcopy(data)\n for server in copied.keys():\n if server not in self.__valid_servers.keys():\n data.pop(server, None)\n\n for key in copied[server].keys():\n data[server].pop('', None)\n data[server].pop(' ', None)\n if copied[server][key] == {}:\n data[server].pop(key, None)\n\n for k in copied[server][key].keys():\n if k != \"device_token\":\n data[server][key].pop('', None)\n data[server][key].pop(' ', None)\n if copied[server][key][k] == {} or copied[server][key][k] == \"\":\n data[server][key].pop(k, None)\n\n with open(self.config_file, 'w') as f:\n d = json.dumps(data)\n f.write(d)","def deserialize(self, str):\n try:\n if self.header is None:\n self.header = std_msgs.msg.Header()\n end = 0\n _x = self\n start = end\n end += 12\n (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _get_struct_3I().unpack(str[start:end])\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n start = end\n end += length\n if python3:\n self.header.frame_id = str[start:end].decode('utf-8')\n else:\n self.header.frame_id = str[start:end]\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n start = end\n end += length\n if python3:\n self.canmsg = str[start:end].decode('utf-8')\n else:\n self.canmsg = str[start:end]\n _x = self\n start = end\n end += 30\n (_x.track_id, _x.track_lat_rate, _x.track_group_changed, _x.track_status, _x.track_angle, _x.track_range, _x.track_bridge_object, _x.track_rolling_count, _x.track_width, _x.track_range_accel, _x.track_med_range_mode, _x.track_range_rate,) = _get_struct_Bf2B2f2B2fBf().unpack(str[start:end])\n self.track_group_changed = bool(self.track_group_changed)\n self.track_bridge_object = bool(self.track_bridge_object)\n self.track_rolling_count = bool(self.track_rolling_count)\n return self\n except struct.error as e:\n raise genpy.DeserializationError(e) #most likely buffer underfill","def _decode_header(self):\n #header = self.file_content[0:6]\n log_screen_descr = self.file_content[6:13]\n self.canvas_width = log_screen_descr[0] + (log_screen_descr[1]<<8)\n self.canvas_height = log_screen_descr[2] + (log_screen_descr[3]<<8)\n # is there a global color table? (usually yes)\n flags = log_screen_descr[4]\n self.glob_col_table = (flags & 0b10000000) != 0\n\n # determine the number of bits per primary color value\n self.color_resolution = (flags & 0b01110000) >> 4\n self.bits_per_pixel = self.color_resolution + 1\n\n # If the value is 1, then the colors in the global color table are sorted\n # in order of \"decreasing importance,\" which typically means \"decreasing\n # frequency\" in the image\n self.sort_flag = (flags & 0b00001000) != 0\n\n # If this value is N, then the actual table size is 2^(N+1).\n self.glob_col_table_sz = 1 << ((flags & 0b00000111)+1)\n\n self.bg_color_index = log_screen_descr[5]\n self.pix_asp_ratio = log_screen_descr[6]","def _unpack(self, headerBytes):\n xtraH = struct.unpack(self.PACKAGING_FORMAT, headerBytes)\n\n self.qubit_id = xtraH[0]\n self.remote_app_id = xtraH[1]\n self.remote_node = xtraH[2]\n self.cmdLength = xtraH[3]\n self.remote_port = xtraH[4]\n self.step = xtraH[5]","def upload_initial_data():\n data = {\"updated\":1512866292573,\"data\":[[[\"DAY %\",\"PPS (CAD)\",\"TKR\",\"NAME\",\"SECTOR\",\"EX.\",\"ALT. TKR\",\"VOL\",\"VOL @ CRNT $\",\"MC ($MM)\"],[\"5.84%\",\"1.45\",\"ABCN\",\"ABcann Medicinals\",\"BioTech\",\"CVE\",\"ABCCF\",\"901,940\",\"1,307,813\",\"78.49\"],[\"6.14%\",\"7.09\",\"ACB\",\"Aurora Cannabis\",\"Cultivation & Retail\",\"TSE\",\"ACBFF\",\"13,927,205\",\"98,743,883.45\",\"2,861.53\"],[\"9.09%\",\"0.24\",\"ACG\",\"Alliance Growers \",\"AgTech\",\"CNSX\",\"--\",\"1,189,385\",\"285,452.4\",\"\"],[\"0.00%\",\"0.10\",\"AFI\",\"Affinor Growers\",\"AgTech\",\"CNSX\",\"RSSFF\",\"210,310\",\"21,031\",\"\"],[\"3.22%\",\"13.47\",\"APH\",\"Aphria\",\"Cultivation & Retail\",\"TSE\",\"APHQF\",\"2,663,133\",\"35,872,401.51\",\"2,042.08\"],[\"13.95%\",\"0.25\",\"ATT\",\"Abattis Bio\",\"BioTech\",\"CNSX\",\"ATTBF\",\"2,706,357\",\"676,589.25\",\"39.86\"],[\"0.00%\",\"2.03\",\"BE\",\"Beleave\",\"Cultivation & Retail\",\"CNSX\",\"BLEVF\",\"597,909\",\"1,213,755.27\",\"\"],[\"1.28%\",\"1.58\",\"BLO\",\"Cannabix Tech\",\"LawTech\",\"CNSX\",\"BLOZF\",\"465,869\",\"736,073.02\",\"136.61\"],[\"-2.20%\",\"0.89\",\"CBW\",\"Cannabis Wheaton \",\"Investing & Finance\",\"CVE\",\"KWFLF\",\"815,477\",\"725,774.53\",\"234.57\"],[\"-0.65%\",\"19.93\",\"CMED\",\"Cannimed\",\"Cultivation & Retail\",\"TSE\",\"CMMDF\",\"130,722\",\"2,605,289.46\",\"457.69\"],[\"12.73%\",\"0.62\",\"CMM\",\"Canabo Medical\",\"MedCare\",\"CVE\",\"CAMDF\",\"330,404\",\"204,850.48\",\"23.54\"],[\"-2.87%\",\"2.71\",\"CRZ\",\"Cannaroyalty\",\"Investing & Finance\",\"CNSX\",\"CNNRF\",\"961,449\",\"2,605,526.79\",\"115.09\"],[\"-6.67%\",\"0.28\",\"CYX\",\"Calyx Bio\",\"AgTech\",\"CVE\",\"CLYXF\",\"2,120,562\",\"593,757.36\",\"24.23\"],[\"0.00%\",\"1.23\",\"DOJA\",\"DOJA Cannabis\",\"Cultivation & Retail\",\"CNSX\",\"DJACF\",\"206,635\",\"254,161.05\",\"72.27\"],[\"-4.40%\",\"0.44\",\"DVA\",\"Delivra\",\"BioTech\",\"CVE\",\"--\",\"89,485\",\"39,373.4\",\"19.55\"],[\"6.52%\",\"0.25\",\"EAT\",\"Nutritional High\",\"Marijuana Edibles & Extracts\",\"CNSX\",\"SPLIF\",\"3,067,636\",\"766,909\",\"61.54\"],[\"-1.20%\",\"1.64\",\"EMC\",\"Emblem\",\"Cultivation & Retail\",\"CVE\",\"EMMBF\",\"411,764\",\"675,292.96\",\"130.60\"],[\"2.05%\",\"3.98\",\"EMH\",\"Emerald\",\"Cultivation & Retail\",\"CVE\",\"TBQBF\",\"1,430,067\",\"5,691,666.66\",\"374.34\"],[\"-5.88%\",\"0.48\",\"FFT\",\"Future Farm Tech\",\"AgTech\",\"CNSX\",\"AGSTF\",\"1,291,240\",\"619,795.2\",\"0.61\"],[\"1.06%\",\"1.90\",\"FIRE\",\"Supreme Pharma\",\"Cultivation & Retail\",\"CVE\",\"SPRWF\",\"1,275,906\",\"2,424,221.4\",\"391.96\"],[\"5.26%\",\"0.10\",\"GHG\",\"Global Hemp\",\"Cultivation & Retail\",\"CNSX\",\"GBHPF\",\"764,350\",\"76,435\",\"\"],[\"3.28%\",\"0.31\",\"GLH\",\"Golden Leaf\",\"Marijuana Products\",\"CNSX\",\"GLDFF\",\"4,298,567\",\"1,332,555.77\",\"116.96\"],[\"-1.96%\",\"0.50\",\"HC\",\"High Hampton Holdings\",\"Investing & Finance\",\"CNSX\",\"--\",\"727,116\",\"363,558\",\"\"],[\"1.89%\",\"0.54\",\"HIP\",\"Newstirke Resources \",\"Cultivation & Retail\",\"CVE\",\"NWKRF\",\"431,875\",\"233,212.5\",\"210.35\"],[\"8.91%\",\"1.10\",\"HVST\",\"Harvest One Cannabis\",\"Cultivation & Retail\",\"CVE\",\"HRVOF\",\"2,192,877\",\"2,412,164.7\",\"98.10\"],[\"8.89%\",\"0.98\",\"ICC\",\"International Cannabis\",\"Cultivation & Retail\",\"CVE\",\"ICCLF\",\"123,538\",\"121,067.24\",\"110.84\"],[\"0.00%\",\"1.62\",\"IMH\",\"Invictus MD\",\"Investing & Finance\",\"CVE\",\"IVITF\",\"781,924\",\"1,266,716.88\",\"129.87\"],[\"12.50%\",\"0.90\",\"IN\",\"Inmed Pharma\",\"BioTech\",\"CNSX\",\"IMLFF\",\"3,846,586\",\"3,461,927.4\",\"\"],[\"2.27%\",\"1.80\",\"ISOL\",\"Isodiol International \",\"Hemp Products\",\"CNSX\",\"LAGBF\",\"8,514,952\",\"15,326,913.6\",\"\"],[\"7.84%\",\"0.28\",\"KALY\",\"Kalytera Therapeutics\",\"BioTech\",\"CVE\",\"QUEZD\",\"5,634,186\",\"1,577,572.08\",\"34.74\"],[\"-1.72%\",\"0.57\",\"LDS\",\"Lifestyle Delivery Systems\",\"BioTech\",\"CNSX\",\"LDSYF\",\"685,628\",\"390,807.96\",\"51.44\"],[\"0.19%\",\"15.50\",\"LEAF\",\"MedReleaf Corp\",\"Cultivation & Retail\",\"TSE\",\"MEDFF\",\"229,190\",\"3,552,445\",\"1,459.18\"],[\"2.33%\",\"0.44\",\"LIB\",\"Liberty Leaf Holdings\",\"Investing & Finance\",\"CNSX\",\"LIBFF\",\"4,555,082\",\"2,004,236.08\",\"\"],[\"10.42%\",\"1.59\",\"LXX\",\"Lexaria Bio\",\"Hemp Products\",\"CNSX\",\"LXRP\",\"1,523,338\",\"2,422,107.42\",\"\"],[\"-1.38%\",\"2.14\",\"MARI\",\"Maricann Group\",\"Cultivation & Retail\",\"CNSX\",\"MRRCF\",\"678,106\",\"1,451,146.84\",\"157.10\"],[\"3.26%\",\"0.95\",\"MDM\",\"Marapharm\",\"Cultivation & Retail\",\"CNSX\",\"MRPHF\",\"209,019\",\"198,568.05\",\"\"],[\"0.00%\",\"0.57\",\"MGW\",\"Maple Leaf Green World\",\"Cultivation & Retail\",\"CVE\",\"MGWFF\",\"367,479\",\"209,463.03\",\"83.83\"],[\"7.37%\",\"1.02\",\"MJ\",\"True Leaf\",\"Hemp Pet Chews\",\"CNSX\",\"TLFMF\",\"164,101\",\"167,383.02\",\"\"],[\"2.27%\",\"4.50\",\"MJN\",\"Pharmacan /Cronos\",\"Investing & Finance\",\"CVE\",\"PRMCF\",\"419,922\",\"1,889,649\",\"675.43\"],[\"4.23%\",\"2.71\",\"MYM\",\"My Marijuana\",\"Cultivation & Retail\",\"CNSX\",\"--\",\"1,066,122\",\"2,889,190.62\",\"\"],[\"4.40%\",\"0.95\",\"N\",\"Namaste Tech\",\"Consumption Devices\",\"CNSX\",\"NXTTF\",\"5,714,764\",\"5,429,025.8\",\"192.50\"],[\"0.00%\",\"0.10\",\"NF\",\"New Age Farm\",\"Hemp Products\",\"CNSX\",\"NWGFF\",\"3,938,476\",\"393,847.6\",\"\"],[\"-7.27%\",\"0.25\",\"NSP\",\"Naturally Splendid\",\"Hemp Products\",\"CVE\",\"NSPDF\",\"484,812\",\"121,203\",\"24.42\"],[\"4.99%\",\"3.79\",\"OGI\",\"Organigram\",\"Cultivation & Retail\",\"CVE\",\"OGRMF\",\"3,654,843\",\"13,851,854.97\",\"375.89\"],[\"1.15%\",\"0.88\",\"PUF\",\"PUF Ventures\",\"Consumption Devices\",\"CNSX\",\"PUFXF\",\"719,534\",\"633,189.92\",\"45.85\"],[\"10.68%\",\"1.14\",\"RHT\",\"Reliq Health Tech\",\"Mobile Software\",\"CVE\",\"RQHTF\",\"1,564,567\",\"1,783,606.38\",\"98.74\"],[\"4.05%\",\"1.80\",\"RTI\",\"Radient Technologies\",\"Extraction\",\"CVE\",\"RDDTF\",\"2,181,473\",\"3,926,651.4\",\"345.53\"],[\"3.64%\",\"0.28\",\"RVV\",\"Revive Therapeutics\",\"Medication\",\"CVE\",\"RVVTF\",\"399,705\",\"111,917.4\",\"15.50\"],[\"-2.90%\",\"0.67\",\"SUN\",\"Wildflower\",\"Hemp Products\",\"CNSX\",\"WLDFF\",\"87,197\",\"58,421.99\",\"29.48\"],[\"-0.67%\",\"4.45\",\"SXP\",\"Supremex\",\"Packaging\",\"TSE\",\"SUMXF\",\"27,015\",\"120,216.75\",\"126.40\"],[\"0.00%\",\"0.76\",\"TBP\",\"Tetra Bio-Pharma\",\"BioTech\",\"CVE\",\"GRPOF\",\"497,745\",\"378,286.2\",\"88.67\"],[\"2.44%\",\"2.10\",\"TER\",\"TerrAscend Corp\",\"Cultivation & Retail\",\"CNSX\",\"--\",\"270,176\",\"567,369.6\",\"\"],[\"4.29%\",\"0.73\",\"THC\",\"THC Biomed\",\"BioTech\",\"CNSX\",\"THCBF\",\"818,162\",\"597,258.26\",\"81.29\"],[\"3.55%\",\"3.21\",\"THCX\",\"Hydropothecary Corp\",\"Cultivation & Retail\",\"CVE\",\"HYYDF\",\"1,581,640\",\"5,077,064.4\",\"282.37\"],[\"8.22%\",\"0.79\",\"TNY\",\"Tinley Beverage Co\",\"Beverage\",\"CNSX\",\"QRSRF\",\"945,154\",\"746,671.66\",\"57.81\"],[\"3.49%\",\"7.70\",\"TRST\",\"CannTrust\",\"Cultivation & Biotech\",\"CNSX\",\"CNTTF\",\"368,892\",\"2,840,468.4\",\"699.98\"],[\"-8.04%\",\"1.03\",\"VGW\",\"Valens Groworks\",\"BioTech\",\"CNSX\",\"MYMSF\",\"23,285\",\"23,983.55\",\"62.77\"],[\"0.00%\",\"0.52\",\"VIN\",\"Vinergy Resources\",\"Investing & Finance\",\"CNSX\",\"VNNYF\",\"0\",\"\",\"\"],[\"-2.50%\",\"0.39\",\"VP\",\"Vodis Pharma\",\"Cultivation & Retail\",\"CNSX\",\"VDQSF\",\"52,661\",\"20,537.79\",\"\"],[\"6.67%\",\"0.80\",\"VRT\",\"Veritas Pharma\",\"BioTech\",\"CNSX\",\"VRTHF\",\"377,901\",\"302,320.8\",\"\"],[\"6.41%\",\"19.42\",\"WEED\",\"Canopy Growth\",\"Cultivation & Retail\",\"TSE\",\"TWMJF\",\"4,940,034\",\"95,935,460.28\",\"3,706.63\"],[\"6.25%\",\"2.38\",\"WMD\",\"WeedMD\",\"Cultivation & Retail\",\"CVE\",\"WDDMF\",\"1,174,148\",\"2,794,472.24\",\"124.71\"],[\"3.36%\",\"14.75\",\"HMMJ\",\"Horizons Marijuana Life Sciences\",\"Canadian Marijuana ETF\",\"TSE\",\"HMLSF\",\"336,579\",\"4,964,540.25\",\"197.64\"]]],\"sheetnames\":[\"ALLSHOW\"]}\n \n exchange_suffixes = {'TSE': 'TO', 'CVE': 'V'}\n\n # create sector\n sector, _ = Sector.objects.get_or_create(name=\"Cannabis\", slug='cannabis')\n\n # create currency\n currency, _ = Currency.objects.get_or_create(symbol='CAD', defaults={'character':'$', 'name':'Canadian Dollar'})\n us_currency, _ = Currency.objects.get_or_create(symbol='USD', defaults={'character':'$', 'name':'US Dollar'})\n\n # OTC exchange\n otc, _ = Exchange.objects.get_or_create(symbol='OTC', defaults={'name':'OTC', 'currency': us_currency})\n\n # iterate over each item in our table, make the items\n for row in data[\"data\"][0][1:]:\n # percent = float(row[0].replace(\"%\",\"\"))\n suffix = exchange_suffixes[row[5]] if row[5] in exchange_suffixes else ''\n exchange, _ = Exchange.objects.get_or_create(symbol=row[5], defaults={'name':row[5], 'currency':currency, 'ticker_suffix': suffix})\n company, _ = Company.objects.get_or_create(name=row[3], defaults={'sector':sector})\n stock, _ = Stock.objects.get_or_create(ticker=row[2], defaults={\n 'company': company,\n 'exchange': exchange,\n 'market_cap': float(row[9].replace(\",\",\"\")) * 1000000 if row[9] else 0.0,\n # 'previous_close': float(row[1]) - float(row[1]) * percent / 100,\n # 'open': float(row[1]),\n # 'current': float(row[1]),\n # 'volume': float(row[8].replace(\",\",\"\")) if row[8] else 0.0,\n })\n stock.save()\n\n if row[4]:\n tag, _ = Tag.objects.get_or_create(name=row[4])\n company.tags.add(tag)\n\n if row[6] and not row[6] == \"--\":\n stock, _ = Stock.objects.get_or_create(ticker=row[6], defaults={'company':company, 'exchange':otc})\n\n\n print data","def Load(self):\n\t\tfile = open(self.fileName, 'r')\n\t\tself.hdr = file.readline().split('\\n')[0].split(',')\n\t\t\n\t\tfor line in file.readlines():\n\t\t\ttokens = line.split('\\n')[0].split(',')\n\t\t\tif int(tokens[1]) == 0:\n\t\t\t\tself.h0.append(tokens[0])\n\t\t\telse:\n\t\t\t\tself.h1.append(tokens[0])\n\t\tfile.close()\n\t\tself.numH1 = len(self.h1)\n\t\tself.numH0 = len(self.h0)","def read_header(infile):\n h = dict()\n fid = open(infile, 'r+b')\n h['filename'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 20))\n h['parent_filename'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 20))\n h['comments1'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 80))\n h['comments2'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 80))\n h['energy_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['config_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['file_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['trans_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['scan_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['data_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['date_modified'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 16))\n h['frequency'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['mat_velocity'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['num_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\n h['num_polarization_channels'] =np.fromfile(fid, dtype = np.int16,count = 1)\n h['spare00'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['adc_min_voltage'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['adc_max_voltage'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['band_width'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['spare01'] = np.fromfile(fid, dtype = np.int16, count = 5)\n h['polarization_type'] = np.fromfile(fid, dtype = np.int16, count = 4)\n h['record_header_size'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['word_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['word_precision'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['min_data_value'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['max_data_value'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['avg_data_value'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['data_scale_factor'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['data_units'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['surf_removal'] = np.fromfile(fid, dtype = np.uint16, count = 1)\n h['edge_weighting'] = np.fromfile(fid, dtype = np.uint16, count = 1)\n h['x_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\n h['y_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\n h['z_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\n h['t_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\n h['spare02'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['x_return_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_return_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_return_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['scan_orientation'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['scan_direction'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['data_storage_order'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['scanner_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['x_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['t_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['num_x_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\n h['num_y_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\n h['num_z_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\n h['num_t_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\n h['x_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['x_acc'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_acc'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_acc'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['x_motor_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_motor_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_motor_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['x_encoder_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_encoder_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_encoder_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['date_processed'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 8))\n h['time_processed'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 8))\n h['depth_recon'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['x_max_travel'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_max_travel'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['elevation_offset_angle'] = np.fromfile(fid,dtype = np.float32, count = 1)\n h['roll_offset_angle'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_max_travel'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['azimuth_offset_angle'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['adc_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['spare06'] = np.fromfile(fid, dtype = np.int16, count = 1)\n h['scanner_radius'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['x_offset'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['y_offset'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['z_offset'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['t_delay'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['range_gate_start'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['range_gate_end'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['ahis_software_version'] = np.fromfile(fid, dtype = np.float32, count = 1)\n h['spare_end'] = np.fromfile(fid, dtype = np.float32, count = 10)\n return h","def _decode_data_dict(self, data_dict: dict) -> dict:\n if ENCODED_DATA_KEY not in data_dict:\n return data_dict\n\n encoded_data = data_dict[ENCODED_DATA_KEY]\n _buffer = io.BytesIO(encoded_data)\n data_dict = torch.load(\n _buffer,\n map_location=\"cpu\"\n # Not using ray.cloudpickle here as it doesn't\n # define an Unpickler (as it is not necessary).\n )\n return data_dict","def headersFromRawFile(self, rawFile: str, headers: Dict) -> None:\n dFile = open(os.path.join(self.dataPath, rawFile), \"r\", encoding=\"ISO-8859-1\")\n generalHeaderString = dFile.read(1000) # this should be long enough\n generalSplit = generalHeaderString.split()\n # read GENERAL HEADER\n generalHeader = {}\n generalHeader[\"recLength\"] = int(generalSplit[0])\n generalHeader[\"fileType\"] = generalSplit[1]\n generalHeader[\"wordLength\"] = int(generalSplit[2])\n generalHeader[\"version\"] = generalSplit[3]\n generalHeader[\"procId\"] = generalSplit[4]\n generalHeader[\"numCh\"] = int(generalSplit[5])\n generalHeader[\"totalRec\"] = int(generalSplit[6])\n generalHeader[\"firstEvent\"] = int(generalSplit[7])\n generalHeader[\"numEvent\"] = int(generalSplit[8])\n generalHeader[\"extend\"] = int(generalSplit[9])\n\n # read EVENT HEADER - there can be multiple of these, but normally only the one\n # Multiple events are largely deprecated. Only a single event is used\n eventHeaders = []\n fileSize = os.path.getsize(os.path.join(self.dataPath, rawFile))\n record = generalHeader[\"firstEvent\"]\n for ir in range(0, generalHeader[\"numEvent\"]):\n seekPt = (record - 1) * generalHeader[\"recLength\"]\n if not seekPt > fileSize:\n # seek from beginning of file\n dFile.seek(seekPt, 0)\n # read extra to make sure\n eventString = dFile.read(1000)\n eventSplit = eventString.split()\n eH = {}\n eH[\"start\"] = int(eventSplit[0])\n eH[\"startms\"] = int(eventSplit[1])\n eH[\"stop\"] = int(eventSplit[2])\n eH[\"stopms\"] = int(eventSplit[3])\n eH[\"cvalue1\"] = float(eventSplit[4])\n eH[\"cvalue2\"] = float(eventSplit[5])\n eH[\"cvalue3\"] = float(eventSplit[6])\n eH[\"EHInfile\"] = int(eventSplit[7])\n eH[\"nextEH\"] = int(eventSplit[8])\n eH[\"previousEH\"] = int(eventSplit[9])\n eH[\"numData\"] = int(eventSplit[10])\n eH[\"startData\"] = int(eventSplit[11])\n eH[\"extended\"] = int(eventSplit[12])\n eventHeaders.append(eH)\n if eH[\"nextEH\"] < generalHeader[\"totalRec\"]:\n record = eH[\"nextEH\"] # set to go to next eH\n else:\n break # otherwise break out of for loops\n # close the data file\n dFile.close()\n # now compare number of samples with that calculated previously\n if eventHeaders[0][\"numData\"] != headers[\"num_samples\"]:\n self.printWarning(\"Data file: {}\".format(dFile))\n self.printWarning(\n \"Number of samples in raw file header {} does not equal that calculated from data {}\".format(\n eventHeaders[0][\"numData\"], headers[\"num_samples\"]\n )\n )\n self.printWarning(\"Number of samples calculated from data will be used\")\n # set the byte offset for the file\n self.dataByteOffset[rawFile] = (\n eventHeaders[0][\"startData\"] - 1\n ) * generalHeader[\"recLength\"]\n self.recChannels[rawFile] = generalHeader[\"numCh\"]","def decodemeta(data):\n d = {}\n for l in data.split('\\0'):\n if l:\n key, value = l.split(':')\n d[key] = value\n return d","def loads(self, data):\n self._id = data.get('id', -1)\n self._created = data.get('created', 0) # datetime.strptime(data.get('created', '1970-01-01T00:00:00'), '%Y-%m-%dT%H:%M:%S').timestamp()\n self._stage = data.get('stage', 0) # self.stage_from_str(data.get('stage', ''))\n self._dir = data.get('direction', 0) # self.direction_from_str(data.get('direction', ''))\n self._timeframe = data.get('timeframe') # timeframe_from_str(data.get('timeframe', 't'))\n self._expiry = data.get('expiry', 0) # datetime.strptime(data.get('expiry', '1970-01-01T00:00:00'), '%Y-%m-%dT%H:%M:%S').timestamp()","def _read_old_header(self, raw):\n\n byte_count = 0\n\n data_size = 4\n self.label = struct.unpack('<4s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.version = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.revision = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 26\n self.date = struct.unpack('<26s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.file_format = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.file_type = struct.unpack('<4s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.original_file_name = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.reference_file_name = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.related_file_name_a = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.related_file_name_b = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.related_file_name_c = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.related_file_name_d = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 82\n self.annotate = struct.unpack('<82s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 33\n self.instrument_model = struct.unpack('<33s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 33\n self.instrument_serial_number = struct.unpack('<33s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 33\n self.software_version_number = struct.unpack('<33s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 33\n self.crystal_material = struct.unpack('<33s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.laser_wavelength_microns = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.laser_null_doubling = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.optical_ratio = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.dispersion_constant_xc = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.dispersion_constant_xm = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.dispersion_constant_xb = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.interferogram_size = struct.unpack('<H',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.interferogram_center.append(struct.unpack('<H',\n raw[byte_count:byte_count+data_size])[0])\n byte_count += data_size\n\n data_size = 2\n self.interferogram_center.append(struct.unpack('<H',\n raw[byte_count:byte_count+data_size])[0])\n byte_count += data_size\n\n data_size = 2\n self.acquire_mode = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.emissivity = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.apodization = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.zero_fill = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.run_time_math = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.fft_size = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.number_of_coadds = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 2\n self.number_of_igrams = struct.unpack('<h',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.amb_temperature = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.inst_temperature = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.wbb_temperature = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.cbb_temperature = struct.unpack('<f',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 20\n self.spare_i = struct.unpack('<hhhhhhhhhh',\n raw[byte_count:byte_count+data_size])\n byte_count += data_size\n\n data_size = 40\n self.spare_f = struct.unpack('<ffffffffff',\n raw[byte_count:byte_count+data_size])\n byte_count += data_size\n\n data_size = 40\n self.spare_l = struct.unpack('<ffffffffff',\n raw[byte_count:byte_count+data_size])\n byte_count += data_size\n\n data_size = 65\n self.spare_na = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.spare_nb = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.spare_nc = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.spare_nd = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 65\n self.spare_ne = struct.unpack('<65s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size\n\n data_size = 4\n self.header_end = struct.unpack('<4s',\n raw[byte_count:byte_count+data_size])[0]\n byte_count += data_size","def verify_header (filename, htypes=None):\n\n # dictionary\n dict_head = {\n # raw header\n # commenting out SIMPLE, BSCALE and BZERO - basic keywords\n # that will be present in images but not in binary fits tables\n #'SIMPLE': {'htype':'raw', 'dtype':bool, 'DB':False, 'None_OK':True},\n #'BSCALE': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\n #'BZERO': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\n 'BITPIX': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n 'NAXIS': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n 'NAXIS1': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n 'NAXIS2': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n 'BUNIT': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n #'CCD-AMP': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'SET-TEMP': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\n 'CCD-TEMP': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'XBINNING': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n 'YBINNING': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n #'CCD-SET': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'ALTITUDE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'AZIMUTH': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'DOMEAZ': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\n 'RADESYS': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'EPOCH': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\n 'RA': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\n 'RA-REF': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n #'RA-TEL': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\n 'DEC': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\n 'DEC-REF': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n #'DEC-TEL': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\n 'HA': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\n 'FLIPSTAT': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'EXPTIME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\n 'ISTRACKI': {'htype':'raw', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'ACQSTART': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n 'ACQEND': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'GPSSTART': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'GPSEND': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'GPS-SHUT': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'DATE-OBS': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n 'MJD-OBS': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\n 'LST': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n 'UTC': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\n 'TIMESYS': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'ORIGIN': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'MPC-CODE': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n 'TELESCOP': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n 'CL-BASE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RH-MAST': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RH-DOME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RH-AIRCO': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RH-PIER': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PRESSURE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-PIER': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-DOME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-ROOF': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-AIRCO': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-MAST': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-STRUT': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-CRING': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-SPIDER': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-FWN': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-FWS': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-M2HOLD': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-GUICAM': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-M1': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-CRYWIN': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-CRYGET': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-CRYCP': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PRES-CRY': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'WINDAVE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'WINDGUST': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'WINDDIR': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'SITELAT': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'SITELONG': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'ELEVATIO': {'htype':'raw', 'dtype':int, 'DB':True, 'None_OK':True},\n #'WEATIME': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'FILTER': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n #'FILTERID': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'CCD-ID': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'CONTROLL': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'DETSPEED': {'htype':'raw', 'dtype':int, 'DB':True, 'None_OK':True},\n 'CCD-NW': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n 'CCD-NH': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\n 'INSTRUME': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'FOCUSPOS': {'htype':'raw', 'dtype':int, 'DB':True, 'None_OK':True},\n 'IMAGETYP': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\n 'OBJECT': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n 'AIRMASS': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\n 'ORIGFILE': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\n 'OBSERVER': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'ABOTVER': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'PROGNAME': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'PROGID': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'GUIDERST': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\n 'GUIDERFQ': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'TRAKTIME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'ADCX': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n 'ADCY': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\n #\n # full header\n 'BB-V': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\n 'BB-START': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\n 'KW-V': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\n 'LOG': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'LOG-IMA': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'N-INFNAN': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'XTALK-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'XTALK-F': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'NONLIN-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'NONLIN-F': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'GAIN-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'GAIN': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'GAIN1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'GAIN16': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'OS-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'BIASMEAN': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'BIASM1': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'BIASM16': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RDNOISE': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RDN1': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RDN16': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'BIAS1A0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'BIAS1A1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'VFITOK1': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'BIAS16A0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'BIAS16A1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'VFITOK16': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'MBIAS-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'MBIAS-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\n 'MB-NDAYS': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'SATURATE': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'NOBJ-SAT': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'MFLAT-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'MFLAT-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\n 'MF-NDAYS': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'MFRING-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'MFRING-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\n 'FRRATIO': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'COSMIC-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'NCOSMICS': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'SAT-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'NSATS': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'REDFILE': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\n 'MASKFILE': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\n 'S-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'S-V': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'S-NOBJ': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'S-FWHM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'S-FWSTD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'S-SEEING': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'S-SEESTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'S-ELONG': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'S-ELOSTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'S-BKG': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'S-BKGSTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'S-VIGNET': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'BKG-CORR': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'BKG-CHI2': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'BKG-CF1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'BKG-CF16': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'BKG-FDEG': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'BKG-FC0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'A-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'A-V': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'A-INDEX': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'A-PSCALE': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'A-PSCALX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'A-PSCALY': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'A-ROT': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'A-ROTX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'A-ROTY': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'A-CAT-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\n 'A-NAST': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'A-TNAST': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'A-NAMAX': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'A-DRA': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'A-DRASTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'A-DDEC': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'A-DDESTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PSF-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'PSF-V': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n 'PSF-RAD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-RADP': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-SIZE': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'PSF-FRAC': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-SAMP': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-CFGS': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'PSF-NOBJ': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'PSF-FIX': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'PSF-PLDG': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PSF-CHI2': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PSF-FWHM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-SEE': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PSF-PMIN': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-PMAX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-PMED': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-PSTD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-BMIN': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-BMAX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-BMED': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-BSTD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-EMNM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-EMXM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-EMDM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-ESTM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FMNM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FMXM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FMDM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FSTM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-EMNG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-EMXG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-EMDG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-ESTG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FMNG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FMXG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FMDG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PSF-FSTG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PC-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'PC-CAT-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\n 'PC-NCAL': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'PC-TNCAL': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PC-FNCAL': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PC-NCMAX': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PC-NCMIN': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PC-ZPFDG': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PC-ZPF0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PC-TNSUB': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PC-NSUB': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\n 'PC-MZPD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PC-MZPS': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PC-ZPDEF': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'PC-ZP': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PC-ZPSTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PC-EXTCO': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'AIRMASSC': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'RA-CNTR': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'DEC-CNTR': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'PC-AIRM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'NSIGMA': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'LIMEFLUX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\n 'LIMMAG': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'NOBJECTS': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\n 'RADECOFF': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\n 'FORMAT-P': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'DUMCAT': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'QC-FLAG': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\n 'DATEFILE': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\n #\n # transient header\n 'SWARP-P': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'SWARP-V': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\n 'Z-REF': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\n 'Z-DXYLOC': {'htype':'trans', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'Z-DX': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-DY': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-DXSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-DYSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-FNRLOC': {'htype':'trans', 'dtype':bool, 'DB':False, 'None_OK':True},\n 'Z-FNR': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-FNRSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-P': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'Z-V': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\n 'Z-SIZE': {'htype':'trans', 'dtype':int, 'DB':False, 'None_OK':True},\n 'Z-BSIZE': {'htype':'trans', 'dtype':int, 'DB':False, 'None_OK':True},\n 'Z-SCMED': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-SCSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'Z-FPEMED': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\n 'Z-FPESTD': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\n 'T-NSIGMA': {'htype':'trans', 'dtype':int, 'DB':True, 'None_OK':True},\n 'T-LFLUX': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\n 'T-NTRANS': {'htype':'trans', 'dtype':int, 'DB':True, 'None_OK':True},\n 'T-FTRANS': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-LMAG': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\n 'T-NFAKE': {'htype':'trans', 'dtype':int, 'DB':False, 'None_OK':True},\n 'T-FAKESN': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\n 'MC-P': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'MC-V': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\n 'MC-MODEL': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\n 'TDUMCAT': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\n 'TQC-FLAG': {'htype':'trans', 'dtype':str, 'DB':True, 'None_OK':False},\n }\n\n # read header of filename\n if isfile (filename):\n header = read_hdulist (filename, get_data=False, get_header=True)\n else:\n # return success=False if it does not exist\n log.warning ('file {} does not exist; not able to verify its header'\n .format(filename))\n return False\n\n\n # force [htypes] to be a list\n htypes_list = list(htypes)\n\n # loop keys in dict_head\n for key in dict_head.keys():\n\n # only check keywords with htype matching the input [htypes]\n if dict_head[key]['htype'] not in htypes_list:\n continue\n\n # check that key is present in header\n if key in header:\n\n # provide warning if dtype not as expected and header\n # keyword value is not 'None'\n if (dict_head[key]['dtype'] != type(header[key]) and\n header[key] != 'None'):\n log.warning ('dtype of keyword {}: {} does not match the '\n 'expected dtype: {} in header of {}'\n .format(key, type(header[key]),\n dict_head[key]['dtype'], filename))\n\n # if key goes to DataBase and value is 'None' or None\n # while 'None_OK' is False, raise an exception\n if (dict_head[key]['DB'] and not dict_head[key]['None_OK'] and\n (header[key] is None or header[key] == 'None')):\n msg = ('DataBase keyword {} not allowed to have \\'None\\' or '\n 'None value in header of {}'.format(key, filename))\n log.error (msg)\n raise ValueError (msg)\n\n\n else:\n msg = 'keyword {} not present in header of {}'.format(key, filename)\n # if keyword will be ingested into the database, raise an exception\n if dict_head[key]['DB']:\n log.error (msg)\n raise KeyError (msg)\n\n else:\n log.warning (msg)\n\n\n return","def read_data(filename):\n # Store debug mode\n debug = params.debug\n params.debug = None\n\n # Initialize dictionary\n header_dict = {}\n\n headername = filename + \".hdr\"\n\n with open(headername, \"r\") as f:\n # Replace characters for easier parsing\n hdata = f.read()\n hdata = hdata.replace(\",\\n\", \",\")\n hdata = hdata.replace(\"\\n,\", \",\")\n hdata = hdata.replace(\"{\\n\", \"{\")\n hdata = hdata.replace(\"\\n}\", \"}\")\n hdata = hdata.replace(\" \\n \", \"\")\n hdata = hdata.replace(\";\", \"\")\n hdata = hdata.split(\"\\n\")\n\n # Loop through and create a dictionary from the header file\n for i, string in enumerate(hdata):\n if ' = ' in string:\n header_data = string.split(\" = \")\n header_dict.update({header_data[0].rstrip(): header_data[1].rstrip()})\n elif ' : ' in string:\n header_data = string.split(\" : \")\n header_dict.update({header_data[0].rstrip(): header_data[1].rstrip()})\n\n # Reformat wavelengths\n header_dict[\"wavelength\"] = header_dict[\"wavelength\"].replace(\"{\", \"\")\n header_dict[\"wavelength\"] = header_dict[\"wavelength\"].replace(\"}\", \"\")\n header_dict[\"wavelength\"] = header_dict[\"wavelength\"].replace(\" \", \"\")\n header_dict[\"wavelength\"] = header_dict[\"wavelength\"].split(\",\")\n\n # Create dictionary of wavelengths\n wavelength_dict = {}\n for j, wavelength in enumerate(header_dict[\"wavelength\"]):\n wavelength_dict.update({float(wavelength): float(j)})\n\n # Replace datatype ID number with the numpy datatype\n dtype_dict = {\"1\": np.uint8, \"2\": np.int16, \"3\": np.int32, \"4\": np.float32, \"5\": np.float64, \"6\": np.complex64,\n \"9\": np.complex128, \"12\": np.uint16, \"13\": np.uint32, \"14\": np.uint64, \"15\": np.uint64}\n header_dict[\"data type\"] = dtype_dict[header_dict[\"data type\"]]\n\n # Read in the data from the file\n raw_data = np.fromfile(filename, header_dict[\"data type\"], -1)\n\n # Reshape the raw data into a datacube array\n array_data = raw_data.reshape(int(header_dict[\"lines\"]),\n int(header_dict[\"bands\"]),\n int(header_dict[\"samples\"])).transpose((0, 2, 1))\n\n if \"default bands\" in header_dict:\n header_dict[\"default bands\"] = header_dict[\"default bands\"].replace(\"{\", \"\")\n header_dict[\"default bands\"] = header_dict[\"default bands\"].replace(\"}\", \"\")\n default_bands = header_dict[\"default bands\"].split(\",\")\n\n pseudo_rgb = cv2.merge((array_data[:, :, int(default_bands[0])],\n array_data[:, :, int(default_bands[1])],\n array_data[:, :, int(default_bands[2])]))\n\n else:\n max_wavelength = max([float(i) for i in wavelength_dict.keys()])\n min_wavelength = min([float(i) for i in wavelength_dict.keys()])\n # Check range of available wavelength\n if max_wavelength >= 635 and min_wavelength <= 490:\n id_red = _find_closest(np.array([float(i) for i in wavelength_dict.keys()]), 710)\n id_green = _find_closest(np.array([float(i) for i in wavelength_dict.keys()]), 540)\n id_blue = _find_closest(np.array([float(i) for i in wavelength_dict.keys()]), 480)\n\n pseudo_rgb = cv2.merge((array_data[:, :, [id_blue]],\n array_data[:, :, [id_green]],\n array_data[:, :, [id_red]]))\n else:\n # Otherwise take 3 wavelengths, first, middle and last available wavelength\n id_red = int(header_dict[\"bands\"]) - 1\n id_green = int(id_red / 2)\n pseudo_rgb = cv2.merge((array_data[:, :, [0]],\n array_data[:, :, [id_green]],\n array_data[:, :, [id_red]]))\n\n # Gamma correct pseudo_rgb image\n pseudo_rgb = pseudo_rgb ** (1 / 2.2)\n # Scale each of the channels up to 255\n pseudo_rgb = cv2.merge((rescale(pseudo_rgb[:, :, 0]),\n rescale(pseudo_rgb[:, :, 1]),\n rescale(pseudo_rgb[:, :, 2])))\n\n max_wl = float(str(header_dict[\"wavelength\"][-1]).rstrip())\n min_wl = float(str(header_dict[\"wavelength\"][0]).rstrip())\n\n # Create an instance of the spectral_data class\n spectral_array = Spectral_data(array_data=array_data, max_wavelength=max_wl,\n min_wavelength=min_wl, d_type=header_dict[\"data type\"],\n wavelength_dict=wavelength_dict, samples=int(header_dict[\"samples\"]),\n lines=int(header_dict[\"lines\"]), interleave=header_dict[\"interleave\"],\n wavelength_units=header_dict[\"wavelength units\"], array_type=\"datacube\",\n pseudo_rgb=pseudo_rgb, filename=filename)\n\n # Reset debug mode\n params.debug = debug\n\n if params.debug == \"plot\":\n # Gamma correct pseudo_rgb image\n plot_image(pseudo_rgb)\n elif params.debug == \"print\":\n print_image(pseudo_rgb, os.path.join(params.debug_outdir, str(params.device) + \"_pseudo_rgb.png\"))\n\n return spectral_array","def __init__(self,\n resp_data,\n ):\n self.raw_data = resp_data.dict()\n\n # Packet parsed for host db processing\n self.parsed_data = {'insert': {'product': self.get_product_pack(),\n 'selling_status': self.get_selling_status_pack(),\n 'shipping_info': self.get_shipping_info_pack(),\n 'listing_info': self.get_listing_info_pack(),\n },\n 'items_received': resp_data.dict()['searchResult']['_count']}","def processLnkHeader(self):\n\t\t# Read LNK heaer from file\n\t\theader_raw = self.fpLnk.read(HEADER_LEN)\n\t\t# Build new dictionary containing header data\n\t\tself.header = parseStructuredData(header_raw, LNK_HEADER)","def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\n assert isinstance(header, CmdHeader)\n assert isinstance(raw_data, (bytes, bytearray))\n self.header = header\n self.raw_data = raw_data\n self.status, = unpack_from(\"<L\", raw_data)","def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\n super().__init__(header, raw_data)\n self.status, self.length = unpack_from('<2I', raw_data)","def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\n super().__init__(header, raw_data)\n self.status, self.length = unpack_from('<2I', raw_data)","def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\n super().__init__(header, raw_data)\n self.status, self.length = unpack_from('<2I', raw_data)","def load(self):\n basepath = os.path.dirname(os.path.abspath(__file__))\n filename = os.sep.join([basepath, c.FOLDER_JSON, c.FILE_GAME_VERSIONS])\n Handler.ALL_VERS_DATA = {} # reset known data; do not retain defunct information\n with open(filename, \"r\") as f:\n data = json.loads( f.read() )\n self.update(data)\n self._updated = False\n #for v,record in iteritems(Handler.ALL_VERS_DATA):\n # print(type(v), v)\n #for k,v in iteritems(record): ","def _read_headers(self):\n # Read the textual header.\n self._read_textual_header()\n # The next 400 bytes are from the Binary File Header.\n binary_file_header = self.file.read(400)\n bfh = SEGYBinaryFileHeader(binary_file_header, self.endian)\n self.binary_file_header = bfh\n self.data_encoding = self.binary_file_header.data_sample_format_code\n # If bytes 3506-3506 are not zero, an extended textual header follows\n # which is not supported so far.\n if bfh.number_of_3200_byte_ext_file_header_records_following != 0:\n msg = 'Extended textual headers are supported yet. ' + \\\n 'Please contact the developers.'\n raise NotImplementedError(msg)","def _build_header_dictionary(self):\n start = 0\n #print self.raw_data\n for a in range(20):\n redatapuller = re.compile(\"\\r\\n\\r\\n\\r\\n(?P<word>.*?)\\t.*?\\n\", re.DOTALL)\n m = redatapuller.search(self.raw_data[start:])\n if not(m):\n break\n self.header_dictionary[m.group(\"word\")] = start + m.end()\n if a==0:\n self.header_dictionary[\"main\"] = start + m.end()\n start += m.end()","def parse(data):\n try:\n header = decompress(data)\n version, game, save, log = parse_version(header, data)\n if version not in (Version.USERPATCH15, Version.DE, Version.HD):\n raise RuntimeError(f\"{version} not supported\")\n de = parse_de(header, version, save)\n hd = parse_hd(header, version, save)\n metadata, num_players = parse_metadata(header)\n map_ = parse_map(header, version)\n players, mod, device = parse_players(header, num_players, version, save)\n scenario = parse_scenario(header, num_players, version, save)\n lobby = parse_lobby(header, version, save)\n except (struct.error, zlib.error, AssertionError, MemoryError, ValueError) as e:\n raise RuntimeError(f\"could not parse: {e}\")\n return dict(\n version=version,\n game_version=game,\n save_version=save,\n log_version=log,\n players=players,\n map=map_,\n de=de,\n hd=hd,\n mod=de.get('dlc_ids') if de else mod,\n metadata=metadata,\n scenario=scenario,\n lobby=lobby,\n device=device\n )","def on_frame(self, frame: str) -> None:\n\n logger.debug(\"Frame: {}\".format(frame))\n try:\n message = json.loads(frame)\n except:\n logger.exception(\"Could not decode the JSON message\")\n self.transport.close()\n return\n\n mtype = message.get('type', None)\n self.log_state(mtype)\n if mtype == 'NEGOTIATION_RESPONSE':\n logger.debug(\"NEGOTIATION RESPONSE\")\n\n # Receive the chosen algorithms by the server \n self.process_negotiation_response(message)\n\n # Generate DH client private and public keys\n bytes_public_key,p,g,y=self.crypto.dh_client()\n \n message = {'type':'DH_PARAMETERS','parameters':{'p':p,'g':g,'public_key':str(bytes_public_key,'ISO-8859-1')}}\n self._send(message)\n self.state = STATE_DH\n \n return\n\n elif mtype == 'DH_PARAMETERS_RESPONSE':\n logger.debug('DH_PARAMETERS_RESPONSE')\n public_key=bytes(message['parameters']['public_key'],'ISO-8859-1')\n \n #Create shared key with the server public key\n self.crypto.create_shared_key(public_key)\n \n # Generate a symmetric key\n self.crypto.symmetric_key_gen()\n logger.debug(\"Key: {}\".format(self.crypto.symmetric_key))\n\n if self.state == STATE_ROTATION:\n self.state = STATE_OPEN\n self.send_file(self.file_name)\n \n elif self.state == STATE_DH:\n secure_message = self.encrypt_message({'type': 'OPEN', 'file_name': self.file_name})\n self._send(secure_message)\n self.send_mac()\n self.state = STATE_OPEN\n\n return\n\n elif mtype == 'INTEGRITY_CONTROL':\n flag = message['data']\n if flag == 'True':\n self._send(self.encrypt_message({'type': 'CLOSE'}))\n self.send_mac()\n logger.info(\"File transfer finished. Closing transport\")\n self.transport.close()\n\n elif mtype == 'OK': # Server replied OK. We can advance the state\n if self.state == STATE_OPEN:\n logger.info(\"Channel open\")\n self.send_file(self.file_name)\n elif self.state == STATE_DATA: # Got an OK during a message transfer.\n # Reserved for future use\n pass\n else:\n logger.warning(\"Ignoring message from server\")\n return\n\n elif mtype == 'ERROR':\n logger.warning(\"Got error from server: {}\".format(message.get('data', None)))\n \n else:\n logger.warning(\"Invalid message type\")\n\n logger.debug('Closing')\n self.transport.close()\n self.loop.stop()","def to_data(self) -> dict:\n return {'pingData': {'challenge': self.ping_challenge}}","def load_id_dict(self) -> None:\n sys.stdout.write(\"Loading identifier dictionaries...\\n\")\n assert os.path.exists(self.mapping_file)\n with open(self.mapping_file, 'r') as f:\n self.forward_map, self.backward_map = json.load(f)\n self.forward_map = {int(k): v for k, v in self.forward_map.items()}","def __init__(self, header=None):\r\n\r\n self.data = []","def _initialize_data(self):\n self.reset_count = 0\n self._idn_no_firmware = \"KEPCO,BOP 50-20,E1234,\"\n self._firmware = 2.6\n self._init_data()","def _init_data(self) -> None:\n self.dtype = dict()\n self.shape = dict()\n self.size = dict()\n self.attrs = dict()\n self.data_ptr = dict()\n\n if self.mode == 'r':\n for k in self.fp.keys():\n self.dtype[k] = self.fp[k].dtype\n self.shape[k] = self.fp[k].shape\n self.size[k] = self.fp[k].shape[0]\n self.data_ptr[k] = 0","def _read_chunk_head(self, data):\n if ';' in data:\n data, ext = data.split(';', 1)\n else:\n ext = ''\n\n length = int(data.strip(), 16)\n\n if length == 0:\n resp = self.current_response\n if resp._decompressor:\n resp.body += resp._decompressor.flush()\n del resp._decompressor\n\n self._stream.on_read = self._read_additional_headers\n resp._additional_headers = ''\n self._stream.read_delimiter = CRLF\n\n else:\n self._stream.on_read = self._read_chunk_body\n self._stream.read_delimiter = length + 2","def _load(self):\n # Extract the ASCII header (5 first lines)\n with open(self._xst_bin, 'rb') as f:\n header = list(islice(f, 0, 5))\n assert header[0] == b'HeaderStart\\n',\\\n 'Wrong header start'\n assert header[-1] == b'HeaderStop\\n',\\\n 'Wrong header stop'\n header = [s.decode('utf-8') for s in header]\n hd_size = sum([len(s) for s in header])\n\n # Parse informations into a metadata dictionnary\n keys = ['freq', 'ma', 'accu']\n search = ['Freq.List', 'Mr.List', 'accumulation']\n types = ['float64', 'int', 'int']\n for key, word, typ in zip(keys, search, types):\n for h in header:\n if word in h:\n self.meta[key] = np.array(\n h.split('=')[1].split(','),\n dtype=typ\n )\n\n # Deduce the dtype for decoding\n n_ma = self.meta['ma'].size\n n_sb = self.meta['freq'].size\n dtype = np.dtype(\n [('jd', 'float64'),\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\n )\n\n # Decoding the binary file\n tmp = np.memmap(\n filename=self._xst_bin,\n dtype='int8',\n mode='r',\n offset=hd_size\n )\n decoded = tmp.view(dtype)\n\n self.data = decoded['data'] / self.meta['accu']\n self.time = Time(decoded['jd'], format='jd', precision=0)\n\n return","def _decode(self):\n \n self.version = int(data_to_hex_str(self.packet[0])[2])\n self.header_len = int(data_to_hex_str(self.packet[0])[3]) * 4\n self.type_of_service = data_to_hex_str(self.packet[1:2])\n self.total_len = int(data_to_hex_str(self.packet[2:4]), 16)\n self.id = data_to_hex_str(self.packet[4:6])\n \n #parse the flags fields(reservedbit, don't fragment, more fragment)\n if ((ord(self.packet[6]) & (1 << 7)) != 0):\n self.flags_reservedbit = 1\n else:\n self.flags_reservedbit = 0\n #endof if\n \n if ((ord(self.packet[6]) & (1 << 6)) != 0):\n self.flags_dont_fragment = 1\n else:\n self.flags_dont_fragment = 0\n #endof if\n \n if ((ord(self.packet[6]) & (1 << 5)) != 0):\n self.flags_more_fragment = 1\n else:\n self.flags_more_fragment = 0\n #endof if\n \n #parse the offset field(in packet[6:7]): 00011111 & packet[6] (to filter flags) -->> get packet[6:7] in hex_str\n #tmp = str(31 & ord(self.packet[6]))\n self.fragment_offset = int(data_to_hex_str(self.packet[6:8]), 16)\n if (self.fragment_offset >= (1 << 13)):\n #take away the flags fields: 00011111 11111111 & self.fragment_offset\n self.fragment_offset = self.fragment_offset & ((1 << 13) - 1) \n \n self.TTL = ord(self.packet[8])\n self.protocol = IPPROTO[ord(self.packet[9])]\n self.header_checksum = data_to_hex_str(self.packet[10:12])\n \n self.src = str(ord(self.packet[12])) + '.' + str(ord(self.packet[13])) + '.' + \\\n str(ord(self.packet[14])) + '.' + str(ord(self.packet[15]))\n self.dst = str(ord(self.packet[16])) + '.' + str(ord(self.packet[17])) + '.' + \\\n str(ord(self.packet[18])) + '.' + str(ord(self.packet[19]))\n \n if (self.header_len > 20):\n self.opt_paddings = self.packet[20 : (self.header_len)]","def act_on_header(self, dct):\n self.socket.send_pyobj(dict(dct), protocol=2)","def deserialize(self, reader: serialization.BinaryReader) -> None:\n self.index_start = reader.read_uint32()\n self.count = reader.read_int16()\n if self.count < 1 or self.count == 0 or self.count > HeadersPayload.MAX_HEADERS_COUNT:\n raise ValueError(\"Deserialization error - invalid count\")","def _parseHeader(self):\n # Big or little endian for the header.\n self._getEndianess()\n # Read the fixed header.\n self._readFixedHeader()\n # Get the present blockettes.\n self._getBlockettes()\n # Calculate the starttime.\n self._calculateStarttime()","def _decode1(self, body, data):\r\n if \" \" in body:\r\n evtype,body = body.split(\" \",1)\r\n else:\r\n evtype,body = body,\"\"\r\n evtype = evtype.upper()\r\n if evtype == \"CIRC\":\r\n m = re.match(r\"(\\d+)\\s+(\\S+)(\\s\\S+)?(\\s\\S+)?(\\s\\S+)?(\\s\\S+)?\", body)\r\n if not m:\r\n raise ProtocolError(\"CIRC event misformatted.\")\r\n ident,status,path,purpose,reason,remote = m.groups()\r\n ident = int(ident)\r\n if path:\r\n if \"PURPOSE=\" in path:\r\n remote = reason\r\n reason = purpose\r\n purpose=path\r\n path=[]\r\n elif \"REASON=\" in path:\r\n remote = reason\r\n reason = path\r\n purpose = \"\"\r\n path=[]\r\n else:\r\n path_verb = path.strip().split(\",\")\r\n path = []\r\n for p in path_verb:\r\n path.append(p.replace(\"~\", \"=\").split(\"=\")[0])\r\n else:\r\n path = []\r\n\r\n if purpose and \"REASON=\" in purpose:\r\n remote=reason\r\n reason=purpose\r\n purpose=\"\"\r\n\r\n if purpose: purpose = purpose[9:]\r\n if reason: reason = reason[8:]\r\n if remote: remote = remote[15:]\r\n event = CircuitEvent(evtype, ident, status, path, purpose, reason,\r\n remote, body)\r\n elif evtype == \"STREAM\":\r\n #plog(\"DEBUG\", \"STREAM: \"+body)\r\n m = re.match(r\"(\\S+)\\s+(\\S+)\\s+(\\S+)\\s+(\\S+)?:(\\d+)(\\sREASON=\\S+)?(\\sREMOTE_REASON=\\S+)?(\\sSOURCE=\\S+)?(\\sSOURCE_ADDR=\\S+)?(\\s+PURPOSE=\\S+)?\", body)\r\n if not m:\r\n raise ProtocolError(\"STREAM event misformatted.\")\r\n ident,status,circ,target_host,target_port,reason,remote,source,source_addr,purpose = m.groups()\r\n ident,circ = map(int, (ident,circ))\r\n if not target_host: # This can happen on SOCKS_PROTOCOL failures\r\n target_host = \"(none)\"\r\n if reason: reason = reason[8:]\r\n if remote: remote = remote[15:]\r\n if source: source = source[8:]\r\n if source_addr: source_addr = source_addr[13:]\r\n if purpose:\r\n purpose = purpose.lstrip()\r\n purpose = purpose[8:]\r\n event = StreamEvent(evtype, ident, status, circ, target_host,\r\n int(target_port), reason, remote, source, source_addr,\r\n purpose, body)\r\n elif evtype == \"ORCONN\":\r\n m = re.match(r\"(\\S+)\\s+(\\S+)(\\sAGE=\\S+)?(\\sREAD=\\S+)?(\\sWRITTEN=\\S+)?(\\sREASON=\\S+)?(\\sNCIRCS=\\S+)?\", body)\r\n if not m:\r\n raise ProtocolError(\"ORCONN event misformatted.\")\r\n target, status, age, read, wrote, reason, ncircs = m.groups()\r\n\r\n #plog(\"DEBUG\", \"ORCONN: \"+body)\r\n if ncircs: ncircs = int(ncircs[8:])\r\n else: ncircs = 0\r\n if reason: reason = reason[8:]\r\n if age: age = int(age[5:])\r\n else: age = 0\r\n if read: read = int(read[6:])\r\n else: read = 0\r\n if wrote: wrote = int(wrote[9:])\r\n else: wrote = 0\r\n event = ORConnEvent(evtype, status, target, age, read, wrote,\r\n reason, ncircs, body)\r\n elif evtype == \"STREAM_BW\":\r\n m = re.match(r\"(\\d+)\\s+(\\d+)\\s+(\\d+)\", body)\r\n if not m:\r\n raise ProtocolError(\"STREAM_BW event misformatted.\")\r\n event = StreamBwEvent(evtype, body, *m.groups())\r\n elif evtype == \"BW\":\r\n m = re.match(r\"(\\d+)\\s+(\\d+)\", body)\r\n if not m:\r\n raise ProtocolError(\"BANDWIDTH event misformatted.\")\r\n read, written = map(long, m.groups())\r\n event = BWEvent(evtype, read, written, body)\r\n elif evtype in (\"DEBUG\", \"INFO\", \"NOTICE\", \"WARN\", \"ERR\"):\r\n event = LogEvent(evtype, body)\r\n elif evtype == \"NEWDESC\":\r\n ids_verb = body.split(\" \")\r\n ids = []\r\n for i in ids_verb:\r\n ids.append(i.replace(\"~\", \"=\").split(\"=\")[0].replace(\"$\",\"\"))\r\n event = NewDescEvent(evtype, ids, body)\r\n elif evtype == \"ADDRMAP\":\r\n # TODO: Also parse errors and GMTExpiry\r\n m = re.match(r'(\\S+)\\s+(\\S+)\\s+(\\\"[^\"]+\\\"|\\w+)', body)\r\n if not m:\r\n raise ProtocolError(\"ADDRMAP event misformatted.\")\r\n fromaddr, toaddr, when = m.groups()\r\n if when.upper() == \"NEVER\": \r\n when = None\r\n else:\r\n when = time.strptime(when[1:-1], \"%Y-%m-%d %H:%M:%S\")\r\n event = AddrMapEvent(evtype, fromaddr, toaddr, when, body)\r\n elif evtype == \"NS\":\r\n event = NetworkStatusEvent(evtype, parse_ns_body(data), data)\r\n elif evtype == \"NEWCONSENSUS\":\r\n event = NewConsensusEvent(evtype, parse_ns_body(data), data)\r\n elif evtype == \"BUILDTIMEOUT_SET\":\r\n m = re.match(\r\n r\"(\\S+)\\sTOTAL_TIMES=(\\d+)\\sTIMEOUT_MS=(\\d+)\\sXM=(\\d+)\\sALPHA=(\\S+)\\sCUTOFF_QUANTILE=(\\S+)\",\r\n body)\r\n set_type, total_times, timeout_ms, xm, alpha, quantile = m.groups()\r\n event = BuildTimeoutSetEvent(evtype, set_type, int(total_times),\r\n int(timeout_ms), int(xm), float(alpha),\r\n float(quantile), body)\r\n elif evtype == \"GUARD\":\r\n m = re.match(r\"(\\S+)\\s(\\S+)\\s(\\S+)\", body)\r\n entry, guard, status = m.groups()\r\n event = GuardEvent(evtype, entry, guard, status, body)\r\n elif evtype == \"TORCTL_TIMER\":\r\n event = TimerEvent(evtype, data)\r\n else:\r\n event = UnknownEvent(evtype, body)\r\n\r\n return event","def prepare_data(self):\n self.empty = 'yes' if len(self.data) == 0 else 'no'\n self._keys = sorted(key for key in self.data.keys())\n\n # Validate the keys\n for key in self._keys:\n if not is_valid_matlab_field_label(key):\n msg = \"'{}' is not a valid MATLAB field label\".format(key)\n raise ValueError(msg)\n self.field_names = \" \".join(self._keys)","def __read_json(self):\n try:\n with open(self.X_path) as Xfile, open(self.Y_path) as Yfile:\n print('Starting to read the json files')\n t1 = time.perf_counter()\n Ydata = [obj[0] for obj in json.load(Yfile)]\n Xdata = json.load(Xfile)\n # Note: some samples (31) are empty\n # Xdata = [obj for obj in json.load(Xfile) if len(obj)>1]\n for record in Xdata:\n del record['sha256'] # Remove signature from features\n t2 = time.perf_counter()\n print(f'Finished reading the json files. '\n f'Elapsed time: {(t2 - t1) / 60.0} minutes')\n except Exception as e:\n print(f'Exception while reading json files ({e})')\n raise e\n\n self.Y = np.array(Ydata, dtype=np.uint8)\n print('Y.shape', self.Y.shape)\n self.vectorizer = DictVectorizer(sparse=True, dtype=np.uint8)\n self.X = self.vectorizer.fit_transform(Xdata)\n print('X.shape (All):', self.X.shape)\n # If feature selection is applied\n if self.n_features != -1:\n support = SelectKBest(chi2, k=self.n_features).fit(self.X, self.Y)\n self.vectorizer.restrict(support.get_support())\n self.X = support.transform(self.X)\n print('X.shape (Reduced):', self.X.shape)\n\n self.feature_names = self.vectorizer.feature_names_\n malware_idx = np.where(self.Y == 1)[0]\n self.X_malware = self.X[malware_idx, :]\n goodware_idx = np.where(self.Y == 0)[0]\n self.X_goodware = self.X[goodware_idx, :]\n\n\n try:\n with shelve.open(self.shelf_path, 'c') as shelf:\n print('Saving data to a shelf')\n shelf['X'] = self.X\n shelf['X_malware'] = self.X_malware\n shelf['X_goodware'] = self.X_goodware\n shelf['Y'] = self.Y\n shelf['feature_names'] = self.feature_names\n print('Finished saving the shelf')\n except Exception as e:\n print(f'Exception while saving data to a shelf ({e})')","def __init__(self, data: dict):\n super().__init__(data)\n self._supports_validation = False\n self._ping_data_raw = data['pingData']","def _decode_5104(data):\n\n text = []\n start_byte = 0\n while start_byte + 2 < len(data):\n tag = data[start_byte:start_byte + 2]\n if tag == b'#u':\n start_byte += 2\n text_size = struct.unpack(\n '<h', data[start_byte:start_byte + 2])[0]\n start_byte += 2\n text.append(data[start_byte:start_byte + text_size].decode('utf8'))\n start_byte += text_size\n start_byte += 6\n elif tag == b'$u':\n start_byte += 2\n text.append(struct.unpack(\n '<h', data[start_byte:start_byte + 2])[0])\n start_byte += 2\n start_byte += 6\n elif tag == b',u':\n start_byte += 2\n text.append(struct.unpack(\n '<h', data[start_byte:start_byte + 2])[0])\n start_byte += 2\n else:\n start_byte += 1\n\n return {'analyst': text[0],\n 'date': text[2],\n 'image_name': text[4],\n 'instrument_model': text[5],\n 'instrument_serial_number': text[6],\n 'instrument_software_version': text[7],\n 'accumulations': text[9],\n 'detector': text[11],\n 'source': text[12],\n 'beam_splitter': text[13],\n 'apodization': text[15],\n 'spectrum_type': text[16],\n 'beam_type': text[17],\n 'phase_correction': text[20],\n 'ir_accessory': text[26],\n 'igram_type': text[28],\n 'scan_direction': text[29],\n 'background_scans': text[32]}","def get_json(self):\n data = {}\n data['ip'] = self.ip\n\n try:\n data['country'] = self.processedvtdata[\"country\"]\n except KeyError:\n data['country'] = 'None'\n try:\n data['as'] = self.processedvtdata[\"as_owner\"]\n except KeyError:\n data['as'] = 'None'\n try:\n data['rdns'] = self.processedvtdata[\"self.reversedns\"]\n except KeyError:\n data['rdns'] = 'None'\n try:\n data['label'] = self.expertlabel\n except AttributeError:\n data['label'] = ''\n\n # geodata\n #{\"status\":\"success\",\"country\":\"Yemen\",\"countryCode\":\"YE\",\"region\":\"SA\",\"regionName\":\"Amanat Alasimah\",\"city\":\"Sanaa\",\"zip\":\"\",\"lat\":15.3522,\"lon\":44.2095,\"timezone\":\"Asia/Aden\",\"isp\":\"Public Telecommunication Corporation\",\"org\":\"YemenNet\",\"as\":\"AS30873 Public Telecommunication Corporation\",\"query\":\"134.35.218.63\"}\n if self.geodata:\n data['geodata'] = self.geodata\n \n # vt resolutions. Is a list\n data['vt'] = {}\n try:\n if self.processedvtdata['resolutions'] != 'None':\n data['vt']['resolutions'] = []\n for count, resolution_tuple in enumerate(self.processedvtdata['resolutions']):\n if count >= self.amount_to_print:\n break\n temp = {}\n temp['date'] = resolution_tuple[0]\n temp['domain'] = resolution_tuple[1]\n data['vt']['resolutions'].append(temp)\n except KeyError:\n pass\n\n # vt urls. Is a list\n try:\n if self.processedvtdata['detected_urls'] != 'None':\n data['vt']['detected_urls'] = []\n for count, url_tuple in enumerate(self.processedvtdata['detected_urls']):\n if count >= self.amount_to_print:\n break\n temp = {}\n temp['date'] = url_tuple[0]\n temp['url'] = url_tuple[1][0]\n temp['detections'] = str(url_tuple[1][1]) + '/' + str(url_tuple[1][2])\n data['vt']['detected_urls'].append(temp)\n except KeyError:\n pass\n\n\n # vt detected communicating samples. Is a list\n try:\n if self.processedvtdata['detected_communicating_samples'] != 'None':\n data['vt']['detected_communicating_samples'] = []\n for count, communcating_tuple in enumerate(self.processedvtdata['detected_communicating_samples']):\n if count >= self.amount_to_print:\n break\n temp = {}\n temp['date'] = communcating_tuple[0]\n temp['detections'] = str(communcating_tuple[1][0]) + '/' + str(communcating_tuple[1][1])\n temp['sha256'] = communcating_tuple[1][2]\n data['vt']['detected_communicating_samples'].append(temp)\n except AttributeError:\n pass\n\n # vt detected downloaded samples. Is a list\n try:\n if self.processedvtdata['detected_downloaded_samples'] != 'None':\n data['vt']['detected_downloaded_samples'] = []\n for count, detected_tuple in enumerate(self.processedvtdata['detected_downloaded_samples']):\n if count >= self.amount_to_print:\n break\n temp = {}\n temp['date'] = detected_tuple[0]\n temp['detections'] = str(detected_tuple[1][0]) + '/' + str(detected_tuple[1][1])\n temp['sha256'] = detected_tuple[1][2]\n data['vt']['detected_downloaded_samples'].append(temp)\n except AttributeError:\n pass\n\n # vt referrer downloaded samples. Is a list\n try:\n if self.processedvtdata['detected_referrer_samples'] != 'None':\n data['vt']['detected_referrer_samples'] = []\n for count, referrer_tuple in enumerate(self.processedvtdata['detected_referrer_samples']):\n if count >= self.amount_to_print:\n break\n temp = {}\n temp['sha256'] = referrer_tuple[0]\n temp['detections'] = str(referrer_tuple[1][0]) + '/' + str(referrer_tuple[1][1])\n data['vt']['detected_referrer_samples'].append(temp)\n except AttributeError:\n pass\n\n # pt data\n data['pt'] = {}\n if self.processedptdata:\n count = 0\n data['pt']['passive_dns'] = []\n for result in self.processedptdata_results:\n if count >= self.amount_to_print:\n break\n temp = {}\n temp['lastseen'] = result[0]\n temp['firstseen'] = result[1][0]\n temp['hostname'] = result[1][1]\n data['pt']['passive_dns'].append(temp)\n count += 1\n\n # shodan data\n try:\n if self.shodandata:\n data['shodan'] = self.shodandata\n except AttributeError:\n pass\n\n data = json.dumps(data)\n return data","def load_data(self) -> None:","def __init__(self):\n self.data = []\n self.record = {}","def _readHeader(self):\n self.ControllerVersion = self._readInt(0)\n self.LogicOutput = self._readInt(2)\n self.AppHiCapLowNoise = self._readInt(4)\n self.TimingMode = self._readInt(8)\n self.Exposure = self._readFloat(10)\n self.DetTemperature = self._readFloat(36)\n self.DetectorType = self._readInt(40)\n self.TriggerDiode = self._readInt(44)\n self.DelayTime = self._readFloat(46)\n self.ShutterControl = self._readInt(50)\n self.AbsorbLive = self._readInt(52)\n self.AbsorbMode = self._readInt(54)\n self.CanDoVirtualChip = self._readInt(56)\n self.ThresholdMinLive = self._readInt(58)\n self.ThresholdMin = self._readFloat(60)\n self.ThresholdMaxLive = self._readInt(64)\n self.ThresholdMax = self._readFloat(66)\n self.ADCOffset = self._readInt(188)\n self.ADCRate = self._readInt(190)\n self.ADCType = self._readInt(192)\n self.ADCRes = self._readInt(194)\n self.ADCBitAdj = self._readInt(196)\n self.Gain = self._readInt(198)\n self.GeometricOps = self._readInt(600)","def startProtocol(self):\n #init state trackers\n self.initialMessageSentToServer = False\n self.sentPacketToPeerPublicAndPrivateAddresses = False\n self.mirroredBackWhicheverPacketMadeIt = False\n self.peerConnectionEstablished = False\n #init peer info\n self.peerPublicAddress = None\n self.peerPrivateAddress = None\n self.peerAddress = None \n self.peerUserName = None\n\n #talk to handshake server\n if iAmServer:\n data = {\n 'registering-server': True,\n 'user-name': userName,\n 'private-ip': myPrivateIp, \n 'private-port': myPrivatePort\n }\n else:\n data = {\n 'registering-server': False,\n 'user-name': userName,\n 'private-ip': myPrivateIp, \n 'private-port': myPrivatePort,\n 'server-name' : serverName,\n 'server-password': serverPassword,\n }\n self.transport.write(json.dumps(data).encode(), (HANDSHAKE_SERVER_IP, HANDSHAKE_SERVER_PORT))\n print(\"sent initial message to server \" + HANDSHAKE_SERVER_IP + \":\" + str(HANDSHAKE_SERVER_PORT))\n self.initialMessageSentToServer = True","def _decode(self, input_dict):\n pass","def _read_header_line_2(lines: list) -> dict:\n fields = (\n \"detection_status\",\n \"warning\",\n \"cloud_base_data\",\n \"warning_flags\",\n )\n values = [[line[0], line[1], line[3:20], line[21:].strip()] for line in lines]\n return values_to_dict(fields, values)","def __init__(self, fileName):\n self.recordDict = {}\n for line in open(fileName, 'r') :\n sipRecord = json.loads(line)\n self.recordDict[sipRecord['addressOfRecord']] = line","def __process_ethframe(self, eth_header: bytes) -> Dict[str, Any]:\n eth = struct.unpack('!6s6sH', eth_header)\n eth_protocol = socket.ntohs(eth[2])\n\n return {\n 'header_length': Sniffer.ETH_HEADER_LENGTH,\n 'protocol': eth_protocol,\n }"],"string":"[\n \"def _read_header(\\n self, header, filename, run_check_acceptability=True, background_lsts=True\\n ):\\n # get telescope information\\n latitude = header[\\\"latitude\\\"][()]\\n longitude = header[\\\"longitude\\\"][()]\\n altitude = header[\\\"altitude\\\"][()]\\n self.telescope_location_lat_lon_alt_degrees = (latitude, longitude, altitude)\\n self.instrument = header[\\\"instrument\\\"][()].tobytes().decode(\\\"utf8\\\")\\n self.telescope_name = header[\\\"telescope_name\\\"][()].tobytes().decode(\\\"utf8\\\")\\n\\n # get source information\\n self.object_name = header[\\\"object_name\\\"][()].tobytes().decode(\\\"utf8\\\")\\n\\n # set history appropriately\\n self.history = header[\\\"history\\\"][()].tobytes().decode(\\\"utf8\\\")\\n if not uvutils._check_history_version(self.history, self.pyuvdata_version_str):\\n self.history += self.pyuvdata_version_str\\n\\n # check for vis_units\\n if \\\"vis_units\\\" in header:\\n self.vis_units = header[\\\"vis_units\\\"][()].tobytes().decode(\\\"utf8\\\")\\n else:\\n # default to uncalibrated data\\n self.vis_units = \\\"UNCALIB\\\"\\n\\n # check for optional values\\n if \\\"dut1\\\" in header:\\n self.dut1 = float(header[\\\"dut1\\\"][()])\\n if \\\"earth_omega\\\" in header:\\n self.earth_omega = float(header[\\\"earth_omega\\\"][()])\\n if \\\"gst0\\\" in header:\\n self.gst0 = float(header[\\\"gst0\\\"][()])\\n if \\\"rdate\\\" in header:\\n self.rdate = header[\\\"rdate\\\"][()].tobytes().decode(\\\"utf8\\\")\\n if \\\"timesys\\\" in header:\\n self.timesys = header[\\\"timesys\\\"][()].tobytes().decode(\\\"utf8\\\")\\n if \\\"x_orientation\\\" in header:\\n self.x_orientation = header[\\\"x_orientation\\\"][()].tobytes().decode(\\\"utf8\\\")\\n if \\\"blt_order\\\" in header:\\n blt_order_str = header[\\\"blt_order\\\"][()].tobytes().decode(\\\"utf8\\\")\\n self.blt_order = tuple(blt_order_str.split(\\\", \\\"))\\n if self.blt_order == (\\\"bda\\\",):\\n self._blt_order.form = (1,)\\n\\n if \\\"antenna_diameters\\\" in header:\\n self.antenna_diameters = header[\\\"antenna_diameters\\\"][()]\\n if \\\"uvplane_reference_time\\\" in header:\\n self.uvplane_reference_time = int(header[\\\"uvplane_reference_time\\\"][()])\\n if \\\"eq_coeffs\\\" in header:\\n self.eq_coeffs = header[\\\"eq_coeffs\\\"][()]\\n if \\\"eq_coeffs_convention\\\" in header:\\n self.eq_coeffs_convention = (\\n header[\\\"eq_coeffs_convention\\\"][()].tobytes().decode(\\\"utf8\\\")\\n )\\n\\n # check for phasing information\\n self.phase_type = header[\\\"phase_type\\\"][()].tobytes().decode(\\\"utf8\\\")\\n if self.phase_type == \\\"phased\\\":\\n self._set_phased()\\n self.phase_center_ra = float(header[\\\"phase_center_ra\\\"][()])\\n self.phase_center_dec = float(header[\\\"phase_center_dec\\\"][()])\\n self.phase_center_epoch = float(header[\\\"phase_center_epoch\\\"][()])\\n if \\\"phase_center_frame\\\" in header:\\n self.phase_center_frame = (\\n header[\\\"phase_center_frame\\\"][()].tobytes().decode(\\\"utf8\\\")\\n )\\n elif self.phase_type == \\\"drift\\\":\\n self._set_drift()\\n else:\\n self._set_unknown_phase_type()\\n\\n # get antenna arrays\\n # cast to native python int type\\n self.Nants_data = int(header[\\\"Nants_data\\\"][()])\\n self.Nants_telescope = int(header[\\\"Nants_telescope\\\"][()])\\n self.ant_1_array = header[\\\"ant_1_array\\\"][:]\\n self.ant_2_array = header[\\\"ant_2_array\\\"][:]\\n self.antenna_names = [\\n n.tobytes().decode(\\\"utf8\\\") for n in header[\\\"antenna_names\\\"][:]\\n ]\\n self.antenna_numbers = header[\\\"antenna_numbers\\\"][:]\\n self.antenna_positions = header[\\\"antenna_positions\\\"][:]\\n\\n # set telescope params\\n try:\\n self.set_telescope_params()\\n except ValueError as ve:\\n warnings.warn(str(ve))\\n\\n # get baseline array\\n self.baseline_array = self.antnums_to_baseline(\\n self.ant_1_array, self.ant_2_array\\n )\\n self.Nbls = len(np.unique(self.baseline_array))\\n\\n # get uvw array\\n self.uvw_array = header[\\\"uvw_array\\\"][:, :]\\n\\n # get time information\\n self.time_array = header[\\\"time_array\\\"][:]\\n integration_time = header[\\\"integration_time\\\"]\\n self.integration_time = integration_time[:]\\n proc = None\\n if \\\"lst_array\\\" in header:\\n self.lst_array = header[\\\"lst_array\\\"][:]\\n # check that lst_array in file is self-consistent\\n if run_check_acceptability:\\n (\\n latitude,\\n longitude,\\n altitude,\\n ) = self.telescope_location_lat_lon_alt_degrees\\n lst_array = uvutils.get_lst_for_time(\\n self.time_array, latitude, longitude, altitude\\n )\\n if not np.all(\\n np.isclose(\\n self.lst_array,\\n lst_array,\\n rtol=self._lst_array.tols[0],\\n atol=self._lst_array.tols[1],\\n )\\n ):\\n warnings.warn(\\n \\\"LST values stored in {file} are not self-consistent \\\"\\n \\\"with time_array and telescope location. Consider \\\"\\n \\\"recomputing with utils.get_lst_for_time.\\\".format(file=filename)\\n )\\n else:\\n # compute lst_array from time_array and telescope location\\n proc = self.set_lsts_from_time_array(background=background_lsts)\\n\\n # get frequency information\\n self.freq_array = header[\\\"freq_array\\\"][:, :]\\n self.channel_width = float(header[\\\"channel_width\\\"][()])\\n self.spw_array = header[\\\"spw_array\\\"][:]\\n\\n # get polarization information\\n self.polarization_array = header[\\\"polarization_array\\\"][:]\\n\\n # get data shapes\\n self.Nfreqs = int(header[\\\"Nfreqs\\\"][()])\\n self.Npols = int(header[\\\"Npols\\\"][()])\\n self.Ntimes = int(header[\\\"Ntimes\\\"][()])\\n self.Nblts = int(header[\\\"Nblts\\\"][()])\\n self.Nspws = int(header[\\\"Nspws\\\"][()])\\n\\n # get extra_keywords\\n if \\\"extra_keywords\\\" in header:\\n self.extra_keywords = {}\\n for key in header[\\\"extra_keywords\\\"].keys():\\n if header[\\\"extra_keywords\\\"][key].dtype.type in (np.string_, np.object_):\\n self.extra_keywords[key] = (\\n header[\\\"extra_keywords\\\"][key][()].tobytes().decode(\\\"utf8\\\")\\n )\\n else:\\n self.extra_keywords[key] = header[\\\"extra_keywords\\\"][key][()]\\n\\n if proc is not None:\\n # if lsts are in the background wait for them to return\\n proc.join()\\n\\n return\",\n \"def _main_header(self, hdr):\\n d = {}\\n # Called readDefAnalysis in OpenMIMS\\n d['sample type'], d['data included'], d['sample x'], d['sample y'], \\\\\\n d['analysis type'], d['user name'], d['sample z'], date, time = \\\\\\n unpack(self._bo + '4i 32s 16s i 12x 16s 16s', hdr.read(112))\\n\\n d['data included'] = bool(d['data included'])\\n d['user name'] = self._cleanup_string(d['user name'])\\n d['analysis type'] = self._cleanup_string(d['analysis type']).lower()\\n date = self._cleanup_string(date)\\n time = self._cleanup_string(time)\\n d['date'] = self._cleanup_date(date + ' ' + time)\\n\\n if self.header['file type'] in (27, 29, 39):\\n # Called MaskImage/readMaskIm in OpenMIMS\\n d['original filename'], d['analysis duration'], d['frames'], \\\\\\n d['scan type'], d['magnification'], d['size type'], \\\\\\n d['size detector'], d['beam blanking'], d['presputtering'], \\\\\\n d['presputtering duration'] = \\\\\\n unpack(self._bo + '16s 3i 3h 2x 3i', hdr.read(48))\\n\\n d['AutoCal'] = self._autocal(hdr)\\n d['HVControl'] = {}\\n d['HVControl']['hvcontrol enabled'] = False\\n\\n elif self.header['file type'] in (22, 41):\\n # Called MaskSampleStageImage/readMaskIss in OpenMIMS\\n d['original filename'], d['analysis duration'], d['scan type'], \\\\\\n d['steps'], d['step size x'], d['step size y'], d['step size?'], \\\\\\n d['step waittime'], d['frames'], d['beam blanking'], \\\\\\n d['presputtering'], d['presputtering duration'] = \\\\\\n unpack(self._bo + '16s 6i d 4i', hdr.read(64))\\n\\n d['scan type'] = _stage_scan_types.get(d['scan type'], str(d['scan type']))\\n\\n d['AutoCal'] = self._autocal(hdr)\\n d['HVControl'] = self._hvcontrol(hdr)\\n # Don't know if this unused byte needs to go after HVControl or after SigRef.\\n hdr.seek(4, 1)\\n\\n elif self.header['file type'] in (21, 26):\\n # Not in OpenMIMS\\n # this bit same as image, 1 extra unused/unknown\\n d['original filename'], d['analysis duration'], d['frames'], \\\\\\n d['scan type'], d['magnification'], d['size type'], \\\\\\n d['size detector'], d['beam blanking'], d['presputtering'], \\\\\\n d['presputtering duration'] = \\\\\\n unpack(self._bo + '16s 4x 3i 3h 2x 3i', hdr.read(52))\\n\\n # this bit same as stage scan\\n d['AutoCal'] = self._autocal(hdr)\\n d['HVControl'] = self._hvcontrol(hdr)\\n\\n # 24 bytes unknown, not sure if they go here or before AutoCal\\n hdr.seek(24, 1)\\n\\n elif self.header['file type'] == 31:\\n # Don't know if this is correct, all 0s anyway\\n d['original filename'], d['scan type'], \\\\\\n d['beam blanking'], d['presputtering'] = \\\\\\n unpack(self._bo + '16s 3i 4x', hdr.read(32))\\n\\n elif self.header['file type'] == 35:\\n d['original filename'], d['scan type'], d['analysis duration'], \\\\\\n d['frames'], d['beam blanking'], d['presputtering'] = \\\\\\n unpack(self._bo + '16s 5i 40x', hdr.read(76))\\n\\n d['AutoCal'] = self._autocal(hdr)\\n d['HVControl'] = self._hvcontrol(hdr)\\n\\n else:\\n raise TypeError('What type of image are you? {}'.format(self.header['file type']))\\n\\n # Continue main header for all types\\n d['SigRef'] = self._sigref(hdr)\\n d['masses'] = unpack(self._bo + 'i', hdr.read(4))[0]\\n\\n # scan type is set for stage scan analysis, set others\\n if isinstance(d['scan type'], int):\\n if d['scan type'] == 0:\\n d['scan type'] = ''\\n else:\\n d['scan type'] = str(d['scan type'])\\n\\n d['beam blanking'] = bool(d['beam blanking'])\\n d['presputtering'] = bool(d['presputtering'])\\n d['original filename'] = self._cleanup_string(d['original filename'])\\n\\n if self.header['file type'] in (21, 26, 27, 29, 35, 39):\\n if self.header['file version'] >= 4108:\\n n = 60\\n else:\\n n = 10\\n elif self.header['file type'] in (22, 31, 40, 41):\\n n = 20\\n else:\\n n = 0\\n\\n # Not sure what this is, memory pointers? Not needed.\\n # d['mass table ptr'] = unpack(self._bo + 2*n*'h', hdr.read(n*4))\\n hdr.seek(n*4, 1)\\n\\n if self.header['file type'] in (21, 22, 26, 40, 41, 35):\\n hdr.seek(4, 1) # 4 bytes unused\\n\\n # Mass table, dict by species label.\\n d['MassTable'] = collections.OrderedDict()\\n for m in range(d['masses']):\\n mi = {}\\n mi['trolley index'], unknown, mi['mass'], mi['matrix or trace'], \\\\\\n mi['detector'], mi['wait time'], mi['frame count time'] = \\\\\\n unpack(self._bo + '2i d 2i 2d', hdr.read(40))\\n\\n if self.header['file type'] == 31:\\n if d['analysis type'].endswith('trolley step scan'):\\n # start and end are in mm, step is in μm; convert to mm\\n mi['radius start'], mi['radius end'], \\\\\\n mi['radius step'], mi['b field bits'] = \\\\\\n unpack(self._bo + '3d i', hdr.read(28))\\n mi['radius step'] /= 1000\\n else:\\n mi['voltage start'], mi['voltage end'], \\\\\\n mi['voltage step'], mi['b field bits'] = \\\\\\n unpack(self._bo + '3d i', hdr.read(28))\\n else:\\n mi['offset'], mi['b field bits'] = unpack(self._bo + '2i', hdr.read(8))\\n\\n mi.update(self._species(hdr))\\n\\n if self.header['file type'] == 31:\\n hdr.seek(4, 1)\\n\\n # Add correction controls, my own addition.\\n mi['background corrected'] = False\\n mi['deadtime corrected'] = False\\n mi['yield corrected'] = False\\n\\n label = mi.pop('label')\\n # This is true for NS50L and file version 4108.\\n # Anywhere else different?\\n # Maybe confirm this with the Trolleys dict,\\n # there is an Esi trolley.\\n if mi['trolley index'] == 8:\\n label = 'SE'\\n\\n d['MassTable'][label] = mi\\n\\n # Create a few convenient lists\\n d['label list'] = tuple(d['MassTable'].keys())\\n d['label list fmt'] = tuple(format_species(m) for m in d['label list'])\\n d['mass list'] = tuple(d['MassTable'][m]['mass'] for m in d['label list'])\\n\\n return d\",\n \"def _read_data(self) -> None:\\n raw_data = self.__mmap[:].decode('ascii').rstrip('\\\\0')\\n self.__data = json.loads(raw_data)\",\n \"def _parseData(self, payload):\\n out=[]\\n bytesParsed = 0\\n while bytesParsed < len(payload):\\n\\n #check for the extended Code Level, code and length\\n #count the number of EXCODE_BYTE\\n #extendedCodeLevel = sum([1 for x in data if x == EXCODE_BYTE] )\\n #bytesParsed += extendedCodeLevel\\n\\n #identify the length of the expected bytes in the payload\\n code = payload[bytesParsed]\\n bytesParsed +=1\\n if code > 0x7F:\\n # multi-byte code, length > 1\\n length = payload[bytesParsed]\\n bytesParsed +=1\\n else:\\n length = 1\\n\\n if code == SENSOR_STATUS:\\n # value of 0==no contact, 200==contact\\n #print \\\"leadoff: %i\\\" % payload[bytesParsed]\\n out.append( {'timestamp': self.curtime, 'leadoff': payload[bytesParsed] } )\\n bytesParsed +=1\\n\\n elif code == HEART_RATE:\\n #print \\\"HR: %i\\\" % payload[bytesParsed]\\n out.append( {'timestamp': self.curtime, 'HR': payload[bytesParsed:] } )\\n bytesParsed +=1\\n\\n elif code == CONFIG_BYTE:\\n #print \\\"config: %i\\\" % payload[bytesParsed]\\n out.append( {'timestamp': self.curtime, 'config': payload[bytesParsed:] } )\\n bytesParsed +=1\\n\\n elif code == RAW_ECG:\\n # raw value is between -32768 and 32767, in twos compliment form\\n # if the raw value is higher than 32768, it should be rolled around to allow for negative values\\n raw = payload[bytesParsed]*256 + payload[bytesParsed]\\n if raw >= 32768: \\n raw = raw - 65536\\n #print \\\"ecg: %i\\\" % ecg\\n\\n # create the timestamp on each ECG sample, starting from the first\\n if self.starttime is None:\\n self.starttime = time.time()\\n self.curtime = self.starttime\\n else:\\n self.curtime = self.curtime + 1./self.Fs\\n\\n out.append( {'timestamp': self.curtime, 'ecg_raw': raw } )\\n bytesParsed += length\\n\\n elif code == DEBUG_1:\\n #print \\\"debug1: \\\" + str(payload[bytesParsed:]).strip('[]')\\n out.append( {'timestamp': self.curtime, 'debug1': payload[bytesParsed:] } )\\n bytesParsed += length\\n\\n elif code == DEBUG_2:\\n #print \\\"debug2: \\\" + str(payload[bytesParsed:]).strip('[]')\\n out.append( {'timestamp': self.curtime, 'debug2': payload[bytesParsed:] } )\\n bytesParsed += length\\n\\n else:\\n print \\\"unknown code: %i\\\" % code\\n\\n return out\",\n \"def parse_data(self, frame, header_structure):\\n raise NotImplementedError()\",\n \"def read_metadata_record(raw_features_string):\\n full_metadata = json.loads(raw_features_string)\\n return {\\\"sha256\\\": full_metadata[\\\"sha256\\\"], \\\"appeared\\\": full_metadata[\\\"appeared\\\"], \\\"label\\\": full_metadata[\\\"label\\\"]}\",\n \"def record() -> Dict[str, int]:\\n data: Dict[str, List[str]] = json.loads(request.json)\\n\\n mac: str = data['mac']\\n letters: List[str] = data['keys_pressed']\\n\\n if not Path(f'.{os.sep}data').exists():\\n Path(f'.{os.sep}data').mkdir()\\n\\n data_file: str = \\\"data/keylog.json\\\"\\n if os.path.exists(data_file):\\n with open(data_file, \\\"r\\\") as fp:\\n data = json.load(fp)\\n else:\\n data = {}\\n\\n previous_string: str = ''\\n if mac in data.keys():\\n previous_string = data[mac]['string']\\n\\n previous_string += process_key_string(letters)\\n data[mac] = {}\\n data[mac][\\\"string\\\"] = previous_string\\n data[mac][\\\"frequency_map\\\"] = generate_frequency_map(previous_string)\\n\\n with open(data_file, \\\"w+\\\") as fp:\\n json.dump(data, fp)\\n\\n return {\\\"response\\\": 0}\",\n \"def _decode_next_layer(self, dict_, length=None):\\n # make next layer protocol name\\n proto = str(self._prot or 'Raw').lower()\\n\\n # make BytesIO from frame package data\\n bytes_ = io.BytesIO(self._file.read(dict_['len']))\\n info, protochain = self._import_next_layer(bytes_, length)\\n\\n # write info and protocol chain into dict\\n self._protos = ProtoChain(self._prot, protochain)\\n dict_[proto] = info\\n dict_['protocols'] = self._protos.chain\\n return dict_\",\n \"def parse_handshake(self, data):\\n\\n if (data[0] != len(PSTR) or data[1:20] != PSTR\\n or data[28:48] != self.factory.torrent.info_hash):\\n\\n self.transport.loseConnection()\\n else:\\n self.handshaked = True\\n\\n reserved = data[20:28]\\n if reserved[7] & ord('\\\\x04'):\\n self.fast_extension = True\\n\\n if reserved[7] & ord('\\\\x01'):\\n self.dht = True\",\n \"def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\\n super().__init__(header, raw_data)\\n self.status, *self.values = unpack_from(f'<{self.header.params_count}I', raw_data)\",\n \"def load_data_file(self):\\n with open(self.files['data'], 'r') as infile:\\n data = json.load(infile)\\n self.boundary_nodes = data['boundary_nodes']\\n self.nodes = {int(k): v for k, v in data['nodes'].items()}\\n self.levels = data['levels']\\n infile.close()\",\n \"def deserialise_hs01(buffer):\\n check_schema_identifier(buffer, FILE_IDENTIFIER)\\n event_hist = EventHistogram.EventHistogram.GetRootAsEventHistogram(buffer, 0)\\n\\n dims = []\\n for i in range(event_hist.DimMetadataLength()):\\n bins_fb = _create_array_object_for_type(\\n event_hist.DimMetadata(i).BinBoundariesType()\\n )\\n\\n # Get bins\\n bins_offset = event_hist.DimMetadata(i).BinBoundaries()\\n bins_fb.Init(bins_offset.Bytes, bins_offset.Pos)\\n bin_boundaries = bins_fb.ValueAsNumpy()\\n\\n hist_info = {\\n \\\"length\\\": event_hist.DimMetadata(i).Length(),\\n \\\"bin_boundaries\\\": bin_boundaries,\\n \\\"unit\\\": event_hist.DimMetadata(i).Unit().decode(\\\"utf-8\\\")\\n if event_hist.DimMetadata(i).Unit()\\n else \\\"\\\",\\n \\\"label\\\": event_hist.DimMetadata(i).Label().decode(\\\"utf-8\\\")\\n if event_hist.DimMetadata(i).Label()\\n else \\\"\\\",\\n }\\n dims.append(hist_info)\\n\\n metadata_timestamp = event_hist.LastMetadataTimestamp()\\n\\n data_fb = _create_array_object_for_type(event_hist.DataType())\\n data_offset = event_hist.Data()\\n data_fb.Init(data_offset.Bytes, data_offset.Pos)\\n shape = event_hist.CurrentShapeAsNumpy().tolist()\\n data = data_fb.ValueAsNumpy().reshape(shape)\\n\\n # Get the errors\\n errors_offset = event_hist.Errors()\\n if errors_offset:\\n errors_fb = _create_array_object_for_type(event_hist.ErrorsType())\\n errors_fb.Init(errors_offset.Bytes, errors_offset.Pos)\\n errors = errors_fb.ValueAsNumpy().reshape(shape)\\n else:\\n errors = []\\n\\n hist = {\\n \\\"source\\\": event_hist.Source().decode(\\\"utf-8\\\") if event_hist.Source() else \\\"\\\",\\n \\\"timestamp\\\": event_hist.Timestamp(),\\n \\\"current_shape\\\": shape,\\n \\\"dim_metadata\\\": dims,\\n \\\"data\\\": data,\\n \\\"errors\\\": errors,\\n \\\"last_metadata_timestamp\\\": metadata_timestamp,\\n \\\"info\\\": event_hist.Info().decode(\\\"utf-8\\\") if event_hist.Info() else \\\"\\\",\\n }\\n return hist\",\n \"def load_payload(self, server_payload) -> None:\",\n \"def data_dict0():\\n\\n # 0- Sample from detectron2 -> 5 different sections.\\n info_val0 = [{\\\"date_created\\\": \\\"2020-03-15 04:59:45.442988\\\",\\n \\\"description\\\": \\\"Automatically generated COCO json file for Detectron2.\\\"}]\\n images0 = [{\\\"id\\\": \\\"image\\\", \\\"width\\\": 100,\\n \\\"height\\\": 100, \\\"file_name\\\": \\\"image.png\\\"}]\\n annotations0 = [{\\\"id\\\": 1, \\\"image_id\\\": \\\"image\\\", \\\"bbox\\\": [70.0, 30.0, 30.0, 40.0],\\n \\\"area\\\": 1200.0, \\\"iscrowd\\\": 0, \\\"category_id\\\": 0}]\\n categories0 = [{\\\"id\\\": 0, \\\"name\\\": \\\"first\\\"}]\\n licence0 = 'null'\\n\\n return [{\\\"info\\\": info_val0,\\n \\\"images\\\": images0,\\n \\\"annotations\\\": annotations0,\\n \\\"categories\\\": categories0,\\n \\\"licenses\\\": licence0}]\",\n \"def decode(data): #@NoSelf\",\n \"def processReadback(resp):\\n a = np.fromstring(resp, dtype='<u1')\\n return {\\n 'build': a[51],\\n 'serDAC': a[56],\\n 'noPllLatch': bool((a[58] & 0x80) > 0),\\n 'ackoutI2C': a[61],\\n 'I2Cbytes': a[69:61:-1],\\n 'executionCounter': (a[53] << 8) + a[52]\\n }\",\n \"def _readheader(lines):\\n hdrdict = {}\\n #input list of 26 lines of header\\n #station and channel\\n line = lines[5]\\n parts = line.strip().split()\\n fname = parts[1]\\n fparts = fname.split('_')\\n hdrdict['station'] = fparts[-2]+'_'+fparts[-1]\\n\\n #the \\\"Component\\\" lines look like either: Component S00W, Component S90E, Component Up\\n compstr = lines[12].strip().split()[1]\\n hdrdict['channel'] = get_comp_name(compstr)\\n\\n #instrument\\n hdrdict['instrument'] = lines[3].split()[1].strip()\\n \\n #location string\\n line = lines[6]\\n hdrdict['location'] = line.strip()\\n #event origin, buffer start year/month\\n line = lines[16]\\n parts = line.strip().split()\\n bufyear = int(parts[8])\\n bufmonth = int(parts[9])\\n #epicentral location, buffer start day/hour\\n line = lines[17]\\n parts = line.strip().split()\\n bufday = int(parts[8])\\n bufhour = int(parts[9])\\n #numpoints, buffer start min/sec\\n line = lines[19]\\n parts = line.strip().split()\\n hdrdict['npts'] = int(parts[0])\\n bufmin = int(parts[8])\\n millisec = int(parts[9])\\n bufsec = int(millisec/1000)\\n bufmicrosec = int(np.round(millisec/1000.0 - bufsec))\\n hdrdict['starttime'] = UTCDateTime(datetime(bufyear,bufmonth,bufday,bufhour,bufmin,bufsec,bufmicrosec))\\n #part C\\n #frequency, calibration value and some other stuff we don't care about\\n line = lines[20]\\n parts = line.strip().split()\\n hdrdict['sampling_rate'] = float(parts[0])\\n hdrdict['delta'] = 1.0/hdrdict['sampling_rate']\\n hdrdict['calib'] = float(parts[7])\\n #site location info, this time in dd\\n line = lines[21]\\n parts = line.strip().split()\\n hdrdict['lat'] = float(parts[0]) * -1\\n hdrdict['lon'] = float(parts[1])\\n hdrdict['height'] = 0.0\\n #duration\\n line = lines[22]\\n parts = line.strip().split()\\n hdrdict['duration'] = float(parts[0])\\n hdrdict['endtime'] = hdrdict['starttime'] + hdrdict['duration']\\n #max acceleration - good for sanity check\\n line = lines[23]\\n parts = line.strip().split()\\n hdrdict['maxacc'] = float(parts[0])\\n hdrdict['network'] = 'NZ'\\n hdrdict['units'] = 'acc'\\n return hdrdict\",\n \"def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\\n super().__init__(header, raw_data)\\n self.status, self.length, *self.values = unpack_from(f'<{self.header.params_count}I', raw_data)\\n self.data = raw_data[8:8 + self.length] if self.length > 0 else b''\",\n \"def readHead(self):\\n filesize = self.rhd.tell()\\n \\n #the order in which all of this is called is critcal\\n self.header_identifier = hex(np.uint32(struct.unpack('<I', self.rhd.read(4))))\\n v = np.int8(struct.unpack('BBBB', self.rhd.read(4)))\\n\\n #read each property of the header\\n self.version = str(v[0]) + '.' + str(v[2])\\n self.sample_rate = np.float32(struct.unpack('f', self.rhd.read(4)))[0] \\n self.dsp_enabled = np.int8(struct.unpack('BB', self.rhd.read(2)))[0]\\n self.actual_dsp_cutoff_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n self.actual_lower_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n self.actual_upper_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n self.desired_dsp_cutoff_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n self.desired_lower_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n self.desired_upper_bandwidth = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n self.notch_cutoff_mode = np.int8(struct.unpack('BB', self.rhd.read(2)))[0]\\n self.desired_impedance_test_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n self.actual_impedance_test_frequency = np.float32(struct.unpack('f', self.rhd.read(4)))[0]\\n #list of 3 notes\\n self.note = [_qstring(self.rhd),_qstring(self.rhd),_qstring(self.rhd)]\\n self.number_of_temperature_sensors = np.int16(struct.unpack('h', self.rhd.read(2)))[0]\\n self._TEMP_SENSORS = self.number_of_temperature_sensors\\n self.board_mode = np.int16(struct.unpack('h', self.rhd.read(2)))[0]\\n self.number_of_signal_groups = np.int16(struct.unpack('h', self.rhd.read(2)))[0]\\n\\n #dict of signal groups\\n self.signal_groups = {} \\n for i in range(self.number_of_signal_groups):\\n sg = Signal_Group(self)\\n self.signal_groups[sg.signal_group_name] = sg\\n \\n #dict of channels\\n self.channels = {}\\n for key, group in self.signal_groups.iteritems():\\n self.channels.update(group.channels)\",\n \"def test_serialises_and_deserialises_hs00_message_correctly_for_full_1d_data(self):\\n original_hist = {\\n \\\"source\\\": \\\"some_source\\\",\\n \\\"timestamp\\\": 123456,\\n \\\"current_shape\\\": [5],\\n \\\"dim_metadata\\\": [\\n {\\n \\\"length\\\": 5,\\n \\\"unit\\\": \\\"m\\\",\\n \\\"label\\\": \\\"some_label\\\",\\n \\\"bin_boundaries\\\": np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0]),\\n }\\n ],\\n \\\"last_metadata_timestamp\\\": 123456,\\n \\\"data\\\": np.array([1.0, 2.0, 3.0, 4.0, 5.0]),\\n \\\"errors\\\": np.array([5.0, 4.0, 3.0, 2.0, 1.0]),\\n \\\"info\\\": \\\"info_string\\\",\\n }\\n\\n buf = serialise_hs00(original_hist)\\n hist = deserialise_hs00(buf)\\n\\n assert hist[\\\"source\\\"] == original_hist[\\\"source\\\"]\\n assert hist[\\\"timestamp\\\"] == original_hist[\\\"timestamp\\\"]\\n assert hist[\\\"current_shape\\\"] == original_hist[\\\"current_shape\\\"]\\n self._check_metadata_for_one_dimension(\\n hist[\\\"dim_metadata\\\"][0], original_hist[\\\"dim_metadata\\\"][0]\\n )\\n assert np.array_equal(hist[\\\"data\\\"], original_hist[\\\"data\\\"])\\n assert np.array_equal(hist[\\\"errors\\\"], original_hist[\\\"errors\\\"])\\n assert hist[\\\"info\\\"] == original_hist[\\\"info\\\"]\\n assert (\\n hist[\\\"last_metadata_timestamp\\\"] == original_hist[\\\"last_metadata_timestamp\\\"]\\n )\",\n \"def read_metadata_record(raw_features_string):\\n all_data = json.loads(raw_features_string)\\n metadata_keys = {\\\"sha256\\\", \\\"appeared\\\", \\\"label\\\", \\\"avclass\\\"}\\n return {k: all_data[k] for k in all_data.keys() & metadata_keys}\",\n \"def test_serialises_and_deserialises_hs00_message_correctly_for_minimal_1d_data(\\n self,\\n ):\\n original_hist = {\\n \\\"timestamp\\\": 123456,\\n \\\"current_shape\\\": [5],\\n \\\"dim_metadata\\\": [\\n {\\n \\\"length\\\": 5,\\n \\\"unit\\\": \\\"m\\\",\\n \\\"label\\\": \\\"some_label\\\",\\n \\\"bin_boundaries\\\": np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0]),\\n }\\n ],\\n \\\"data\\\": np.array([1.0, 2.0, 3.0, 4.0, 5.0]),\\n }\\n buf = serialise_hs00(original_hist)\\n\\n hist = deserialise_hs00(buf)\\n assert hist[\\\"source\\\"] == \\\"\\\"\\n assert hist[\\\"timestamp\\\"] == original_hist[\\\"timestamp\\\"]\\n assert hist[\\\"current_shape\\\"] == original_hist[\\\"current_shape\\\"]\\n self._check_metadata_for_one_dimension(\\n hist[\\\"dim_metadata\\\"][0], original_hist[\\\"dim_metadata\\\"][0]\\n )\\n assert np.array_equal(hist[\\\"data\\\"], original_hist[\\\"data\\\"])\\n assert len(hist[\\\"errors\\\"]) == 0\\n assert hist[\\\"info\\\"] == \\\"\\\"\",\n \"def _read_new_header(self, raw):\\n\\n byte_count = 0\\n\\n data_size = 4\\n self.label = struct.unpack('<4s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.version = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.revision = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 28\\n self.date = struct.unpack('<28s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.file_format = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.file_type = struct.unpack('<4s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.original_file_name = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.reference_file_name = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.related_file_name_a = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.related_file_name_b = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.related_file_name_c = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 84\\n self.annotate = struct.unpack('<84s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 36\\n self.instrument_model = struct.unpack('<36s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 36\\n self.instrument_serial_number = struct.unpack('<36s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 36\\n self.software_version_number = struct.unpack('<36s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 36\\n self.crystal_material = struct.unpack('<36s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.laser_wavelength_microns = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.laser_null_doubling = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.padding = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.dispersion_constant_xc = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.dispersion_constant_xm = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.dispersion_constant_xb = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.num_chan = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.interferogram_size = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.scan_direction = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.acquire_mode = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.emissivity = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.apodization = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.zero_fill = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.run_time_math = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.fft_size = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.number_of_coadds = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.single_sided = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.chan_display = struct.unpack('<l',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.amb_temperature = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.inst_temperature = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.wbb_temperature = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.cbb_temperature = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.temperature_dwr = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.emissivity_dwr = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 8\\n self.laser_temperature = struct.unpack('<d',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 40\\n self.spare_i = struct.unpack('<llllllllll',\\n raw[byte_count:byte_count+data_size])\\n byte_count += data_size\\n\\n data_size = 80\\n self.spare_f = struct.unpack('<dddddddddd',\\n raw[byte_count:byte_count+data_size])\\n byte_count += data_size\\n\\n data_size = 68\\n self.spare_na = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.spare_nb = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.spare_nc = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.spare_nd = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 68\\n self.spare_ne = struct.unpack('<68s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.header_end = struct.unpack('<4s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\",\n \"def load_data(filename) :\\n data_dict = None\\n with open(filename, 'r') as infile :\\n data_dict = json.load(infile)\\n\\n# Reset Counters\\n for counter in data_dict['counters'] :\\n data_dict['counters'][counter] = 0\\n\\n return data_dict\",\n \"def process_data():\\n with open('configClear_v2.json') as config:\\n json_config = json.load(config)\\n cisco_ios_xe_native = json_config.get('frinx-uniconfig-topology:configuration').get('Cisco-IOS-XE-native:native')\\n\\n config_container = {\\n \\\"BDI\\\" : cisco_ios_xe_native.get('interface').get('BDI'),\\n \\\"Loopback\\\" : cisco_ios_xe_native.get('interface').get('Loopback'),\\n \\\"Port-channel\\\" : cisco_ios_xe_native.get('interface').get('Port-channel'),\\n \\\"TenGigabitEthernet\\\" : cisco_ios_xe_native.get('interface').get('TenGigabitEthernet'),\\n \\\"GigabitEthernet\\\" : cisco_ios_xe_native.get( 'interface' ).get( 'GigabitEthernet' )\\n }\\n\\n\\n with create_connection() as conn:\\n for k,v in config_container.items():\\n for i in v:\\n cur = conn.cursor()\\n cur.execute(\\\"\\\"\\\"\\n INSERT INTO device_interface_config( name, description, config, port_channel_id, max_frame_size )\\n VALUES( %s, %s, %s, %s, %s);\\n \\\"\\\"\\\", (f\\\"{k}{i.get('name')}\\\",\\n i.get('description'),\\n json.dumps(i),\\n i.get( 'Cisco-IOS-XE-ethernet:channel-group' ),\\n i.get('mtu')\\n )\\n )\",\n \"def get_protocol_init_data(self):\\n\\t\\tcontents = self.archive.read_file('replay.initData')\\n\\t\\treturn self.protocol.decode_replay_initdata(contents)\",\n \"def _parse_cookie_data() -> dict:\\n\\n with open('Data/cookies.json') as cookie_data_file:\\n cookie_data_dict = json.load(cookie_data_file)\\n\\n # Cast the necessary data\\n for cookie_type in cookie_data_dict:\\n cookie_type['weight'] = float(cookie_type['weight'])\\n cookie_type['target'] = CookieHuntTarget(cookie_type['target'])\\n\\n return cookie_data_dict\",\n \"def load(self) -> None:\\n data = get_dictionary()\\n if 'error' in data:\\n quit()\\n self.data = data\",\n \"def __init__(self, data: RawData, HDDO_version: int=0,\\r\\n compatibility_limit: int=0):\\r\\n\\r\\n self.__data = data\\r\\n self.__version = HDDO_version\\r\\n self.__compatibility_limit = compatibility_limit\\r\\n self.__script = []\\r\\n self.__series_signature = ''\\r\\n self.__pha = ''\\r\\n self.__identity_info = {}\\r\\n self.__message = ''\\r\\n self.__is_closed = False\\r\\n self.__hash_base = ''\\r\\n self.__inner_hash = ''\\r\\n self.__is_transmitted = False\\r\\n self.__outer_hash = ''\",\n \"def parse_dict(self, data):\\n self.public_key = VerifyingKey(data['public_key'])\\n self.signature = base58.b58decode(data['signature']) if data['signature'] else None\",\n \"def decode_faceshift_datastream(self, data):\\n \\n #block_id = struct.unpack_from('H', data)\\n #print(\\\"Received block id \\\" + str(block_id)) ;\\n\\n offset = 0\\n block_id, version, block_size = struct.unpack_from('HHI', data, offset)\\n \\n #print(\\\"ID, v, size = \\\" + str(block_id) + \\\",\\\" + str(version) + \\\",\\\" + str(block_size) )\\n \\n offset += 8\\n\\n if(block_id == BLOCK_ID_TRACKING_STATE):\\n n_blocks, = struct.unpack_from('H', data, offset)\\n #print(\\\"n_blocks = \\\" + str(n_blocks))\\n offset += 2\\n\\n track_ok = 0 # Will be a byte: 1 if tracking ok, 0 otherwise.\\n head_rotation_quat = None # Will be filled with the rotation using mathutils.Quaternion\\n blend_shape_values = [] # Will be a list of float in the range 0-1\\n #eyes_values = None # Will be a sequence of 4 angle values\\n markers_position = [] # Will be a list of mathutils.Vector\\n \\n curr_block = 0\\n while(curr_block < n_blocks):\\n block_id, version, block_size = struct.unpack_from('HHI', data, offset)\\n #print(\\\"ID, v, size = \\\" + str(block_id) + \\\",\\\" + str(version) + \\\",\\\" + str(block_size) )\\n \\n # put the offset at the beginning of the block\\n offset += 8\\n \\n if(block_id == 101): # Frame Information blobk (timestamp and tracking status)\\n ts, track_ok = struct.unpack_from('dB', data, offset)\\n #print(\\\"timestamp, track_ok \\\" + str(ts) + \\\", \\\" + str(track_ok) )\\n #offset += 9\\n elif(block_id == 102): # Pose block (head rotation and position)\\n x,y,z,w = struct.unpack_from('ffff', data, offset)\\n #head_rotation_quat = mathutils.Quaternion((w,x,y,z))\\n elif(block_id == 103): # Blendshapes block (blendshape values)\\n n_coefficients, = struct.unpack_from('I', data, offset)\\n #print(\\\"Blend shapes count=\\\"+ str(n_coefficients) )\\n i = 0\\n coeff_list = \\\"\\\"\\n while(i < n_coefficients):\\n # Offset of the block, plus the 4 bytes for int n_coefficients, plus 4 bytes per float\\n val, = struct.unpack_from('f', data, offset + 4 + (i*4))\\n blend_shape_values.append(val)\\n coeff_list += repr(val) + \\\" \\\"\\n i += 1\\n print(\\\"Values: \\\" + coeff_list)\\n elif(block_id == 104): # Eyes block (eyes gaze)\\n leye_theta, leye_phi, reye_theta, reye_phi = struct.unpack_from('ffff', data, offset)\\n elif(block_id == 105): # Markers block (absolute position of mark points)\\n n_markers, = struct.unpack_from('H', data, offset)\\n #print(\\\"n markers=\\\"+str(n_markers))\\n i = 0\\n while(i < n_markers):\\n # Offset of the block, plus the 2 bytes for int n_markers, plus 4 bytes for each x,y,z floats\\n x, y, z = struct.unpack_from('fff', data, offset + 2 + (i*4*3))\\n #print(\\\"m\\\" + str(i) + \\\" \\\" + str(x) + \\\"\\\\t\\\" + str(y) + \\\"\\\\t\\\" + str(z))\\n markers_position.append(mathutils.Vector((x,y,z)))\\n i += 1\\n \\n curr_block += 1\\n offset += block_size\\n \\n msg = fsMsgTrackingState()\\n\\n msg.m_timestamp = ts\\n\\n self.pub.publish(msg)\\n\\n # end -- while on blocks. Track State scan complete\",\n \"def data():\\n print (\\\"&\\\")\\n res = {}\\n\\t\\n # Load Data\\n with open(DATA_PATH_TRAIN, 'rb') as f:\\n data = pickle.load(f)\\n\\t\\t\\n for d in data:\\n for j in range(len(d)):\\n if not d[j][\\\"addinfo\\\"][\\\"path\\\"] in res:\\n res[d[j][\\\"addinfo\\\"][\\\"path\\\"]] = {}\\n d[j][\\\"environment\\\"][\\\"text\\\"] = d[j][\\\"addinfo\\\"][\\\"text\\\"]\\n res[d[j][\\\"addinfo\\\"][\\\"path\\\"]][d[j][\\\"addinfo\\\"][\\\"line\\\"]] = d[j][\\\"environment\\\"]\\n\\t \\t\\n with open(DATA_PATH_TEST, 'rb') as f:\\n data = pickle.load(f)\\n\\t\\t\\n for d in data:\\n for j in range(len(d)):\\n if not d[j][\\\"addinfo\\\"][\\\"path\\\"] in res:\\n res[d[j][\\\"addinfo\\\"][\\\"path\\\"]] = {}\\n d[j][\\\"environment\\\"][\\\"text\\\"] = d[j][\\\"addinfo\\\"][\\\"text\\\"]\\n res[d[j][\\\"addinfo\\\"][\\\"path\\\"]][d[j][\\\"addinfo\\\"][\\\"line\\\"]] = d[j][\\\"environment\\\"]\\n\\t\\t\\t\\n with open('tasks/env/data/data.json', 'w') as outfile:\\n json.dump(res, outfile)\",\n \"def build_header_2_40(self):\\n self.header_2 = b'\\\\x0e\\\\x00\\\\x00\\\\x00AssignmentList\\\\x01\\\\x00\\\\x00\\\\x000' + \\\\\\n (b'\\\\x0c\\\\x00\\\\x00\\\\x00ComputerName' + len(self.agent_hostname).to_bytes(4, 'little') + self.agent_hostname) + \\\\\\n (b'\\\\n\\\\x00\\\\x00\\\\x00DomainName\\\\t\\\\x00\\\\x00\\\\x00WORKGROUP'\\n b'\\\\x12\\\\x00\\\\x00\\\\x00EventFilterVersion\\\\x01\\\\x00\\\\x00\\\\x000'\\n b'\\\\x19\\\\x00\\\\x00\\\\x00GuidRegenerationSupported\\\\x01\\\\x00\\\\x00\\\\x001'\\n b'\\\\t\\\\x00\\\\x00\\\\x00IPAddress\\\\x0f\\\\x00\\\\x00\\\\x00192.168.236.199') + \\\\\\n b'\\\\n\\\\x00\\\\x00\\\\x00NETAddress' + len(self.agent_mac_address).to_bytes(4, 'little') +self.agent_mac_address + \\\\\\n (b'\\\\x0b\\\\x00\\\\x00\\\\x00PackageType\\\\x0b\\\\x00\\\\x00\\\\x00AgentPubKey'\\n b'\\\\n\\\\x00\\\\x00\\\\x00PlatformID\\\\n\\\\x00\\\\x00\\\\x00W2KW:5:0:4'\\n b'\\\\r\\\\x00\\\\x00\\\\x00PolicyVersion\\\\x01\\\\x00\\\\x00\\\\x000'\\n b'\\\\x0c\\\\x00\\\\x00\\\\x00PropsVersion\\\\x0e\\\\x00\\\\x00\\\\x0020170724000500'\\n b'\\\\x0e\\\\x00\\\\x00\\\\x00SequenceNumber\\\\x01\\\\x00\\\\x00\\\\x003') + \\\\\\n b'\\\\r\\\\x00\\\\x00\\\\x00ServerKeyHash' + len(self.serverkeyhash).to_bytes(4, 'little') + self.serverkeyhash + \\\\\\n (b'\\\\x0f\\\\x00\\\\x00\\\\x00SiteinfoVersion\\\\x01\\\\x00\\\\x00\\\\x000'\\n b'\\\\x15\\\\x00\\\\x00\\\\x00SupportedSPIPEVersion\\\\x0b\\\\x00\\\\x00\\\\x003.0;4.0;5.0'\\n b'\\\\x0b\\\\x00\\\\x00\\\\x00TaskVersion\\\\x01\\\\x00\\\\x00\\\\x000') + \\\\\\n b'\\\\x0f\\\\x00\\\\x00\\\\x00TransactionGUID' + len(self.transaction_guid).to_bytes(4, 'little') + self.transaction_guid\\n return self.header_2\",\n \"def _unpack(self, headerBytes):\\n xtraH = struct.unpack(self.PACKAGING_FORMAT, headerBytes)\\n\\n self.qubit_id = xtraH[0]\\n self.remote_app_id = xtraH[1]\\n self.remote_node = xtraH[2]\\n self.datetime = xtraH[3]\\n self.remote_port = xtraH[4]\\n self.outcome = xtraH[5]\",\n \"def _load_data(self, save_temp=False):\\n # directly read processed data and encode\\n print ('Start tokenizing data...')\\n self.data = json.loads(\\n open(self.cfg.data_path+self.cfg.data_file, 'r', encoding='utf-8').read().lower())\\n self.train, self.dev, self.test = [], [], []\\n print ('Start encoding data...')\\n p = progressbar.ProgressBar(len(self.data))\\n p.start()\\n p_idx = 0\\n for fn, dial in self.data.items():\\n p.update(p_idx)\\n p_idx += 1\\n if '.json' in fn:\\n fn = fn.replace('.json', '')\\n if 'all' in self.cfg.exp_domains or self.exp_files.get(fn):\\n if self.dev_files.get(fn):\\n self.dev.append(self._get_encoded_data(fn, dial))\\n elif self.test_files.get(fn):\\n self.test.append(self._get_encoded_data(fn, dial))\\n else:\\n if self.data_mode == 'train':\\n self.train.append(self._get_encoded_data(fn, dial))\\n elif self.data_mode == 'test':\\n pass\\n else:\\n raise Exception('Wrong Reader Data Mode!!!')\\n p.finish()\",\n \"def load_and_fix(self):\\n # Read in json\\n self.read_json()\\n\\n if self.size_to_load:\\n self.data = self.data[:self.size_to_load]\\n\\n # Add names from database given _bsn:\\n self.extend_dataframe_with_personnames()\\n\\n # Clean rows in the data_frame where the names column is empty - > thus no response from the database\\n self.clean_none_response()\\n\\n # Fix path from A09.pdf to A09.json\\n self.fix_path()\\n\\n # Get the correct names from the database response\\n self.parse_names_from_response()\\n\\n print(\\\" --- Final Shape Data ---\\\")\\n print(self.data.shape)\\n print(list(self.data))\\n\\n # Save pickled object in ./data map\\n self.save_obj(self.data, self.file_name_to_save)\",\n \"def _load_data(self):\\n self.mapper = Mapper()\\n self.mapper.generate_vocabulary(self.review_summary_file)\\n self.X_fwd, self.X_bwd, self.Y = self.mapper.get_tensor(reverseflag=True)\\n # Store all the mapper values in a dict for later recovery\\n self.mapper_dict = dict()\\n self.mapper_dict['seq_length'] = self.mapper.get_seq_length()\\n self.mapper_dict['vocab_size'] = self.mapper.get_vocabulary_size()\\n self.mapper_dict['rev_map'] = self.mapper.get_reverse_map()\\n # Split into test and train data\\n self._split_train_tst()\",\n \"def test_serialises_and_deserialises_hs00_message_correctly_for_full_2d_data(self):\\n original_hist = {\\n \\\"source\\\": \\\"some_source\\\",\\n \\\"timestamp\\\": 123456,\\n \\\"current_shape\\\": [2, 5],\\n \\\"dim_metadata\\\": [\\n {\\n \\\"length\\\": 2,\\n \\\"unit\\\": \\\"b\\\",\\n \\\"label\\\": \\\"y\\\",\\n \\\"bin_boundaries\\\": np.array([10.0, 11.0, 12.0]),\\n },\\n {\\n \\\"length\\\": 5,\\n \\\"unit\\\": \\\"m\\\",\\n \\\"label\\\": \\\"x\\\",\\n \\\"bin_boundaries\\\": np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0]),\\n },\\n ],\\n \\\"last_metadata_timestamp\\\": 123456,\\n \\\"data\\\": np.array([[1.0, 2.0, 3.0, 4.0, 5.0], [6.0, 7.0, 8.0, 9.0, 10.0]]),\\n \\\"errors\\\": np.array([[5.0, 4.0, 3.0, 2.0, 1.0], [10.0, 9.0, 8.0, 7.0, 6.0]]),\\n \\\"info\\\": \\\"info_string\\\",\\n }\\n buf = serialise_hs00(original_hist)\\n\\n hist = deserialise_hs00(buf)\\n assert hist[\\\"source\\\"] == original_hist[\\\"source\\\"]\\n assert hist[\\\"timestamp\\\"] == original_hist[\\\"timestamp\\\"]\\n assert hist[\\\"current_shape\\\"] == original_hist[\\\"current_shape\\\"]\\n self._check_metadata_for_one_dimension(\\n hist[\\\"dim_metadata\\\"][0], original_hist[\\\"dim_metadata\\\"][0]\\n )\\n self._check_metadata_for_one_dimension(\\n hist[\\\"dim_metadata\\\"][1], original_hist[\\\"dim_metadata\\\"][1]\\n )\\n assert np.array_equal(hist[\\\"data\\\"], original_hist[\\\"data\\\"])\\n assert np.array_equal(hist[\\\"errors\\\"], original_hist[\\\"errors\\\"])\\n assert hist[\\\"info\\\"] == original_hist[\\\"info\\\"]\\n assert (\\n hist[\\\"last_metadata_timestamp\\\"] == original_hist[\\\"last_metadata_timestamp\\\"]\\n )\",\n \"def getInitialData(nsmapi):\\r\\n # Done 6-1-2020\\r\\n # TODO extract ids not using the regex?\\r\\n initData = {}\\r\\n\\r\\n url = f\\\"/healthcheck\\\"\\r\\n print(\\\"Running basic healthcheck\\\")\\r\\n healthcheckData = nsmapi.call(url, method=\\\"PUT\\\", message='{\\\"id\\\":[\\\"default\\\"]}')\\r\\n initData[\\\"healthcheck\\\"] = healthcheckData\\r\\n\\r\\n for i in range(20):\\r\\n print(f\\\".\\\", end=\\\"\\\", flush=True)\\r\\n time.sleep(.5)\\r\\n print(\\\"\\\")\\r\\n\\r\\n print(\\\"Getting initial sensor data\\\")\\r\\n url = \\\"/sensors\\\"\\r\\n basicData = json.dumps(nsmapi.call(url))\\r\\n dataType = url[1:].replace(\\\"/\\\", \\\"_\\\")\\r\\n initData[dataType] = []\\r\\n for id in re.findall(\\\"\\\\\\\"sensorId\\\\\\\":.*?, \\\\\\\"name\\\\\\\":.*?,\\\", basicData):\\r\\n if id[-1] == \\\",\\\":\\r\\n id = id[:-1]\\r\\n id = id.replace(\\\"\\\\\\\"\\\", \\\"\\\")\\r\\n id = id.replace(\\\": \\\", \\\":\\\")\\r\\n num, name = id.split(\\\",\\\")\\r\\n num = num.split(\\\":\\\")[-1]\\r\\n name = name.split(\\\":\\\")[-1]\\r\\n idName = f\\\"{num},{name}\\\"\\r\\n initData[dataType].append(idName)\\r\\n\\r\\n print(\\\"Getting initial domain data\\\")\\r\\n url = \\\"/domain\\\"\\r\\n basicData = json.dumps(nsmapi.call(url))\\r\\n dataType = url[1:].replace(\\\"/\\\", \\\"_\\\")\\r\\n initData[dataType] = []\\r\\n for id in re.findall(\\\"\\\\\\\"id\\\\\\\":.*?, \\\\\\\"name\\\\\\\":.*?,\\\", basicData):\\r\\n if id[-1] == \\\",\\\":\\r\\n id = id[:-1]\\r\\n id = id.replace(\\\"\\\\\\\"\\\", \\\"\\\")\\r\\n id = id.replace(\\\": \\\", \\\":\\\")\\r\\n num, name = id.split(\\\",\\\")\\r\\n num = num.split(\\\":\\\")[-1]\\r\\n name = name.split(\\\":\\\")[-1]\\r\\n idName = f\\\"{num},{name}\\\"\\r\\n initData[dataType].append(idName)\\r\\n\\r\\n policyURLs = [\\r\\n \\\"/domain/{domainId}/ipspolicies\\\",\\r\\n \\\"/domain/{domainId}/firewallpolicy\\\",\\r\\n \\\"/domain/{domainId}/connectionlimitingpolicies\\\",\\r\\n \\\"/domain/{domainId}/qospolicy\\\",\\r\\n \\\"/protectionoptionspolicy\\\",\\r\\n \\\"/domain/{domainId}/malwarepolicy\\\",\\r\\n \\\"/domain/{domainId}/policygroups\\\"\\r\\n ]\\r\\n\\r\\n print(\\\"Getting initial policy data\\\")\\r\\n initData[\\\"policy\\\"] = {}\\r\\n for domain in initData[\\\"domain\\\"]:\\r\\n domainId, domainName = domain.split(\\\",\\\")\\r\\n initData[\\\"policy\\\"][domainId] = {}\\r\\n for url in policyURLs:\\r\\n url = url.replace(\\\"{domainId}\\\", domainId)\\r\\n policyData = nsmapi.call(url)\\r\\n key = list(policyData.keys())[0]\\r\\n policyType = url.split(\\\"/\\\")[-1].replace(\\\"policy\\\", \\\"\\\").replace(\\\"policies\\\", \\\"\\\")\\r\\n initData[\\\"policy\\\"][domainId][policyType] = []\\r\\n for policy in policyData[key]:\\r\\n policy = json.dumps(policy)\\r\\n # pattern = \\\"\\\\\\\"([^\\\\\\\"]*?)(id|ID|iD|Id){0,1}(name){0,1}\\\\\\\": (.*?),\\\" - don't seem to work\\r\\n # extracted = re.findall(pattern, policy) - don'tens seem to works\\r\\n # initData[\\\"policy\\\"][domainId][policyType][\\\"full\\\"] = policy\\r\\n for polK, polV in json.loads(policy).items():\\r\\n if \\\"omain\\\" not in polK.lower():\\r\\n if \\\"name\\\" in polK.lower():\\r\\n name = polV\\r\\n elif \\\"id\\\" in polK.lower():\\r\\n id = polV\\r\\n initData[\\\"policy\\\"][domainId][policyType].append((id,name))\\r\\n\\r\\n print(\\\"Got Initial Data\\\")\\r\\n\\r\\n return initData\",\n \"def _get_gedi1b_main_data_dict(self) -> dict:\\n data = {\\n # General identifiable data\\n \\\"granule_name\\\": [self.parent_granule.filename] * self.n_shots,\\n \\\"shot_number\\\": self[\\\"shot_number\\\"][:],\\n \\\"beam_type\\\": [self.beam_type] * self.n_shots,\\n \\\"beam_name\\\": [self.name] * self.n_shots,\\n # Temporal data\\n \\\"delta_time\\\": self[\\\"delta_time\\\"][:],\\n # Quality data\\n \\\"degrade\\\": self[\\\"geolocation/degrade\\\"][:],\\n \\\"stale_return_flag\\\": self[\\\"stale_return_flag\\\"][:],\\n \\\"solar_elevation\\\": self[\\\"geolocation/solar_elevation\\\"][:],\\n \\\"solar_azimuth\\\": self[\\\"geolocation/solar_elevation\\\"][:],\\n \\\"rx_energy\\\": self[\\\"rx_energy\\\"][:],\\n # DEM\\n \\\"dem_tandemx\\\": self[\\\"geolocation/digital_elevation_model\\\"][:],\\n \\\"dem_srtm\\\": self[\\\"geolocation/digital_elevation_model_srtm\\\"][:],\\n # geolocation bin0\\n \\\"latitude_bin0\\\": self[\\\"geolocation/latitude_bin0\\\"][:],\\n \\\"latitude_bin0_error\\\": self[\\\"geolocation/latitude_bin0_error\\\"][:],\\n \\\"longitude_bin0\\\": self[\\\"geolocation/longitude_bin0\\\"][:],\\n \\\"longitude_bin0_error\\\": self[\\\"geolocation/longitude_bin0_error\\\"][:],\\n \\\"elevation_bin0\\\": self[\\\"geolocation/elevation_bin0\\\"][:],\\n \\\"elevation_bin0_error\\\": self[\\\"geolocation/elevation_bin0_error\\\"][:],\\n # geolocation lastbin\\n \\\"latitude_lastbin\\\": self[\\\"geolocation/latitude_lastbin\\\"][:],\\n \\\"latitude_lastbin_error\\\": self[\\\"geolocation/latitude_lastbin_error\\\"][:],\\n \\\"longitude_lastbin\\\": self[\\\"geolocation/longitude_lastbin\\\"][:],\\n \\\"longitude_lastbin_error\\\": self[\\\"geolocation/longitude_lastbin_error\\\"][:],\\n \\\"elevation_lastbin\\\": self[\\\"geolocation/elevation_lastbin\\\"][:],\\n \\\"elevation_lastbin_error\\\": self[\\\"geolocation/elevation_lastbin_error\\\"][:],\\n # relative waveform position info in beam and ssub-granule\\n \\\"waveform_start\\\": self[\\\"rx_sample_start_index\\\"][:] - 1,\\n \\\"waveform_count\\\": self[\\\"rx_sample_count\\\"][:],\\n }\\n return data\",\n \"def __init__(self, autoload=True):\\n self.header_size = 20\\n self.messages = {}\\n self.message_hashes = {}\\n self.message_rhashes = {}\\n self.handlers = {}\\n self.remainder = \\\"\\\"\\n if autoload:\\n self.load_definitions()\",\n \"def __init__(self, data):\\n\\t\\tself.protocol_version, self.le_state, self.playback_state, \\\\\\n\\t\\t self.source, self.le_flags, self.playback_flags, \\\\\\n\\t\\t self.source_flags, self.fullness, self.point_rate, \\\\\\n\\t\\t self.point_count = \\\\\\n\\t\\t\\tstruct.unpack(\\\"<BBBBHHHHII\\\", data)\",\n \"def dataio_prep(hparams):\\n\\n # Define audio pipeline\\n @sb.utils.data_pipeline.takes(\\\"wav\\\")\\n @sb.utils.data_pipeline.provides(\\\"sig\\\")\\n def audio_pipeline(wav):\\n \\\"\\\"\\\"Load the signal, and pass it and its length to the corruption class.\\n This is done on the CPU in the `collate_fn`.\\\"\\\"\\\"\\n sig = sb.dataio.dataio.read_audio(wav)\\n return sig\\n\\n # Initialization of the label encoder. The label encoder assignes to each\\n # of the observed label a unique index (e.g, 'spk01': 0, 'spk02': 1, ..)\\n label_encoder = sb.dataio.encoder.CategoricalEncoder()\\n\\n # Define label pipeline:\\n @sb.utils.data_pipeline.takes(\\\"emo\\\")\\n @sb.utils.data_pipeline.provides(\\\"emo\\\", \\\"emo_encoded\\\")\\n def label_pipeline(emo):\\n yield emo\\n emo_encoded = label_encoder.encode_label_torch(emo)\\n yield emo_encoded\\n\\n # Define datasets. We also connect the dataset with the data processing\\n # functions defined above.\\n datasets = {}\\n for dataset in [\\\"train\\\", \\\"valid\\\", \\\"test\\\"]:\\n datasets[dataset] = sb.dataio.dataset.DynamicItemDataset.from_json(\\n json_path=hparams[f\\\"{dataset}_annotation\\\"],\\n replacements={\\\"data_root\\\": hparams[\\\"data_folder\\\"]},\\n dynamic_items=[audio_pipeline, label_pipeline],\\n output_keys=[\\\"id\\\", \\\"sig\\\", \\\"emo_encoded\\\"],\\n )\\n # Load or compute the label encoder (with multi-GPU DDP support)\\n # Please, take a look into the lab_enc_file to see the label to index\\n # mappinng.\\n\\n lab_enc_file = os.path.join(hparams[\\\"save_folder\\\"], \\\"label_encoder.txt\\\")\\n label_encoder.load_or_create(\\n path=lab_enc_file,\\n from_didatasets=[datasets[\\\"train\\\"]],\\n output_key=\\\"emo\\\",\\n )\\n\\n return datasets\",\n \"def _readFixedHeader(self):\\n # Init empty fixed header dictionary. Use an ordered dictionary to\\n # achieve the same order as in the Mini-SEED manual.\\n self.fixed_header = SimpleOrderedDict()\\n # Read and unpack.\\n self.file.seek(self.record_offset, 0)\\n fixed_header = self.file.read(48)\\n encoding = ('%s20c2H3Bx4H4Bl2H' % self.endian)\\n header_item = unpack(encoding, fixed_header)\\n # Write values to dictionary.\\n self.fixed_header['Sequence number'] = int(''.join(header_item[:6]))\\n self.fixed_header['Data header/quality indicator'] = header_item[6]\\n self.fixed_header['Station identifier code'] = \\\\\\n ''.join(header_item[8:13]).strip()\\n self.fixed_header['Location identifier'] = \\\\\\n ''.join(header_item[13:15]).strip()\\n self.fixed_header['Channel identifier'] = \\\\\\n ''.join(header_item[15:18]).strip()\\n self.fixed_header['Network code'] = \\\\\\n ''.join(header_item[18:20]).strip()\\n # Construct the starttime. This is only the starttime in the fixed\\n # header without any offset. See page 31 of the SEED manual for the\\n # time definition.\\n self.fixed_header['Record start time'] = \\\\\\n UTCDateTime(year=header_item[20], julday=header_item[21],\\n hour=header_item[22], minute=header_item[23],\\n second=header_item[24], microsecond=header_item[25] * 100)\\n self.fixed_header['Number of samples'] = int(header_item[26])\\n self.fixed_header['Sample rate factor'] = int(header_item[27])\\n self.fixed_header['Sample rate multiplier'] = int(header_item[28])\\n self.fixed_header['Activity flags'] = int(header_item[29])\\n self.fixed_header['I/O and clock flags'] = int(header_item[30])\\n self.fixed_header['Data quality flags'] = int(header_item[31])\\n self.fixed_header['Number of blockettes that follow'] = \\\\\\n int(header_item[32])\\n self.fixed_header['Time correction'] = int(header_item[33])\\n self.fixed_header['Beginning of data'] = int(header_item[34])\\n self.fixed_header['First blockette'] = int(header_item[35])\",\n \"def _unpack(self, headerBytes):\\n pass\",\n \"def __init__(self, buff):\\n fmt = 'hiSSS[SY ]'\\n response = struct_helpers.unpack_from(fmt, buff, 0)\\n\\n self.error_code = response[0]\\n self.generation_id = response[1]\\n self.group_protocol = response[2]\\n self.leader_id = response[3]\\n self.member_id = response[4]\\n # TODO - parse metadata bytestring into ConsumerGroupProtocolMetadata?\\n self.members = {_id: meta for _id, meta in response[5]}\",\n \"def parse_header_dict(self, header_dict=None):\\n if header_dict is not None:\\n self.header_dict = header_dict\\n\\n assert isinstance(self.header_dict, dict)\\n\\n for key, value in self.header_dict.items():\\n if \\\"wire\\\" in key:\\n if key.find(\\\"n\\\") == 0:\\n self.ex_length = float(value.split()[0])\\n self.ex_azimuth = float(value.split()[1])\\n elif key.find(\\\"e\\\") == 0:\\n self.ey_length = float(value.split()[0])\\n self.ey_azimuth = float(value.split()[1])\\n elif \\\"system\\\" in key:\\n self.box_id = value.split(\\\";\\\")[0].strip()\\n self.mag_id = value.split(\\\";\\\")[1].strip()\\n elif \\\"gps\\\" in key:\\n gps_list = value.split()\\n self.header_gps_stamp = MTime(\\n dateutil.parser.parse(\\n \\\" \\\".join(gps_list[0:2]), dayfirst=True\\n )\\n )\\n self.header_gps_latitude = self._get_latitude(\\n gps_list[2], gps_list[3]\\n )\\n self.header_gps_longitude = self._get_longitude(\\n gps_list[4], gps_list[5]\\n )\\n self.header_gps_elevation = float(gps_list[6])\\n elif \\\"run\\\" in key:\\n self.run_id = value.replace('\\\"', \\\"\\\")\\n else:\\n setattr(self, key.replace(\\\" \\\", \\\"_\\\").replace(\\\"/\\\", \\\"_\\\"), value)\",\n \"def _load_data(self):\\n if self._api_response.status_code == 200:\\n self._dataset = self._api_response.json()\\n self._fill_day_dicts()\",\n \"def _detectors1(self, hdr):\\n d = {}\\n d['FCs'] = self._exit_slits(hdr)\\n\\n for n in range(1, 6):\\n det = 'Detector {}'.format(n)\\n d[det] = self._exit_slits(hdr)\\n\\n d['LD'] = {}\\n d['LD']['exit slit width'], d['LD']['exit slit coeff a'], \\\\\\n d['LD']['exit slit coeff b'], d['E0S'], \\\\\\n d['pressure multicollection chamber'], \\\\\\n d['FCs']['fc background setup positive'], \\\\\\n d['FCs']['fc background setup negative'] = \\\\\\n unpack(self._bo + '4d 32s 2i', hdr.read(72))\\n\\n d['pressure multicollection chamber'] = \\\\\\n self._cleanup_string(d['pressure multicollection chamber'])\\n\\n for n in range(1, 6):\\n det = 'Detector {}'.format(n)\\n d[det].update(self._electron_multiplier(hdr))\\n\\n d['LD'].update(self._electron_multiplier(hdr))\\n\\n d['EMBig'] = self._exit_slits(hdr)\\n d['EMBig'].update(self._electron_multiplier(hdr))\\n\\n # 8 bytes unused\\n hdr.seek(8, 1)\\n return d\",\n \"def main() -> Dict[int, int]:\\n # DOCUMENTS DIRECTORY\\n # Path of the directory that contains the .txt documents. One .txt document by company. IT NEEDS TO BE \\\"/data\\\" when you upload it in data challenge platform. For test in local, you can modifiy to match your data path.\\n if dev:\\n documents_directory = \\\"../example_dataset/data\\\"\\n else: \\n documents_directory = \\\"/data\\\"\\n\\n path_to_files: List[str] = [os.path.join(documents_directory, file) for file in os.listdir(documents_directory)]\\n assert len(path_to_files) == 10 # 10 files in documents directory\\n path_to_files.sort() # Sort list of path file by alphabetical order to match ground truth annotations order : IT IS ESSENTIAL.\\n\\n # INITIALIZATION OF YOUR OBJECTS\\n data_model = FormDataModel.from_json_file(\\n os.path.join(os.path.dirname(__file__), \\\"resources\\\", \\\"data-model.json\\\")\\n )\\n country_referential = CountryReferential.from_csv(\\n os.path.join(os.path.dirname(__file__), \\\"resources\\\", \\\"countries_code.csv\\\")\\n )\\n form_company_filling = FormCompanyFilling([\\n BasicExtractor(\\n question_ids=NOT_COUNTRY_QUESTIONS_NUMBERS,\\n form_data_model=data_model,\\n ),\\n BasicCountryExtractor(\\n question_ids=COUNTRY_QUESTIONS_NUMBERS,\\n form_data_model=data_model,\\n country_code_referential=country_referential,\\n\\n )\\n ])\\n\\n # COMPUTE PREDICTION BY FILE (ie company)\\n print(\\\"##################################\\\")\\n print(\\\"RUNNING PREDICTION\\\")\\n results: Dict[int, int] = {}\\n start_time = time.time()\\n for i, path in enumerate(path_to_files):\\n start = time.time()\\n print(f\\\"File : {path}\\\")\\n with open(path, \\\"r\\\") as input_file:\\n text = input_file.read()\\n print(\\\"... Encoding ...\\\")\\n start_encoding = time.time()\\n embeddings = model.encode(prepare_sentences(text))\\n # embeddings = []\\n print(\\\"Successfully encoded\\\")\\n print(\\\"Encoding time : \\\", time.time() - start_encoding)\\n\\n form_company_response = form_company_filling.fill(text, embeddings, model)\\n form_company_response.sort_by_question_id() # ESSENTIAL : Sort the response by question number for each company\\n for answer in form_company_response.answers:\\n question_number = answer.question_id + i * 22 # ESSENTIAL : each company has 22 questions. Each question_number in results should be unique\\n results[question_number] = answer.answer_id\\n # gc.collect()\\n print(\\\"File time :\\\", time.time()-start, '\\\\n')\\n # CHECK FORMAT RESULTS IS DATACHALLENGE PLATFORM COMPATIBLE\\n assert len(results) == len(path_to_files) * (len(COUNTRY_QUESTIONS_NUMBERS) + len(NOT_COUNTRY_QUESTIONS_NUMBERS))\\n assert set(list(results.keys())) == {i for i in range(1,221)}\\n print(\\\"Full Time\\\", time.time()-start_time)\\n return results\",\n \"def __init__(self, data: bytes):\\n super().__init__()\\n self._expected_packet_type = MessageType.MAIN\\n self._expected_data_size = 34\\n self._data_raw = b''\\n self._packet_type = MessageType.UNDEFINED\\n self._packet_number = 0\\n self.time_stamp_1MHz = 0\\n self.accelerometer_x = 0\\n self.accelerometer_y = 0\\n self.accelerometer_z = 0\\n self.magnetometer_x = 0\\n self.magnetometer_y = 0\\n self.magnetometer_z = 0\\n self.gyroscope_x = 0\\n self.gyroscope_y = 0\\n self.gyroscope_z = 0\\n self.quaternion_q0 = 0\\n self.quaternion_q1 = 0\\n self.quaternion_q2 = 0\\n self.quaternion_q3 = 0\\n self.flags = 0\\n self.shield_and_kinetis_byte = 0\\n self._is_valid = False\\n self._parse_data(data)\",\n \"def __record(self, data={}):\\n # Create a config file\\n if not self.config_file:\\n self.config_file = \\\"./default.config\\\"\\n\\n # Create empty config json file if not there\\n if not os.path.isfile(self.config_file):\\n with open(self.config_file, 'w') as f:\\n d = json.dumps({})\\n f.write(d)\\n\\n # This structure ensures that for different servers, there can exist\\n # multiple licenses (`license_key`), which contains one `device_token`\\n # each and multiple users (identified by `user_email`), each with its\\n # own `user_token`.\\n\\n # Overwrite values with current values\\n if not data or data == {}:\\n with open(self.config_file, 'r') as f:\\n data = json.load(f)\\n data[self.server] = {}\\n if self.license_key != '':\\n data[self.server][self.license_key] = {}\\n if self.device_token != '':\\n data[self.server][self.license_key][\\\"device_token\\\"] = self.device_token\\n if self.user.email != '':\\n data[self.server][self.license_key][self.user.email] = {}\\n if self.user_token != '':\\n data[self.server][self.license_key][self.user.email][\\\"user_token\\\"] = self.user_token\\n else:\\n data = data\\n\\n # Clean up the remaining values (i.e. get rid of it if it's empty)\\n copied = copy.deepcopy(data)\\n for server in copied.keys():\\n if server not in self.__valid_servers.keys():\\n data.pop(server, None)\\n\\n for key in copied[server].keys():\\n data[server].pop('', None)\\n data[server].pop(' ', None)\\n if copied[server][key] == {}:\\n data[server].pop(key, None)\\n\\n for k in copied[server][key].keys():\\n if k != \\\"device_token\\\":\\n data[server][key].pop('', None)\\n data[server][key].pop(' ', None)\\n if copied[server][key][k] == {} or copied[server][key][k] == \\\"\\\":\\n data[server][key].pop(k, None)\\n\\n with open(self.config_file, 'w') as f:\\n d = json.dumps(data)\\n f.write(d)\",\n \"def deserialize(self, str):\\n try:\\n if self.header is None:\\n self.header = std_msgs.msg.Header()\\n end = 0\\n _x = self\\n start = end\\n end += 12\\n (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _get_struct_3I().unpack(str[start:end])\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n start = end\\n end += length\\n if python3:\\n self.header.frame_id = str[start:end].decode('utf-8')\\n else:\\n self.header.frame_id = str[start:end]\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n start = end\\n end += length\\n if python3:\\n self.canmsg = str[start:end].decode('utf-8')\\n else:\\n self.canmsg = str[start:end]\\n _x = self\\n start = end\\n end += 30\\n (_x.track_id, _x.track_lat_rate, _x.track_group_changed, _x.track_status, _x.track_angle, _x.track_range, _x.track_bridge_object, _x.track_rolling_count, _x.track_width, _x.track_range_accel, _x.track_med_range_mode, _x.track_range_rate,) = _get_struct_Bf2B2f2B2fBf().unpack(str[start:end])\\n self.track_group_changed = bool(self.track_group_changed)\\n self.track_bridge_object = bool(self.track_bridge_object)\\n self.track_rolling_count = bool(self.track_rolling_count)\\n return self\\n except struct.error as e:\\n raise genpy.DeserializationError(e) #most likely buffer underfill\",\n \"def _decode_header(self):\\n #header = self.file_content[0:6]\\n log_screen_descr = self.file_content[6:13]\\n self.canvas_width = log_screen_descr[0] + (log_screen_descr[1]<<8)\\n self.canvas_height = log_screen_descr[2] + (log_screen_descr[3]<<8)\\n # is there a global color table? (usually yes)\\n flags = log_screen_descr[4]\\n self.glob_col_table = (flags & 0b10000000) != 0\\n\\n # determine the number of bits per primary color value\\n self.color_resolution = (flags & 0b01110000) >> 4\\n self.bits_per_pixel = self.color_resolution + 1\\n\\n # If the value is 1, then the colors in the global color table are sorted\\n # in order of \\\"decreasing importance,\\\" which typically means \\\"decreasing\\n # frequency\\\" in the image\\n self.sort_flag = (flags & 0b00001000) != 0\\n\\n # If this value is N, then the actual table size is 2^(N+1).\\n self.glob_col_table_sz = 1 << ((flags & 0b00000111)+1)\\n\\n self.bg_color_index = log_screen_descr[5]\\n self.pix_asp_ratio = log_screen_descr[6]\",\n \"def _unpack(self, headerBytes):\\n xtraH = struct.unpack(self.PACKAGING_FORMAT, headerBytes)\\n\\n self.qubit_id = xtraH[0]\\n self.remote_app_id = xtraH[1]\\n self.remote_node = xtraH[2]\\n self.cmdLength = xtraH[3]\\n self.remote_port = xtraH[4]\\n self.step = xtraH[5]\",\n \"def upload_initial_data():\\n data = {\\\"updated\\\":1512866292573,\\\"data\\\":[[[\\\"DAY %\\\",\\\"PPS (CAD)\\\",\\\"TKR\\\",\\\"NAME\\\",\\\"SECTOR\\\",\\\"EX.\\\",\\\"ALT. TKR\\\",\\\"VOL\\\",\\\"VOL @ CRNT $\\\",\\\"MC ($MM)\\\"],[\\\"5.84%\\\",\\\"1.45\\\",\\\"ABCN\\\",\\\"ABcann Medicinals\\\",\\\"BioTech\\\",\\\"CVE\\\",\\\"ABCCF\\\",\\\"901,940\\\",\\\"1,307,813\\\",\\\"78.49\\\"],[\\\"6.14%\\\",\\\"7.09\\\",\\\"ACB\\\",\\\"Aurora Cannabis\\\",\\\"Cultivation & Retail\\\",\\\"TSE\\\",\\\"ACBFF\\\",\\\"13,927,205\\\",\\\"98,743,883.45\\\",\\\"2,861.53\\\"],[\\\"9.09%\\\",\\\"0.24\\\",\\\"ACG\\\",\\\"Alliance Growers \\\",\\\"AgTech\\\",\\\"CNSX\\\",\\\"--\\\",\\\"1,189,385\\\",\\\"285,452.4\\\",\\\"\\\"],[\\\"0.00%\\\",\\\"0.10\\\",\\\"AFI\\\",\\\"Affinor Growers\\\",\\\"AgTech\\\",\\\"CNSX\\\",\\\"RSSFF\\\",\\\"210,310\\\",\\\"21,031\\\",\\\"\\\"],[\\\"3.22%\\\",\\\"13.47\\\",\\\"APH\\\",\\\"Aphria\\\",\\\"Cultivation & Retail\\\",\\\"TSE\\\",\\\"APHQF\\\",\\\"2,663,133\\\",\\\"35,872,401.51\\\",\\\"2,042.08\\\"],[\\\"13.95%\\\",\\\"0.25\\\",\\\"ATT\\\",\\\"Abattis Bio\\\",\\\"BioTech\\\",\\\"CNSX\\\",\\\"ATTBF\\\",\\\"2,706,357\\\",\\\"676,589.25\\\",\\\"39.86\\\"],[\\\"0.00%\\\",\\\"2.03\\\",\\\"BE\\\",\\\"Beleave\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"BLEVF\\\",\\\"597,909\\\",\\\"1,213,755.27\\\",\\\"\\\"],[\\\"1.28%\\\",\\\"1.58\\\",\\\"BLO\\\",\\\"Cannabix Tech\\\",\\\"LawTech\\\",\\\"CNSX\\\",\\\"BLOZF\\\",\\\"465,869\\\",\\\"736,073.02\\\",\\\"136.61\\\"],[\\\"-2.20%\\\",\\\"0.89\\\",\\\"CBW\\\",\\\"Cannabis Wheaton \\\",\\\"Investing & Finance\\\",\\\"CVE\\\",\\\"KWFLF\\\",\\\"815,477\\\",\\\"725,774.53\\\",\\\"234.57\\\"],[\\\"-0.65%\\\",\\\"19.93\\\",\\\"CMED\\\",\\\"Cannimed\\\",\\\"Cultivation & Retail\\\",\\\"TSE\\\",\\\"CMMDF\\\",\\\"130,722\\\",\\\"2,605,289.46\\\",\\\"457.69\\\"],[\\\"12.73%\\\",\\\"0.62\\\",\\\"CMM\\\",\\\"Canabo Medical\\\",\\\"MedCare\\\",\\\"CVE\\\",\\\"CAMDF\\\",\\\"330,404\\\",\\\"204,850.48\\\",\\\"23.54\\\"],[\\\"-2.87%\\\",\\\"2.71\\\",\\\"CRZ\\\",\\\"Cannaroyalty\\\",\\\"Investing & Finance\\\",\\\"CNSX\\\",\\\"CNNRF\\\",\\\"961,449\\\",\\\"2,605,526.79\\\",\\\"115.09\\\"],[\\\"-6.67%\\\",\\\"0.28\\\",\\\"CYX\\\",\\\"Calyx Bio\\\",\\\"AgTech\\\",\\\"CVE\\\",\\\"CLYXF\\\",\\\"2,120,562\\\",\\\"593,757.36\\\",\\\"24.23\\\"],[\\\"0.00%\\\",\\\"1.23\\\",\\\"DOJA\\\",\\\"DOJA Cannabis\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"DJACF\\\",\\\"206,635\\\",\\\"254,161.05\\\",\\\"72.27\\\"],[\\\"-4.40%\\\",\\\"0.44\\\",\\\"DVA\\\",\\\"Delivra\\\",\\\"BioTech\\\",\\\"CVE\\\",\\\"--\\\",\\\"89,485\\\",\\\"39,373.4\\\",\\\"19.55\\\"],[\\\"6.52%\\\",\\\"0.25\\\",\\\"EAT\\\",\\\"Nutritional High\\\",\\\"Marijuana Edibles & Extracts\\\",\\\"CNSX\\\",\\\"SPLIF\\\",\\\"3,067,636\\\",\\\"766,909\\\",\\\"61.54\\\"],[\\\"-1.20%\\\",\\\"1.64\\\",\\\"EMC\\\",\\\"Emblem\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"EMMBF\\\",\\\"411,764\\\",\\\"675,292.96\\\",\\\"130.60\\\"],[\\\"2.05%\\\",\\\"3.98\\\",\\\"EMH\\\",\\\"Emerald\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"TBQBF\\\",\\\"1,430,067\\\",\\\"5,691,666.66\\\",\\\"374.34\\\"],[\\\"-5.88%\\\",\\\"0.48\\\",\\\"FFT\\\",\\\"Future Farm Tech\\\",\\\"AgTech\\\",\\\"CNSX\\\",\\\"AGSTF\\\",\\\"1,291,240\\\",\\\"619,795.2\\\",\\\"0.61\\\"],[\\\"1.06%\\\",\\\"1.90\\\",\\\"FIRE\\\",\\\"Supreme Pharma\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"SPRWF\\\",\\\"1,275,906\\\",\\\"2,424,221.4\\\",\\\"391.96\\\"],[\\\"5.26%\\\",\\\"0.10\\\",\\\"GHG\\\",\\\"Global Hemp\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"GBHPF\\\",\\\"764,350\\\",\\\"76,435\\\",\\\"\\\"],[\\\"3.28%\\\",\\\"0.31\\\",\\\"GLH\\\",\\\"Golden Leaf\\\",\\\"Marijuana Products\\\",\\\"CNSX\\\",\\\"GLDFF\\\",\\\"4,298,567\\\",\\\"1,332,555.77\\\",\\\"116.96\\\"],[\\\"-1.96%\\\",\\\"0.50\\\",\\\"HC\\\",\\\"High Hampton Holdings\\\",\\\"Investing & Finance\\\",\\\"CNSX\\\",\\\"--\\\",\\\"727,116\\\",\\\"363,558\\\",\\\"\\\"],[\\\"1.89%\\\",\\\"0.54\\\",\\\"HIP\\\",\\\"Newstirke Resources \\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"NWKRF\\\",\\\"431,875\\\",\\\"233,212.5\\\",\\\"210.35\\\"],[\\\"8.91%\\\",\\\"1.10\\\",\\\"HVST\\\",\\\"Harvest One Cannabis\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"HRVOF\\\",\\\"2,192,877\\\",\\\"2,412,164.7\\\",\\\"98.10\\\"],[\\\"8.89%\\\",\\\"0.98\\\",\\\"ICC\\\",\\\"International Cannabis\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"ICCLF\\\",\\\"123,538\\\",\\\"121,067.24\\\",\\\"110.84\\\"],[\\\"0.00%\\\",\\\"1.62\\\",\\\"IMH\\\",\\\"Invictus MD\\\",\\\"Investing & Finance\\\",\\\"CVE\\\",\\\"IVITF\\\",\\\"781,924\\\",\\\"1,266,716.88\\\",\\\"129.87\\\"],[\\\"12.50%\\\",\\\"0.90\\\",\\\"IN\\\",\\\"Inmed Pharma\\\",\\\"BioTech\\\",\\\"CNSX\\\",\\\"IMLFF\\\",\\\"3,846,586\\\",\\\"3,461,927.4\\\",\\\"\\\"],[\\\"2.27%\\\",\\\"1.80\\\",\\\"ISOL\\\",\\\"Isodiol International \\\",\\\"Hemp Products\\\",\\\"CNSX\\\",\\\"LAGBF\\\",\\\"8,514,952\\\",\\\"15,326,913.6\\\",\\\"\\\"],[\\\"7.84%\\\",\\\"0.28\\\",\\\"KALY\\\",\\\"Kalytera Therapeutics\\\",\\\"BioTech\\\",\\\"CVE\\\",\\\"QUEZD\\\",\\\"5,634,186\\\",\\\"1,577,572.08\\\",\\\"34.74\\\"],[\\\"-1.72%\\\",\\\"0.57\\\",\\\"LDS\\\",\\\"Lifestyle Delivery Systems\\\",\\\"BioTech\\\",\\\"CNSX\\\",\\\"LDSYF\\\",\\\"685,628\\\",\\\"390,807.96\\\",\\\"51.44\\\"],[\\\"0.19%\\\",\\\"15.50\\\",\\\"LEAF\\\",\\\"MedReleaf Corp\\\",\\\"Cultivation & Retail\\\",\\\"TSE\\\",\\\"MEDFF\\\",\\\"229,190\\\",\\\"3,552,445\\\",\\\"1,459.18\\\"],[\\\"2.33%\\\",\\\"0.44\\\",\\\"LIB\\\",\\\"Liberty Leaf Holdings\\\",\\\"Investing & Finance\\\",\\\"CNSX\\\",\\\"LIBFF\\\",\\\"4,555,082\\\",\\\"2,004,236.08\\\",\\\"\\\"],[\\\"10.42%\\\",\\\"1.59\\\",\\\"LXX\\\",\\\"Lexaria Bio\\\",\\\"Hemp Products\\\",\\\"CNSX\\\",\\\"LXRP\\\",\\\"1,523,338\\\",\\\"2,422,107.42\\\",\\\"\\\"],[\\\"-1.38%\\\",\\\"2.14\\\",\\\"MARI\\\",\\\"Maricann Group\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"MRRCF\\\",\\\"678,106\\\",\\\"1,451,146.84\\\",\\\"157.10\\\"],[\\\"3.26%\\\",\\\"0.95\\\",\\\"MDM\\\",\\\"Marapharm\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"MRPHF\\\",\\\"209,019\\\",\\\"198,568.05\\\",\\\"\\\"],[\\\"0.00%\\\",\\\"0.57\\\",\\\"MGW\\\",\\\"Maple Leaf Green World\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"MGWFF\\\",\\\"367,479\\\",\\\"209,463.03\\\",\\\"83.83\\\"],[\\\"7.37%\\\",\\\"1.02\\\",\\\"MJ\\\",\\\"True Leaf\\\",\\\"Hemp Pet Chews\\\",\\\"CNSX\\\",\\\"TLFMF\\\",\\\"164,101\\\",\\\"167,383.02\\\",\\\"\\\"],[\\\"2.27%\\\",\\\"4.50\\\",\\\"MJN\\\",\\\"Pharmacan /Cronos\\\",\\\"Investing & Finance\\\",\\\"CVE\\\",\\\"PRMCF\\\",\\\"419,922\\\",\\\"1,889,649\\\",\\\"675.43\\\"],[\\\"4.23%\\\",\\\"2.71\\\",\\\"MYM\\\",\\\"My Marijuana\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"--\\\",\\\"1,066,122\\\",\\\"2,889,190.62\\\",\\\"\\\"],[\\\"4.40%\\\",\\\"0.95\\\",\\\"N\\\",\\\"Namaste Tech\\\",\\\"Consumption Devices\\\",\\\"CNSX\\\",\\\"NXTTF\\\",\\\"5,714,764\\\",\\\"5,429,025.8\\\",\\\"192.50\\\"],[\\\"0.00%\\\",\\\"0.10\\\",\\\"NF\\\",\\\"New Age Farm\\\",\\\"Hemp Products\\\",\\\"CNSX\\\",\\\"NWGFF\\\",\\\"3,938,476\\\",\\\"393,847.6\\\",\\\"\\\"],[\\\"-7.27%\\\",\\\"0.25\\\",\\\"NSP\\\",\\\"Naturally Splendid\\\",\\\"Hemp Products\\\",\\\"CVE\\\",\\\"NSPDF\\\",\\\"484,812\\\",\\\"121,203\\\",\\\"24.42\\\"],[\\\"4.99%\\\",\\\"3.79\\\",\\\"OGI\\\",\\\"Organigram\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"OGRMF\\\",\\\"3,654,843\\\",\\\"13,851,854.97\\\",\\\"375.89\\\"],[\\\"1.15%\\\",\\\"0.88\\\",\\\"PUF\\\",\\\"PUF Ventures\\\",\\\"Consumption Devices\\\",\\\"CNSX\\\",\\\"PUFXF\\\",\\\"719,534\\\",\\\"633,189.92\\\",\\\"45.85\\\"],[\\\"10.68%\\\",\\\"1.14\\\",\\\"RHT\\\",\\\"Reliq Health Tech\\\",\\\"Mobile Software\\\",\\\"CVE\\\",\\\"RQHTF\\\",\\\"1,564,567\\\",\\\"1,783,606.38\\\",\\\"98.74\\\"],[\\\"4.05%\\\",\\\"1.80\\\",\\\"RTI\\\",\\\"Radient Technologies\\\",\\\"Extraction\\\",\\\"CVE\\\",\\\"RDDTF\\\",\\\"2,181,473\\\",\\\"3,926,651.4\\\",\\\"345.53\\\"],[\\\"3.64%\\\",\\\"0.28\\\",\\\"RVV\\\",\\\"Revive Therapeutics\\\",\\\"Medication\\\",\\\"CVE\\\",\\\"RVVTF\\\",\\\"399,705\\\",\\\"111,917.4\\\",\\\"15.50\\\"],[\\\"-2.90%\\\",\\\"0.67\\\",\\\"SUN\\\",\\\"Wildflower\\\",\\\"Hemp Products\\\",\\\"CNSX\\\",\\\"WLDFF\\\",\\\"87,197\\\",\\\"58,421.99\\\",\\\"29.48\\\"],[\\\"-0.67%\\\",\\\"4.45\\\",\\\"SXP\\\",\\\"Supremex\\\",\\\"Packaging\\\",\\\"TSE\\\",\\\"SUMXF\\\",\\\"27,015\\\",\\\"120,216.75\\\",\\\"126.40\\\"],[\\\"0.00%\\\",\\\"0.76\\\",\\\"TBP\\\",\\\"Tetra Bio-Pharma\\\",\\\"BioTech\\\",\\\"CVE\\\",\\\"GRPOF\\\",\\\"497,745\\\",\\\"378,286.2\\\",\\\"88.67\\\"],[\\\"2.44%\\\",\\\"2.10\\\",\\\"TER\\\",\\\"TerrAscend Corp\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"--\\\",\\\"270,176\\\",\\\"567,369.6\\\",\\\"\\\"],[\\\"4.29%\\\",\\\"0.73\\\",\\\"THC\\\",\\\"THC Biomed\\\",\\\"BioTech\\\",\\\"CNSX\\\",\\\"THCBF\\\",\\\"818,162\\\",\\\"597,258.26\\\",\\\"81.29\\\"],[\\\"3.55%\\\",\\\"3.21\\\",\\\"THCX\\\",\\\"Hydropothecary Corp\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"HYYDF\\\",\\\"1,581,640\\\",\\\"5,077,064.4\\\",\\\"282.37\\\"],[\\\"8.22%\\\",\\\"0.79\\\",\\\"TNY\\\",\\\"Tinley Beverage Co\\\",\\\"Beverage\\\",\\\"CNSX\\\",\\\"QRSRF\\\",\\\"945,154\\\",\\\"746,671.66\\\",\\\"57.81\\\"],[\\\"3.49%\\\",\\\"7.70\\\",\\\"TRST\\\",\\\"CannTrust\\\",\\\"Cultivation & Biotech\\\",\\\"CNSX\\\",\\\"CNTTF\\\",\\\"368,892\\\",\\\"2,840,468.4\\\",\\\"699.98\\\"],[\\\"-8.04%\\\",\\\"1.03\\\",\\\"VGW\\\",\\\"Valens Groworks\\\",\\\"BioTech\\\",\\\"CNSX\\\",\\\"MYMSF\\\",\\\"23,285\\\",\\\"23,983.55\\\",\\\"62.77\\\"],[\\\"0.00%\\\",\\\"0.52\\\",\\\"VIN\\\",\\\"Vinergy Resources\\\",\\\"Investing & Finance\\\",\\\"CNSX\\\",\\\"VNNYF\\\",\\\"0\\\",\\\"\\\",\\\"\\\"],[\\\"-2.50%\\\",\\\"0.39\\\",\\\"VP\\\",\\\"Vodis Pharma\\\",\\\"Cultivation & Retail\\\",\\\"CNSX\\\",\\\"VDQSF\\\",\\\"52,661\\\",\\\"20,537.79\\\",\\\"\\\"],[\\\"6.67%\\\",\\\"0.80\\\",\\\"VRT\\\",\\\"Veritas Pharma\\\",\\\"BioTech\\\",\\\"CNSX\\\",\\\"VRTHF\\\",\\\"377,901\\\",\\\"302,320.8\\\",\\\"\\\"],[\\\"6.41%\\\",\\\"19.42\\\",\\\"WEED\\\",\\\"Canopy Growth\\\",\\\"Cultivation & Retail\\\",\\\"TSE\\\",\\\"TWMJF\\\",\\\"4,940,034\\\",\\\"95,935,460.28\\\",\\\"3,706.63\\\"],[\\\"6.25%\\\",\\\"2.38\\\",\\\"WMD\\\",\\\"WeedMD\\\",\\\"Cultivation & Retail\\\",\\\"CVE\\\",\\\"WDDMF\\\",\\\"1,174,148\\\",\\\"2,794,472.24\\\",\\\"124.71\\\"],[\\\"3.36%\\\",\\\"14.75\\\",\\\"HMMJ\\\",\\\"Horizons Marijuana Life Sciences\\\",\\\"Canadian Marijuana ETF\\\",\\\"TSE\\\",\\\"HMLSF\\\",\\\"336,579\\\",\\\"4,964,540.25\\\",\\\"197.64\\\"]]],\\\"sheetnames\\\":[\\\"ALLSHOW\\\"]}\\n \\n exchange_suffixes = {'TSE': 'TO', 'CVE': 'V'}\\n\\n # create sector\\n sector, _ = Sector.objects.get_or_create(name=\\\"Cannabis\\\", slug='cannabis')\\n\\n # create currency\\n currency, _ = Currency.objects.get_or_create(symbol='CAD', defaults={'character':'$', 'name':'Canadian Dollar'})\\n us_currency, _ = Currency.objects.get_or_create(symbol='USD', defaults={'character':'$', 'name':'US Dollar'})\\n\\n # OTC exchange\\n otc, _ = Exchange.objects.get_or_create(symbol='OTC', defaults={'name':'OTC', 'currency': us_currency})\\n\\n # iterate over each item in our table, make the items\\n for row in data[\\\"data\\\"][0][1:]:\\n # percent = float(row[0].replace(\\\"%\\\",\\\"\\\"))\\n suffix = exchange_suffixes[row[5]] if row[5] in exchange_suffixes else ''\\n exchange, _ = Exchange.objects.get_or_create(symbol=row[5], defaults={'name':row[5], 'currency':currency, 'ticker_suffix': suffix})\\n company, _ = Company.objects.get_or_create(name=row[3], defaults={'sector':sector})\\n stock, _ = Stock.objects.get_or_create(ticker=row[2], defaults={\\n 'company': company,\\n 'exchange': exchange,\\n 'market_cap': float(row[9].replace(\\\",\\\",\\\"\\\")) * 1000000 if row[9] else 0.0,\\n # 'previous_close': float(row[1]) - float(row[1]) * percent / 100,\\n # 'open': float(row[1]),\\n # 'current': float(row[1]),\\n # 'volume': float(row[8].replace(\\\",\\\",\\\"\\\")) if row[8] else 0.0,\\n })\\n stock.save()\\n\\n if row[4]:\\n tag, _ = Tag.objects.get_or_create(name=row[4])\\n company.tags.add(tag)\\n\\n if row[6] and not row[6] == \\\"--\\\":\\n stock, _ = Stock.objects.get_or_create(ticker=row[6], defaults={'company':company, 'exchange':otc})\\n\\n\\n print data\",\n \"def Load(self):\\n\\t\\tfile = open(self.fileName, 'r')\\n\\t\\tself.hdr = file.readline().split('\\\\n')[0].split(',')\\n\\t\\t\\n\\t\\tfor line in file.readlines():\\n\\t\\t\\ttokens = line.split('\\\\n')[0].split(',')\\n\\t\\t\\tif int(tokens[1]) == 0:\\n\\t\\t\\t\\tself.h0.append(tokens[0])\\n\\t\\t\\telse:\\n\\t\\t\\t\\tself.h1.append(tokens[0])\\n\\t\\tfile.close()\\n\\t\\tself.numH1 = len(self.h1)\\n\\t\\tself.numH0 = len(self.h0)\",\n \"def read_header(infile):\\n h = dict()\\n fid = open(infile, 'r+b')\\n h['filename'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 20))\\n h['parent_filename'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 20))\\n h['comments1'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 80))\\n h['comments2'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 80))\\n h['energy_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['config_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['file_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['trans_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['scan_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['data_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['date_modified'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 16))\\n h['frequency'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['mat_velocity'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['num_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\\n h['num_polarization_channels'] =np.fromfile(fid, dtype = np.int16,count = 1)\\n h['spare00'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['adc_min_voltage'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['adc_max_voltage'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['band_width'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['spare01'] = np.fromfile(fid, dtype = np.int16, count = 5)\\n h['polarization_type'] = np.fromfile(fid, dtype = np.int16, count = 4)\\n h['record_header_size'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['word_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['word_precision'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['min_data_value'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['max_data_value'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['avg_data_value'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['data_scale_factor'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['data_units'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['surf_removal'] = np.fromfile(fid, dtype = np.uint16, count = 1)\\n h['edge_weighting'] = np.fromfile(fid, dtype = np.uint16, count = 1)\\n h['x_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\\n h['y_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\\n h['z_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\\n h['t_units'] = np.fromfile(fid, dtype = np.uint16, count = 1)\\n h['spare02'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['x_return_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_return_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_return_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['scan_orientation'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['scan_direction'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['data_storage_order'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['scanner_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['x_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['t_inc'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['num_x_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\\n h['num_y_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\\n h['num_z_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\\n h['num_t_pts'] = np.fromfile(fid, dtype = np.int32, count = 1)\\n h['x_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_speed'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['x_acc'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_acc'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_acc'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['x_motor_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_motor_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_motor_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['x_encoder_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_encoder_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_encoder_res'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['date_processed'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 8))\\n h['time_processed'] = b''.join(np.fromfile(fid, dtype = 'S1', count = 8))\\n h['depth_recon'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['x_max_travel'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_max_travel'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['elevation_offset_angle'] = np.fromfile(fid,dtype = np.float32, count = 1)\\n h['roll_offset_angle'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_max_travel'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['azimuth_offset_angle'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['adc_type'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['spare06'] = np.fromfile(fid, dtype = np.int16, count = 1)\\n h['scanner_radius'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['x_offset'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['y_offset'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['z_offset'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['t_delay'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['range_gate_start'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['range_gate_end'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['ahis_software_version'] = np.fromfile(fid, dtype = np.float32, count = 1)\\n h['spare_end'] = np.fromfile(fid, dtype = np.float32, count = 10)\\n return h\",\n \"def _decode_data_dict(self, data_dict: dict) -> dict:\\n if ENCODED_DATA_KEY not in data_dict:\\n return data_dict\\n\\n encoded_data = data_dict[ENCODED_DATA_KEY]\\n _buffer = io.BytesIO(encoded_data)\\n data_dict = torch.load(\\n _buffer,\\n map_location=\\\"cpu\\\"\\n # Not using ray.cloudpickle here as it doesn't\\n # define an Unpickler (as it is not necessary).\\n )\\n return data_dict\",\n \"def headersFromRawFile(self, rawFile: str, headers: Dict) -> None:\\n dFile = open(os.path.join(self.dataPath, rawFile), \\\"r\\\", encoding=\\\"ISO-8859-1\\\")\\n generalHeaderString = dFile.read(1000) # this should be long enough\\n generalSplit = generalHeaderString.split()\\n # read GENERAL HEADER\\n generalHeader = {}\\n generalHeader[\\\"recLength\\\"] = int(generalSplit[0])\\n generalHeader[\\\"fileType\\\"] = generalSplit[1]\\n generalHeader[\\\"wordLength\\\"] = int(generalSplit[2])\\n generalHeader[\\\"version\\\"] = generalSplit[3]\\n generalHeader[\\\"procId\\\"] = generalSplit[4]\\n generalHeader[\\\"numCh\\\"] = int(generalSplit[5])\\n generalHeader[\\\"totalRec\\\"] = int(generalSplit[6])\\n generalHeader[\\\"firstEvent\\\"] = int(generalSplit[7])\\n generalHeader[\\\"numEvent\\\"] = int(generalSplit[8])\\n generalHeader[\\\"extend\\\"] = int(generalSplit[9])\\n\\n # read EVENT HEADER - there can be multiple of these, but normally only the one\\n # Multiple events are largely deprecated. Only a single event is used\\n eventHeaders = []\\n fileSize = os.path.getsize(os.path.join(self.dataPath, rawFile))\\n record = generalHeader[\\\"firstEvent\\\"]\\n for ir in range(0, generalHeader[\\\"numEvent\\\"]):\\n seekPt = (record - 1) * generalHeader[\\\"recLength\\\"]\\n if not seekPt > fileSize:\\n # seek from beginning of file\\n dFile.seek(seekPt, 0)\\n # read extra to make sure\\n eventString = dFile.read(1000)\\n eventSplit = eventString.split()\\n eH = {}\\n eH[\\\"start\\\"] = int(eventSplit[0])\\n eH[\\\"startms\\\"] = int(eventSplit[1])\\n eH[\\\"stop\\\"] = int(eventSplit[2])\\n eH[\\\"stopms\\\"] = int(eventSplit[3])\\n eH[\\\"cvalue1\\\"] = float(eventSplit[4])\\n eH[\\\"cvalue2\\\"] = float(eventSplit[5])\\n eH[\\\"cvalue3\\\"] = float(eventSplit[6])\\n eH[\\\"EHInfile\\\"] = int(eventSplit[7])\\n eH[\\\"nextEH\\\"] = int(eventSplit[8])\\n eH[\\\"previousEH\\\"] = int(eventSplit[9])\\n eH[\\\"numData\\\"] = int(eventSplit[10])\\n eH[\\\"startData\\\"] = int(eventSplit[11])\\n eH[\\\"extended\\\"] = int(eventSplit[12])\\n eventHeaders.append(eH)\\n if eH[\\\"nextEH\\\"] < generalHeader[\\\"totalRec\\\"]:\\n record = eH[\\\"nextEH\\\"] # set to go to next eH\\n else:\\n break # otherwise break out of for loops\\n # close the data file\\n dFile.close()\\n # now compare number of samples with that calculated previously\\n if eventHeaders[0][\\\"numData\\\"] != headers[\\\"num_samples\\\"]:\\n self.printWarning(\\\"Data file: {}\\\".format(dFile))\\n self.printWarning(\\n \\\"Number of samples in raw file header {} does not equal that calculated from data {}\\\".format(\\n eventHeaders[0][\\\"numData\\\"], headers[\\\"num_samples\\\"]\\n )\\n )\\n self.printWarning(\\\"Number of samples calculated from data will be used\\\")\\n # set the byte offset for the file\\n self.dataByteOffset[rawFile] = (\\n eventHeaders[0][\\\"startData\\\"] - 1\\n ) * generalHeader[\\\"recLength\\\"]\\n self.recChannels[rawFile] = generalHeader[\\\"numCh\\\"]\",\n \"def decodemeta(data):\\n d = {}\\n for l in data.split('\\\\0'):\\n if l:\\n key, value = l.split(':')\\n d[key] = value\\n return d\",\n \"def loads(self, data):\\n self._id = data.get('id', -1)\\n self._created = data.get('created', 0) # datetime.strptime(data.get('created', '1970-01-01T00:00:00'), '%Y-%m-%dT%H:%M:%S').timestamp()\\n self._stage = data.get('stage', 0) # self.stage_from_str(data.get('stage', ''))\\n self._dir = data.get('direction', 0) # self.direction_from_str(data.get('direction', ''))\\n self._timeframe = data.get('timeframe') # timeframe_from_str(data.get('timeframe', 't'))\\n self._expiry = data.get('expiry', 0) # datetime.strptime(data.get('expiry', '1970-01-01T00:00:00'), '%Y-%m-%dT%H:%M:%S').timestamp()\",\n \"def _read_old_header(self, raw):\\n\\n byte_count = 0\\n\\n data_size = 4\\n self.label = struct.unpack('<4s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.version = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.revision = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 26\\n self.date = struct.unpack('<26s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.file_format = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.file_type = struct.unpack('<4s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.original_file_name = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.reference_file_name = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.related_file_name_a = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.related_file_name_b = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.related_file_name_c = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.related_file_name_d = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 82\\n self.annotate = struct.unpack('<82s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 33\\n self.instrument_model = struct.unpack('<33s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 33\\n self.instrument_serial_number = struct.unpack('<33s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 33\\n self.software_version_number = struct.unpack('<33s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 33\\n self.crystal_material = struct.unpack('<33s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.laser_wavelength_microns = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.laser_null_doubling = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.optical_ratio = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.dispersion_constant_xc = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.dispersion_constant_xm = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.dispersion_constant_xb = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.interferogram_size = struct.unpack('<H',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.interferogram_center.append(struct.unpack('<H',\\n raw[byte_count:byte_count+data_size])[0])\\n byte_count += data_size\\n\\n data_size = 2\\n self.interferogram_center.append(struct.unpack('<H',\\n raw[byte_count:byte_count+data_size])[0])\\n byte_count += data_size\\n\\n data_size = 2\\n self.acquire_mode = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.emissivity = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.apodization = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.zero_fill = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.run_time_math = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.fft_size = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.number_of_coadds = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 2\\n self.number_of_igrams = struct.unpack('<h',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.amb_temperature = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.inst_temperature = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.wbb_temperature = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.cbb_temperature = struct.unpack('<f',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 20\\n self.spare_i = struct.unpack('<hhhhhhhhhh',\\n raw[byte_count:byte_count+data_size])\\n byte_count += data_size\\n\\n data_size = 40\\n self.spare_f = struct.unpack('<ffffffffff',\\n raw[byte_count:byte_count+data_size])\\n byte_count += data_size\\n\\n data_size = 40\\n self.spare_l = struct.unpack('<ffffffffff',\\n raw[byte_count:byte_count+data_size])\\n byte_count += data_size\\n\\n data_size = 65\\n self.spare_na = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.spare_nb = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.spare_nc = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.spare_nd = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 65\\n self.spare_ne = struct.unpack('<65s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\\n\\n data_size = 4\\n self.header_end = struct.unpack('<4s',\\n raw[byte_count:byte_count+data_size])[0]\\n byte_count += data_size\",\n \"def verify_header (filename, htypes=None):\\n\\n # dictionary\\n dict_head = {\\n # raw header\\n # commenting out SIMPLE, BSCALE and BZERO - basic keywords\\n # that will be present in images but not in binary fits tables\\n #'SIMPLE': {'htype':'raw', 'dtype':bool, 'DB':False, 'None_OK':True},\\n #'BSCALE': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\\n #'BZERO': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'BITPIX': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'NAXIS': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'NAXIS1': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'NAXIS2': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'BUNIT': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n #'CCD-AMP': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'SET-TEMP': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'CCD-TEMP': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'XBINNING': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'YBINNING': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n #'CCD-SET': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'ALTITUDE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'AZIMUTH': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'DOMEAZ': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'RADESYS': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'EPOCH': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'RA': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\\n 'RA-REF': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n #'RA-TEL': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'DEC': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\\n 'DEC-REF': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n #'DEC-TEL': {'htype':'raw', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'HA': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\\n 'FLIPSTAT': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'EXPTIME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\\n 'ISTRACKI': {'htype':'raw', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'ACQSTART': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'ACQEND': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'GPSSTART': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'GPSEND': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'GPS-SHUT': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'DATE-OBS': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'MJD-OBS': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\\n 'LST': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'UTC': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\\n 'TIMESYS': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'ORIGIN': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'MPC-CODE': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'TELESCOP': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'CL-BASE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RH-MAST': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RH-DOME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RH-AIRCO': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RH-PIER': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PRESSURE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-PIER': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-DOME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-ROOF': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-AIRCO': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-MAST': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-STRUT': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-CRING': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-SPIDER': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-FWN': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-FWS': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-M2HOLD': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-GUICAM': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-M1': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-CRYWIN': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-CRYGET': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-CRYCP': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PRES-CRY': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'WINDAVE': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'WINDGUST': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'WINDDIR': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'SITELAT': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'SITELONG': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'ELEVATIO': {'htype':'raw', 'dtype':int, 'DB':True, 'None_OK':True},\\n #'WEATIME': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'FILTER': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n #'FILTERID': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'CCD-ID': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'CONTROLL': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'DETSPEED': {'htype':'raw', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'CCD-NW': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'CCD-NH': {'htype':'raw', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'INSTRUME': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'FOCUSPOS': {'htype':'raw', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'IMAGETYP': {'htype':'raw', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'OBJECT': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'AIRMASS': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':False},\\n 'ORIGFILE': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'OBSERVER': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'ABOTVER': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'PROGNAME': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'PROGID': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'GUIDERST': {'htype':'raw', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'GUIDERFQ': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'TRAKTIME': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'ADCX': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'ADCY': {'htype':'raw', 'dtype':float, 'DB':True, 'None_OK':True},\\n #\\n # full header\\n 'BB-V': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'BB-START': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'KW-V': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'LOG': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'LOG-IMA': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'N-INFNAN': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'XTALK-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'XTALK-F': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'NONLIN-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'NONLIN-F': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'GAIN-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'GAIN': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'GAIN1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'GAIN16': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'OS-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'BIASMEAN': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'BIASM1': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'BIASM16': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RDNOISE': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RDN1': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RDN16': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'BIAS1A0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'BIAS1A1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'VFITOK1': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'BIAS16A0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'BIAS16A1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'VFITOK16': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'MBIAS-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'MBIAS-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'MB-NDAYS': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'SATURATE': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'NOBJ-SAT': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'MFLAT-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'MFLAT-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'MF-NDAYS': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'MFRING-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'MFRING-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'FRRATIO': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'COSMIC-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'NCOSMICS': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'SAT-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'NSATS': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'REDFILE': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'MASKFILE': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'S-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'S-V': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'S-NOBJ': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'S-FWHM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'S-FWSTD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'S-SEEING': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'S-SEESTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'S-ELONG': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'S-ELOSTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'S-BKG': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'S-BKGSTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'S-VIGNET': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'BKG-CORR': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'BKG-CHI2': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'BKG-CF1': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'BKG-CF16': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'BKG-FDEG': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'BKG-FC0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'A-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'A-V': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'A-INDEX': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'A-PSCALE': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'A-PSCALX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'A-PSCALY': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'A-ROT': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'A-ROTX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'A-ROTY': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'A-CAT-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'A-NAST': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'A-TNAST': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'A-NAMAX': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'A-DRA': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'A-DRASTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'A-DDEC': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'A-DDESTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PSF-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'PSF-V': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'PSF-RAD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-RADP': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-SIZE': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'PSF-FRAC': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-SAMP': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-CFGS': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'PSF-NOBJ': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'PSF-FIX': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'PSF-PLDG': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PSF-CHI2': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PSF-FWHM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-SEE': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PSF-PMIN': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-PMAX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-PMED': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-PSTD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-BMIN': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-BMAX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-BMED': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-BSTD': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-EMNM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-EMXM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-EMDM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-ESTM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FMNM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FMXM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FMDM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FSTM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-EMNG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-EMXG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-EMDG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-ESTG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FMNG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FMXG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FMDG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PSF-FSTG': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PC-P': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'PC-CAT-F': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':True},\\n 'PC-NCAL': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'PC-TNCAL': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PC-FNCAL': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PC-NCMAX': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PC-NCMIN': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PC-ZPFDG': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PC-ZPF0': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PC-TNSUB': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PC-NSUB': {'htype':'full', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'PC-MZPD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PC-MZPS': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PC-ZPDEF': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'PC-ZP': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PC-ZPSTD': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PC-EXTCO': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'AIRMASSC': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'RA-CNTR': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'DEC-CNTR': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'PC-AIRM': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'NSIGMA': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'LIMEFLUX': {'htype':'full', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'LIMMAG': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'NOBJECTS': {'htype':'full', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'RADECOFF': {'htype':'full', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'FORMAT-P': {'htype':'full', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'DUMCAT': {'htype':'full', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'QC-FLAG': {'htype':'full', 'dtype':str, 'DB':True, 'None_OK':False},\\n 'DATEFILE': {'htype':'full', 'dtype':str, 'DB':False, 'None_OK':True},\\n #\\n # transient header\\n 'SWARP-P': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'SWARP-V': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'Z-REF': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'Z-DXYLOC': {'htype':'trans', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'Z-DX': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-DY': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-DXSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-DYSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-FNRLOC': {'htype':'trans', 'dtype':bool, 'DB':False, 'None_OK':True},\\n 'Z-FNR': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-FNRSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-P': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'Z-V': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'Z-SIZE': {'htype':'trans', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'Z-BSIZE': {'htype':'trans', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'Z-SCMED': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-SCSTD': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'Z-FPEMED': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'Z-FPESTD': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'T-NSIGMA': {'htype':'trans', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'T-LFLUX': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'T-NTRANS': {'htype':'trans', 'dtype':int, 'DB':True, 'None_OK':True},\\n 'T-FTRANS': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-LMAG': {'htype':'trans', 'dtype':float, 'DB':True, 'None_OK':True},\\n 'T-NFAKE': {'htype':'trans', 'dtype':int, 'DB':False, 'None_OK':True},\\n 'T-FAKESN': {'htype':'trans', 'dtype':float, 'DB':False, 'None_OK':True},\\n 'MC-P': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'MC-V': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'MC-MODEL': {'htype':'trans', 'dtype':str, 'DB':False, 'None_OK':True},\\n 'TDUMCAT': {'htype':'trans', 'dtype':bool, 'DB':True, 'None_OK':False},\\n 'TQC-FLAG': {'htype':'trans', 'dtype':str, 'DB':True, 'None_OK':False},\\n }\\n\\n # read header of filename\\n if isfile (filename):\\n header = read_hdulist (filename, get_data=False, get_header=True)\\n else:\\n # return success=False if it does not exist\\n log.warning ('file {} does not exist; not able to verify its header'\\n .format(filename))\\n return False\\n\\n\\n # force [htypes] to be a list\\n htypes_list = list(htypes)\\n\\n # loop keys in dict_head\\n for key in dict_head.keys():\\n\\n # only check keywords with htype matching the input [htypes]\\n if dict_head[key]['htype'] not in htypes_list:\\n continue\\n\\n # check that key is present in header\\n if key in header:\\n\\n # provide warning if dtype not as expected and header\\n # keyword value is not 'None'\\n if (dict_head[key]['dtype'] != type(header[key]) and\\n header[key] != 'None'):\\n log.warning ('dtype of keyword {}: {} does not match the '\\n 'expected dtype: {} in header of {}'\\n .format(key, type(header[key]),\\n dict_head[key]['dtype'], filename))\\n\\n # if key goes to DataBase and value is 'None' or None\\n # while 'None_OK' is False, raise an exception\\n if (dict_head[key]['DB'] and not dict_head[key]['None_OK'] and\\n (header[key] is None or header[key] == 'None')):\\n msg = ('DataBase keyword {} not allowed to have \\\\'None\\\\' or '\\n 'None value in header of {}'.format(key, filename))\\n log.error (msg)\\n raise ValueError (msg)\\n\\n\\n else:\\n msg = 'keyword {} not present in header of {}'.format(key, filename)\\n # if keyword will be ingested into the database, raise an exception\\n if dict_head[key]['DB']:\\n log.error (msg)\\n raise KeyError (msg)\\n\\n else:\\n log.warning (msg)\\n\\n\\n return\",\n \"def read_data(filename):\\n # Store debug mode\\n debug = params.debug\\n params.debug = None\\n\\n # Initialize dictionary\\n header_dict = {}\\n\\n headername = filename + \\\".hdr\\\"\\n\\n with open(headername, \\\"r\\\") as f:\\n # Replace characters for easier parsing\\n hdata = f.read()\\n hdata = hdata.replace(\\\",\\\\n\\\", \\\",\\\")\\n hdata = hdata.replace(\\\"\\\\n,\\\", \\\",\\\")\\n hdata = hdata.replace(\\\"{\\\\n\\\", \\\"{\\\")\\n hdata = hdata.replace(\\\"\\\\n}\\\", \\\"}\\\")\\n hdata = hdata.replace(\\\" \\\\n \\\", \\\"\\\")\\n hdata = hdata.replace(\\\";\\\", \\\"\\\")\\n hdata = hdata.split(\\\"\\\\n\\\")\\n\\n # Loop through and create a dictionary from the header file\\n for i, string in enumerate(hdata):\\n if ' = ' in string:\\n header_data = string.split(\\\" = \\\")\\n header_dict.update({header_data[0].rstrip(): header_data[1].rstrip()})\\n elif ' : ' in string:\\n header_data = string.split(\\\" : \\\")\\n header_dict.update({header_data[0].rstrip(): header_data[1].rstrip()})\\n\\n # Reformat wavelengths\\n header_dict[\\\"wavelength\\\"] = header_dict[\\\"wavelength\\\"].replace(\\\"{\\\", \\\"\\\")\\n header_dict[\\\"wavelength\\\"] = header_dict[\\\"wavelength\\\"].replace(\\\"}\\\", \\\"\\\")\\n header_dict[\\\"wavelength\\\"] = header_dict[\\\"wavelength\\\"].replace(\\\" \\\", \\\"\\\")\\n header_dict[\\\"wavelength\\\"] = header_dict[\\\"wavelength\\\"].split(\\\",\\\")\\n\\n # Create dictionary of wavelengths\\n wavelength_dict = {}\\n for j, wavelength in enumerate(header_dict[\\\"wavelength\\\"]):\\n wavelength_dict.update({float(wavelength): float(j)})\\n\\n # Replace datatype ID number with the numpy datatype\\n dtype_dict = {\\\"1\\\": np.uint8, \\\"2\\\": np.int16, \\\"3\\\": np.int32, \\\"4\\\": np.float32, \\\"5\\\": np.float64, \\\"6\\\": np.complex64,\\n \\\"9\\\": np.complex128, \\\"12\\\": np.uint16, \\\"13\\\": np.uint32, \\\"14\\\": np.uint64, \\\"15\\\": np.uint64}\\n header_dict[\\\"data type\\\"] = dtype_dict[header_dict[\\\"data type\\\"]]\\n\\n # Read in the data from the file\\n raw_data = np.fromfile(filename, header_dict[\\\"data type\\\"], -1)\\n\\n # Reshape the raw data into a datacube array\\n array_data = raw_data.reshape(int(header_dict[\\\"lines\\\"]),\\n int(header_dict[\\\"bands\\\"]),\\n int(header_dict[\\\"samples\\\"])).transpose((0, 2, 1))\\n\\n if \\\"default bands\\\" in header_dict:\\n header_dict[\\\"default bands\\\"] = header_dict[\\\"default bands\\\"].replace(\\\"{\\\", \\\"\\\")\\n header_dict[\\\"default bands\\\"] = header_dict[\\\"default bands\\\"].replace(\\\"}\\\", \\\"\\\")\\n default_bands = header_dict[\\\"default bands\\\"].split(\\\",\\\")\\n\\n pseudo_rgb = cv2.merge((array_data[:, :, int(default_bands[0])],\\n array_data[:, :, int(default_bands[1])],\\n array_data[:, :, int(default_bands[2])]))\\n\\n else:\\n max_wavelength = max([float(i) for i in wavelength_dict.keys()])\\n min_wavelength = min([float(i) for i in wavelength_dict.keys()])\\n # Check range of available wavelength\\n if max_wavelength >= 635 and min_wavelength <= 490:\\n id_red = _find_closest(np.array([float(i) for i in wavelength_dict.keys()]), 710)\\n id_green = _find_closest(np.array([float(i) for i in wavelength_dict.keys()]), 540)\\n id_blue = _find_closest(np.array([float(i) for i in wavelength_dict.keys()]), 480)\\n\\n pseudo_rgb = cv2.merge((array_data[:, :, [id_blue]],\\n array_data[:, :, [id_green]],\\n array_data[:, :, [id_red]]))\\n else:\\n # Otherwise take 3 wavelengths, first, middle and last available wavelength\\n id_red = int(header_dict[\\\"bands\\\"]) - 1\\n id_green = int(id_red / 2)\\n pseudo_rgb = cv2.merge((array_data[:, :, [0]],\\n array_data[:, :, [id_green]],\\n array_data[:, :, [id_red]]))\\n\\n # Gamma correct pseudo_rgb image\\n pseudo_rgb = pseudo_rgb ** (1 / 2.2)\\n # Scale each of the channels up to 255\\n pseudo_rgb = cv2.merge((rescale(pseudo_rgb[:, :, 0]),\\n rescale(pseudo_rgb[:, :, 1]),\\n rescale(pseudo_rgb[:, :, 2])))\\n\\n max_wl = float(str(header_dict[\\\"wavelength\\\"][-1]).rstrip())\\n min_wl = float(str(header_dict[\\\"wavelength\\\"][0]).rstrip())\\n\\n # Create an instance of the spectral_data class\\n spectral_array = Spectral_data(array_data=array_data, max_wavelength=max_wl,\\n min_wavelength=min_wl, d_type=header_dict[\\\"data type\\\"],\\n wavelength_dict=wavelength_dict, samples=int(header_dict[\\\"samples\\\"]),\\n lines=int(header_dict[\\\"lines\\\"]), interleave=header_dict[\\\"interleave\\\"],\\n wavelength_units=header_dict[\\\"wavelength units\\\"], array_type=\\\"datacube\\\",\\n pseudo_rgb=pseudo_rgb, filename=filename)\\n\\n # Reset debug mode\\n params.debug = debug\\n\\n if params.debug == \\\"plot\\\":\\n # Gamma correct pseudo_rgb image\\n plot_image(pseudo_rgb)\\n elif params.debug == \\\"print\\\":\\n print_image(pseudo_rgb, os.path.join(params.debug_outdir, str(params.device) + \\\"_pseudo_rgb.png\\\"))\\n\\n return spectral_array\",\n \"def __init__(self,\\n resp_data,\\n ):\\n self.raw_data = resp_data.dict()\\n\\n # Packet parsed for host db processing\\n self.parsed_data = {'insert': {'product': self.get_product_pack(),\\n 'selling_status': self.get_selling_status_pack(),\\n 'shipping_info': self.get_shipping_info_pack(),\\n 'listing_info': self.get_listing_info_pack(),\\n },\\n 'items_received': resp_data.dict()['searchResult']['_count']}\",\n \"def processLnkHeader(self):\\n\\t\\t# Read LNK heaer from file\\n\\t\\theader_raw = self.fpLnk.read(HEADER_LEN)\\n\\t\\t# Build new dictionary containing header data\\n\\t\\tself.header = parseStructuredData(header_raw, LNK_HEADER)\",\n \"def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\\n assert isinstance(header, CmdHeader)\\n assert isinstance(raw_data, (bytes, bytearray))\\n self.header = header\\n self.raw_data = raw_data\\n self.status, = unpack_from(\\\"<L\\\", raw_data)\",\n \"def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\\n super().__init__(header, raw_data)\\n self.status, self.length = unpack_from('<2I', raw_data)\",\n \"def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\\n super().__init__(header, raw_data)\\n self.status, self.length = unpack_from('<2I', raw_data)\",\n \"def __init__(self, header: CmdHeader, raw_data: bytes) -> None:\\n super().__init__(header, raw_data)\\n self.status, self.length = unpack_from('<2I', raw_data)\",\n \"def load(self):\\n basepath = os.path.dirname(os.path.abspath(__file__))\\n filename = os.sep.join([basepath, c.FOLDER_JSON, c.FILE_GAME_VERSIONS])\\n Handler.ALL_VERS_DATA = {} # reset known data; do not retain defunct information\\n with open(filename, \\\"r\\\") as f:\\n data = json.loads( f.read() )\\n self.update(data)\\n self._updated = False\\n #for v,record in iteritems(Handler.ALL_VERS_DATA):\\n # print(type(v), v)\\n #for k,v in iteritems(record): \",\n \"def _read_headers(self):\\n # Read the textual header.\\n self._read_textual_header()\\n # The next 400 bytes are from the Binary File Header.\\n binary_file_header = self.file.read(400)\\n bfh = SEGYBinaryFileHeader(binary_file_header, self.endian)\\n self.binary_file_header = bfh\\n self.data_encoding = self.binary_file_header.data_sample_format_code\\n # If bytes 3506-3506 are not zero, an extended textual header follows\\n # which is not supported so far.\\n if bfh.number_of_3200_byte_ext_file_header_records_following != 0:\\n msg = 'Extended textual headers are supported yet. ' + \\\\\\n 'Please contact the developers.'\\n raise NotImplementedError(msg)\",\n \"def _build_header_dictionary(self):\\n start = 0\\n #print self.raw_data\\n for a in range(20):\\n redatapuller = re.compile(\\\"\\\\r\\\\n\\\\r\\\\n\\\\r\\\\n(?P<word>.*?)\\\\t.*?\\\\n\\\", re.DOTALL)\\n m = redatapuller.search(self.raw_data[start:])\\n if not(m):\\n break\\n self.header_dictionary[m.group(\\\"word\\\")] = start + m.end()\\n if a==0:\\n self.header_dictionary[\\\"main\\\"] = start + m.end()\\n start += m.end()\",\n \"def parse(data):\\n try:\\n header = decompress(data)\\n version, game, save, log = parse_version(header, data)\\n if version not in (Version.USERPATCH15, Version.DE, Version.HD):\\n raise RuntimeError(f\\\"{version} not supported\\\")\\n de = parse_de(header, version, save)\\n hd = parse_hd(header, version, save)\\n metadata, num_players = parse_metadata(header)\\n map_ = parse_map(header, version)\\n players, mod, device = parse_players(header, num_players, version, save)\\n scenario = parse_scenario(header, num_players, version, save)\\n lobby = parse_lobby(header, version, save)\\n except (struct.error, zlib.error, AssertionError, MemoryError, ValueError) as e:\\n raise RuntimeError(f\\\"could not parse: {e}\\\")\\n return dict(\\n version=version,\\n game_version=game,\\n save_version=save,\\n log_version=log,\\n players=players,\\n map=map_,\\n de=de,\\n hd=hd,\\n mod=de.get('dlc_ids') if de else mod,\\n metadata=metadata,\\n scenario=scenario,\\n lobby=lobby,\\n device=device\\n )\",\n \"def on_frame(self, frame: str) -> None:\\n\\n logger.debug(\\\"Frame: {}\\\".format(frame))\\n try:\\n message = json.loads(frame)\\n except:\\n logger.exception(\\\"Could not decode the JSON message\\\")\\n self.transport.close()\\n return\\n\\n mtype = message.get('type', None)\\n self.log_state(mtype)\\n if mtype == 'NEGOTIATION_RESPONSE':\\n logger.debug(\\\"NEGOTIATION RESPONSE\\\")\\n\\n # Receive the chosen algorithms by the server \\n self.process_negotiation_response(message)\\n\\n # Generate DH client private and public keys\\n bytes_public_key,p,g,y=self.crypto.dh_client()\\n \\n message = {'type':'DH_PARAMETERS','parameters':{'p':p,'g':g,'public_key':str(bytes_public_key,'ISO-8859-1')}}\\n self._send(message)\\n self.state = STATE_DH\\n \\n return\\n\\n elif mtype == 'DH_PARAMETERS_RESPONSE':\\n logger.debug('DH_PARAMETERS_RESPONSE')\\n public_key=bytes(message['parameters']['public_key'],'ISO-8859-1')\\n \\n #Create shared key with the server public key\\n self.crypto.create_shared_key(public_key)\\n \\n # Generate a symmetric key\\n self.crypto.symmetric_key_gen()\\n logger.debug(\\\"Key: {}\\\".format(self.crypto.symmetric_key))\\n\\n if self.state == STATE_ROTATION:\\n self.state = STATE_OPEN\\n self.send_file(self.file_name)\\n \\n elif self.state == STATE_DH:\\n secure_message = self.encrypt_message({'type': 'OPEN', 'file_name': self.file_name})\\n self._send(secure_message)\\n self.send_mac()\\n self.state = STATE_OPEN\\n\\n return\\n\\n elif mtype == 'INTEGRITY_CONTROL':\\n flag = message['data']\\n if flag == 'True':\\n self._send(self.encrypt_message({'type': 'CLOSE'}))\\n self.send_mac()\\n logger.info(\\\"File transfer finished. Closing transport\\\")\\n self.transport.close()\\n\\n elif mtype == 'OK': # Server replied OK. We can advance the state\\n if self.state == STATE_OPEN:\\n logger.info(\\\"Channel open\\\")\\n self.send_file(self.file_name)\\n elif self.state == STATE_DATA: # Got an OK during a message transfer.\\n # Reserved for future use\\n pass\\n else:\\n logger.warning(\\\"Ignoring message from server\\\")\\n return\\n\\n elif mtype == 'ERROR':\\n logger.warning(\\\"Got error from server: {}\\\".format(message.get('data', None)))\\n \\n else:\\n logger.warning(\\\"Invalid message type\\\")\\n\\n logger.debug('Closing')\\n self.transport.close()\\n self.loop.stop()\",\n \"def to_data(self) -> dict:\\n return {'pingData': {'challenge': self.ping_challenge}}\",\n \"def load_id_dict(self) -> None:\\n sys.stdout.write(\\\"Loading identifier dictionaries...\\\\n\\\")\\n assert os.path.exists(self.mapping_file)\\n with open(self.mapping_file, 'r') as f:\\n self.forward_map, self.backward_map = json.load(f)\\n self.forward_map = {int(k): v for k, v in self.forward_map.items()}\",\n \"def __init__(self, header=None):\\r\\n\\r\\n self.data = []\",\n \"def _initialize_data(self):\\n self.reset_count = 0\\n self._idn_no_firmware = \\\"KEPCO,BOP 50-20,E1234,\\\"\\n self._firmware = 2.6\\n self._init_data()\",\n \"def _init_data(self) -> None:\\n self.dtype = dict()\\n self.shape = dict()\\n self.size = dict()\\n self.attrs = dict()\\n self.data_ptr = dict()\\n\\n if self.mode == 'r':\\n for k in self.fp.keys():\\n self.dtype[k] = self.fp[k].dtype\\n self.shape[k] = self.fp[k].shape\\n self.size[k] = self.fp[k].shape[0]\\n self.data_ptr[k] = 0\",\n \"def _read_chunk_head(self, data):\\n if ';' in data:\\n data, ext = data.split(';', 1)\\n else:\\n ext = ''\\n\\n length = int(data.strip(), 16)\\n\\n if length == 0:\\n resp = self.current_response\\n if resp._decompressor:\\n resp.body += resp._decompressor.flush()\\n del resp._decompressor\\n\\n self._stream.on_read = self._read_additional_headers\\n resp._additional_headers = ''\\n self._stream.read_delimiter = CRLF\\n\\n else:\\n self._stream.on_read = self._read_chunk_body\\n self._stream.read_delimiter = length + 2\",\n \"def _load(self):\\n # Extract the ASCII header (5 first lines)\\n with open(self._xst_bin, 'rb') as f:\\n header = list(islice(f, 0, 5))\\n assert header[0] == b'HeaderStart\\\\n',\\\\\\n 'Wrong header start'\\n assert header[-1] == b'HeaderStop\\\\n',\\\\\\n 'Wrong header stop'\\n header = [s.decode('utf-8') for s in header]\\n hd_size = sum([len(s) for s in header])\\n\\n # Parse informations into a metadata dictionnary\\n keys = ['freq', 'ma', 'accu']\\n search = ['Freq.List', 'Mr.List', 'accumulation']\\n types = ['float64', 'int', 'int']\\n for key, word, typ in zip(keys, search, types):\\n for h in header:\\n if word in h:\\n self.meta[key] = np.array(\\n h.split('=')[1].split(','),\\n dtype=typ\\n )\\n\\n # Deduce the dtype for decoding\\n n_ma = self.meta['ma'].size\\n n_sb = self.meta['freq'].size\\n dtype = np.dtype(\\n [('jd', 'float64'),\\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\\n )\\n\\n # Decoding the binary file\\n tmp = np.memmap(\\n filename=self._xst_bin,\\n dtype='int8',\\n mode='r',\\n offset=hd_size\\n )\\n decoded = tmp.view(dtype)\\n\\n self.data = decoded['data'] / self.meta['accu']\\n self.time = Time(decoded['jd'], format='jd', precision=0)\\n\\n return\",\n \"def _decode(self):\\n \\n self.version = int(data_to_hex_str(self.packet[0])[2])\\n self.header_len = int(data_to_hex_str(self.packet[0])[3]) * 4\\n self.type_of_service = data_to_hex_str(self.packet[1:2])\\n self.total_len = int(data_to_hex_str(self.packet[2:4]), 16)\\n self.id = data_to_hex_str(self.packet[4:6])\\n \\n #parse the flags fields(reservedbit, don't fragment, more fragment)\\n if ((ord(self.packet[6]) & (1 << 7)) != 0):\\n self.flags_reservedbit = 1\\n else:\\n self.flags_reservedbit = 0\\n #endof if\\n \\n if ((ord(self.packet[6]) & (1 << 6)) != 0):\\n self.flags_dont_fragment = 1\\n else:\\n self.flags_dont_fragment = 0\\n #endof if\\n \\n if ((ord(self.packet[6]) & (1 << 5)) != 0):\\n self.flags_more_fragment = 1\\n else:\\n self.flags_more_fragment = 0\\n #endof if\\n \\n #parse the offset field(in packet[6:7]): 00011111 & packet[6] (to filter flags) -->> get packet[6:7] in hex_str\\n #tmp = str(31 & ord(self.packet[6]))\\n self.fragment_offset = int(data_to_hex_str(self.packet[6:8]), 16)\\n if (self.fragment_offset >= (1 << 13)):\\n #take away the flags fields: 00011111 11111111 & self.fragment_offset\\n self.fragment_offset = self.fragment_offset & ((1 << 13) - 1) \\n \\n self.TTL = ord(self.packet[8])\\n self.protocol = IPPROTO[ord(self.packet[9])]\\n self.header_checksum = data_to_hex_str(self.packet[10:12])\\n \\n self.src = str(ord(self.packet[12])) + '.' + str(ord(self.packet[13])) + '.' + \\\\\\n str(ord(self.packet[14])) + '.' + str(ord(self.packet[15]))\\n self.dst = str(ord(self.packet[16])) + '.' + str(ord(self.packet[17])) + '.' + \\\\\\n str(ord(self.packet[18])) + '.' + str(ord(self.packet[19]))\\n \\n if (self.header_len > 20):\\n self.opt_paddings = self.packet[20 : (self.header_len)]\",\n \"def act_on_header(self, dct):\\n self.socket.send_pyobj(dict(dct), protocol=2)\",\n \"def deserialize(self, reader: serialization.BinaryReader) -> None:\\n self.index_start = reader.read_uint32()\\n self.count = reader.read_int16()\\n if self.count < 1 or self.count == 0 or self.count > HeadersPayload.MAX_HEADERS_COUNT:\\n raise ValueError(\\\"Deserialization error - invalid count\\\")\",\n \"def _parseHeader(self):\\n # Big or little endian for the header.\\n self._getEndianess()\\n # Read the fixed header.\\n self._readFixedHeader()\\n # Get the present blockettes.\\n self._getBlockettes()\\n # Calculate the starttime.\\n self._calculateStarttime()\",\n \"def _decode1(self, body, data):\\r\\n if \\\" \\\" in body:\\r\\n evtype,body = body.split(\\\" \\\",1)\\r\\n else:\\r\\n evtype,body = body,\\\"\\\"\\r\\n evtype = evtype.upper()\\r\\n if evtype == \\\"CIRC\\\":\\r\\n m = re.match(r\\\"(\\\\d+)\\\\s+(\\\\S+)(\\\\s\\\\S+)?(\\\\s\\\\S+)?(\\\\s\\\\S+)?(\\\\s\\\\S+)?\\\", body)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"CIRC event misformatted.\\\")\\r\\n ident,status,path,purpose,reason,remote = m.groups()\\r\\n ident = int(ident)\\r\\n if path:\\r\\n if \\\"PURPOSE=\\\" in path:\\r\\n remote = reason\\r\\n reason = purpose\\r\\n purpose=path\\r\\n path=[]\\r\\n elif \\\"REASON=\\\" in path:\\r\\n remote = reason\\r\\n reason = path\\r\\n purpose = \\\"\\\"\\r\\n path=[]\\r\\n else:\\r\\n path_verb = path.strip().split(\\\",\\\")\\r\\n path = []\\r\\n for p in path_verb:\\r\\n path.append(p.replace(\\\"~\\\", \\\"=\\\").split(\\\"=\\\")[0])\\r\\n else:\\r\\n path = []\\r\\n\\r\\n if purpose and \\\"REASON=\\\" in purpose:\\r\\n remote=reason\\r\\n reason=purpose\\r\\n purpose=\\\"\\\"\\r\\n\\r\\n if purpose: purpose = purpose[9:]\\r\\n if reason: reason = reason[8:]\\r\\n if remote: remote = remote[15:]\\r\\n event = CircuitEvent(evtype, ident, status, path, purpose, reason,\\r\\n remote, body)\\r\\n elif evtype == \\\"STREAM\\\":\\r\\n #plog(\\\"DEBUG\\\", \\\"STREAM: \\\"+body)\\r\\n m = re.match(r\\\"(\\\\S+)\\\\s+(\\\\S+)\\\\s+(\\\\S+)\\\\s+(\\\\S+)?:(\\\\d+)(\\\\sREASON=\\\\S+)?(\\\\sREMOTE_REASON=\\\\S+)?(\\\\sSOURCE=\\\\S+)?(\\\\sSOURCE_ADDR=\\\\S+)?(\\\\s+PURPOSE=\\\\S+)?\\\", body)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"STREAM event misformatted.\\\")\\r\\n ident,status,circ,target_host,target_port,reason,remote,source,source_addr,purpose = m.groups()\\r\\n ident,circ = map(int, (ident,circ))\\r\\n if not target_host: # This can happen on SOCKS_PROTOCOL failures\\r\\n target_host = \\\"(none)\\\"\\r\\n if reason: reason = reason[8:]\\r\\n if remote: remote = remote[15:]\\r\\n if source: source = source[8:]\\r\\n if source_addr: source_addr = source_addr[13:]\\r\\n if purpose:\\r\\n purpose = purpose.lstrip()\\r\\n purpose = purpose[8:]\\r\\n event = StreamEvent(evtype, ident, status, circ, target_host,\\r\\n int(target_port), reason, remote, source, source_addr,\\r\\n purpose, body)\\r\\n elif evtype == \\\"ORCONN\\\":\\r\\n m = re.match(r\\\"(\\\\S+)\\\\s+(\\\\S+)(\\\\sAGE=\\\\S+)?(\\\\sREAD=\\\\S+)?(\\\\sWRITTEN=\\\\S+)?(\\\\sREASON=\\\\S+)?(\\\\sNCIRCS=\\\\S+)?\\\", body)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"ORCONN event misformatted.\\\")\\r\\n target, status, age, read, wrote, reason, ncircs = m.groups()\\r\\n\\r\\n #plog(\\\"DEBUG\\\", \\\"ORCONN: \\\"+body)\\r\\n if ncircs: ncircs = int(ncircs[8:])\\r\\n else: ncircs = 0\\r\\n if reason: reason = reason[8:]\\r\\n if age: age = int(age[5:])\\r\\n else: age = 0\\r\\n if read: read = int(read[6:])\\r\\n else: read = 0\\r\\n if wrote: wrote = int(wrote[9:])\\r\\n else: wrote = 0\\r\\n event = ORConnEvent(evtype, status, target, age, read, wrote,\\r\\n reason, ncircs, body)\\r\\n elif evtype == \\\"STREAM_BW\\\":\\r\\n m = re.match(r\\\"(\\\\d+)\\\\s+(\\\\d+)\\\\s+(\\\\d+)\\\", body)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"STREAM_BW event misformatted.\\\")\\r\\n event = StreamBwEvent(evtype, body, *m.groups())\\r\\n elif evtype == \\\"BW\\\":\\r\\n m = re.match(r\\\"(\\\\d+)\\\\s+(\\\\d+)\\\", body)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"BANDWIDTH event misformatted.\\\")\\r\\n read, written = map(long, m.groups())\\r\\n event = BWEvent(evtype, read, written, body)\\r\\n elif evtype in (\\\"DEBUG\\\", \\\"INFO\\\", \\\"NOTICE\\\", \\\"WARN\\\", \\\"ERR\\\"):\\r\\n event = LogEvent(evtype, body)\\r\\n elif evtype == \\\"NEWDESC\\\":\\r\\n ids_verb = body.split(\\\" \\\")\\r\\n ids = []\\r\\n for i in ids_verb:\\r\\n ids.append(i.replace(\\\"~\\\", \\\"=\\\").split(\\\"=\\\")[0].replace(\\\"$\\\",\\\"\\\"))\\r\\n event = NewDescEvent(evtype, ids, body)\\r\\n elif evtype == \\\"ADDRMAP\\\":\\r\\n # TODO: Also parse errors and GMTExpiry\\r\\n m = re.match(r'(\\\\S+)\\\\s+(\\\\S+)\\\\s+(\\\\\\\"[^\\\"]+\\\\\\\"|\\\\w+)', body)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"ADDRMAP event misformatted.\\\")\\r\\n fromaddr, toaddr, when = m.groups()\\r\\n if when.upper() == \\\"NEVER\\\": \\r\\n when = None\\r\\n else:\\r\\n when = time.strptime(when[1:-1], \\\"%Y-%m-%d %H:%M:%S\\\")\\r\\n event = AddrMapEvent(evtype, fromaddr, toaddr, when, body)\\r\\n elif evtype == \\\"NS\\\":\\r\\n event = NetworkStatusEvent(evtype, parse_ns_body(data), data)\\r\\n elif evtype == \\\"NEWCONSENSUS\\\":\\r\\n event = NewConsensusEvent(evtype, parse_ns_body(data), data)\\r\\n elif evtype == \\\"BUILDTIMEOUT_SET\\\":\\r\\n m = re.match(\\r\\n r\\\"(\\\\S+)\\\\sTOTAL_TIMES=(\\\\d+)\\\\sTIMEOUT_MS=(\\\\d+)\\\\sXM=(\\\\d+)\\\\sALPHA=(\\\\S+)\\\\sCUTOFF_QUANTILE=(\\\\S+)\\\",\\r\\n body)\\r\\n set_type, total_times, timeout_ms, xm, alpha, quantile = m.groups()\\r\\n event = BuildTimeoutSetEvent(evtype, set_type, int(total_times),\\r\\n int(timeout_ms), int(xm), float(alpha),\\r\\n float(quantile), body)\\r\\n elif evtype == \\\"GUARD\\\":\\r\\n m = re.match(r\\\"(\\\\S+)\\\\s(\\\\S+)\\\\s(\\\\S+)\\\", body)\\r\\n entry, guard, status = m.groups()\\r\\n event = GuardEvent(evtype, entry, guard, status, body)\\r\\n elif evtype == \\\"TORCTL_TIMER\\\":\\r\\n event = TimerEvent(evtype, data)\\r\\n else:\\r\\n event = UnknownEvent(evtype, body)\\r\\n\\r\\n return event\",\n \"def prepare_data(self):\\n self.empty = 'yes' if len(self.data) == 0 else 'no'\\n self._keys = sorted(key for key in self.data.keys())\\n\\n # Validate the keys\\n for key in self._keys:\\n if not is_valid_matlab_field_label(key):\\n msg = \\\"'{}' is not a valid MATLAB field label\\\".format(key)\\n raise ValueError(msg)\\n self.field_names = \\\" \\\".join(self._keys)\",\n \"def __read_json(self):\\n try:\\n with open(self.X_path) as Xfile, open(self.Y_path) as Yfile:\\n print('Starting to read the json files')\\n t1 = time.perf_counter()\\n Ydata = [obj[0] for obj in json.load(Yfile)]\\n Xdata = json.load(Xfile)\\n # Note: some samples (31) are empty\\n # Xdata = [obj for obj in json.load(Xfile) if len(obj)>1]\\n for record in Xdata:\\n del record['sha256'] # Remove signature from features\\n t2 = time.perf_counter()\\n print(f'Finished reading the json files. '\\n f'Elapsed time: {(t2 - t1) / 60.0} minutes')\\n except Exception as e:\\n print(f'Exception while reading json files ({e})')\\n raise e\\n\\n self.Y = np.array(Ydata, dtype=np.uint8)\\n print('Y.shape', self.Y.shape)\\n self.vectorizer = DictVectorizer(sparse=True, dtype=np.uint8)\\n self.X = self.vectorizer.fit_transform(Xdata)\\n print('X.shape (All):', self.X.shape)\\n # If feature selection is applied\\n if self.n_features != -1:\\n support = SelectKBest(chi2, k=self.n_features).fit(self.X, self.Y)\\n self.vectorizer.restrict(support.get_support())\\n self.X = support.transform(self.X)\\n print('X.shape (Reduced):', self.X.shape)\\n\\n self.feature_names = self.vectorizer.feature_names_\\n malware_idx = np.where(self.Y == 1)[0]\\n self.X_malware = self.X[malware_idx, :]\\n goodware_idx = np.where(self.Y == 0)[0]\\n self.X_goodware = self.X[goodware_idx, :]\\n\\n\\n try:\\n with shelve.open(self.shelf_path, 'c') as shelf:\\n print('Saving data to a shelf')\\n shelf['X'] = self.X\\n shelf['X_malware'] = self.X_malware\\n shelf['X_goodware'] = self.X_goodware\\n shelf['Y'] = self.Y\\n shelf['feature_names'] = self.feature_names\\n print('Finished saving the shelf')\\n except Exception as e:\\n print(f'Exception while saving data to a shelf ({e})')\",\n \"def __init__(self, data: dict):\\n super().__init__(data)\\n self._supports_validation = False\\n self._ping_data_raw = data['pingData']\",\n \"def _decode_5104(data):\\n\\n text = []\\n start_byte = 0\\n while start_byte + 2 < len(data):\\n tag = data[start_byte:start_byte + 2]\\n if tag == b'#u':\\n start_byte += 2\\n text_size = struct.unpack(\\n '<h', data[start_byte:start_byte + 2])[0]\\n start_byte += 2\\n text.append(data[start_byte:start_byte + text_size].decode('utf8'))\\n start_byte += text_size\\n start_byte += 6\\n elif tag == b'$u':\\n start_byte += 2\\n text.append(struct.unpack(\\n '<h', data[start_byte:start_byte + 2])[0])\\n start_byte += 2\\n start_byte += 6\\n elif tag == b',u':\\n start_byte += 2\\n text.append(struct.unpack(\\n '<h', data[start_byte:start_byte + 2])[0])\\n start_byte += 2\\n else:\\n start_byte += 1\\n\\n return {'analyst': text[0],\\n 'date': text[2],\\n 'image_name': text[4],\\n 'instrument_model': text[5],\\n 'instrument_serial_number': text[6],\\n 'instrument_software_version': text[7],\\n 'accumulations': text[9],\\n 'detector': text[11],\\n 'source': text[12],\\n 'beam_splitter': text[13],\\n 'apodization': text[15],\\n 'spectrum_type': text[16],\\n 'beam_type': text[17],\\n 'phase_correction': text[20],\\n 'ir_accessory': text[26],\\n 'igram_type': text[28],\\n 'scan_direction': text[29],\\n 'background_scans': text[32]}\",\n \"def get_json(self):\\n data = {}\\n data['ip'] = self.ip\\n\\n try:\\n data['country'] = self.processedvtdata[\\\"country\\\"]\\n except KeyError:\\n data['country'] = 'None'\\n try:\\n data['as'] = self.processedvtdata[\\\"as_owner\\\"]\\n except KeyError:\\n data['as'] = 'None'\\n try:\\n data['rdns'] = self.processedvtdata[\\\"self.reversedns\\\"]\\n except KeyError:\\n data['rdns'] = 'None'\\n try:\\n data['label'] = self.expertlabel\\n except AttributeError:\\n data['label'] = ''\\n\\n # geodata\\n #{\\\"status\\\":\\\"success\\\",\\\"country\\\":\\\"Yemen\\\",\\\"countryCode\\\":\\\"YE\\\",\\\"region\\\":\\\"SA\\\",\\\"regionName\\\":\\\"Amanat Alasimah\\\",\\\"city\\\":\\\"Sanaa\\\",\\\"zip\\\":\\\"\\\",\\\"lat\\\":15.3522,\\\"lon\\\":44.2095,\\\"timezone\\\":\\\"Asia/Aden\\\",\\\"isp\\\":\\\"Public Telecommunication Corporation\\\",\\\"org\\\":\\\"YemenNet\\\",\\\"as\\\":\\\"AS30873 Public Telecommunication Corporation\\\",\\\"query\\\":\\\"134.35.218.63\\\"}\\n if self.geodata:\\n data['geodata'] = self.geodata\\n \\n # vt resolutions. Is a list\\n data['vt'] = {}\\n try:\\n if self.processedvtdata['resolutions'] != 'None':\\n data['vt']['resolutions'] = []\\n for count, resolution_tuple in enumerate(self.processedvtdata['resolutions']):\\n if count >= self.amount_to_print:\\n break\\n temp = {}\\n temp['date'] = resolution_tuple[0]\\n temp['domain'] = resolution_tuple[1]\\n data['vt']['resolutions'].append(temp)\\n except KeyError:\\n pass\\n\\n # vt urls. Is a list\\n try:\\n if self.processedvtdata['detected_urls'] != 'None':\\n data['vt']['detected_urls'] = []\\n for count, url_tuple in enumerate(self.processedvtdata['detected_urls']):\\n if count >= self.amount_to_print:\\n break\\n temp = {}\\n temp['date'] = url_tuple[0]\\n temp['url'] = url_tuple[1][0]\\n temp['detections'] = str(url_tuple[1][1]) + '/' + str(url_tuple[1][2])\\n data['vt']['detected_urls'].append(temp)\\n except KeyError:\\n pass\\n\\n\\n # vt detected communicating samples. Is a list\\n try:\\n if self.processedvtdata['detected_communicating_samples'] != 'None':\\n data['vt']['detected_communicating_samples'] = []\\n for count, communcating_tuple in enumerate(self.processedvtdata['detected_communicating_samples']):\\n if count >= self.amount_to_print:\\n break\\n temp = {}\\n temp['date'] = communcating_tuple[0]\\n temp['detections'] = str(communcating_tuple[1][0]) + '/' + str(communcating_tuple[1][1])\\n temp['sha256'] = communcating_tuple[1][2]\\n data['vt']['detected_communicating_samples'].append(temp)\\n except AttributeError:\\n pass\\n\\n # vt detected downloaded samples. Is a list\\n try:\\n if self.processedvtdata['detected_downloaded_samples'] != 'None':\\n data['vt']['detected_downloaded_samples'] = []\\n for count, detected_tuple in enumerate(self.processedvtdata['detected_downloaded_samples']):\\n if count >= self.amount_to_print:\\n break\\n temp = {}\\n temp['date'] = detected_tuple[0]\\n temp['detections'] = str(detected_tuple[1][0]) + '/' + str(detected_tuple[1][1])\\n temp['sha256'] = detected_tuple[1][2]\\n data['vt']['detected_downloaded_samples'].append(temp)\\n except AttributeError:\\n pass\\n\\n # vt referrer downloaded samples. Is a list\\n try:\\n if self.processedvtdata['detected_referrer_samples'] != 'None':\\n data['vt']['detected_referrer_samples'] = []\\n for count, referrer_tuple in enumerate(self.processedvtdata['detected_referrer_samples']):\\n if count >= self.amount_to_print:\\n break\\n temp = {}\\n temp['sha256'] = referrer_tuple[0]\\n temp['detections'] = str(referrer_tuple[1][0]) + '/' + str(referrer_tuple[1][1])\\n data['vt']['detected_referrer_samples'].append(temp)\\n except AttributeError:\\n pass\\n\\n # pt data\\n data['pt'] = {}\\n if self.processedptdata:\\n count = 0\\n data['pt']['passive_dns'] = []\\n for result in self.processedptdata_results:\\n if count >= self.amount_to_print:\\n break\\n temp = {}\\n temp['lastseen'] = result[0]\\n temp['firstseen'] = result[1][0]\\n temp['hostname'] = result[1][1]\\n data['pt']['passive_dns'].append(temp)\\n count += 1\\n\\n # shodan data\\n try:\\n if self.shodandata:\\n data['shodan'] = self.shodandata\\n except AttributeError:\\n pass\\n\\n data = json.dumps(data)\\n return data\",\n \"def load_data(self) -> None:\",\n \"def __init__(self):\\n self.data = []\\n self.record = {}\",\n \"def _readHeader(self):\\n self.ControllerVersion = self._readInt(0)\\n self.LogicOutput = self._readInt(2)\\n self.AppHiCapLowNoise = self._readInt(4)\\n self.TimingMode = self._readInt(8)\\n self.Exposure = self._readFloat(10)\\n self.DetTemperature = self._readFloat(36)\\n self.DetectorType = self._readInt(40)\\n self.TriggerDiode = self._readInt(44)\\n self.DelayTime = self._readFloat(46)\\n self.ShutterControl = self._readInt(50)\\n self.AbsorbLive = self._readInt(52)\\n self.AbsorbMode = self._readInt(54)\\n self.CanDoVirtualChip = self._readInt(56)\\n self.ThresholdMinLive = self._readInt(58)\\n self.ThresholdMin = self._readFloat(60)\\n self.ThresholdMaxLive = self._readInt(64)\\n self.ThresholdMax = self._readFloat(66)\\n self.ADCOffset = self._readInt(188)\\n self.ADCRate = self._readInt(190)\\n self.ADCType = self._readInt(192)\\n self.ADCRes = self._readInt(194)\\n self.ADCBitAdj = self._readInt(196)\\n self.Gain = self._readInt(198)\\n self.GeometricOps = self._readInt(600)\",\n \"def startProtocol(self):\\n #init state trackers\\n self.initialMessageSentToServer = False\\n self.sentPacketToPeerPublicAndPrivateAddresses = False\\n self.mirroredBackWhicheverPacketMadeIt = False\\n self.peerConnectionEstablished = False\\n #init peer info\\n self.peerPublicAddress = None\\n self.peerPrivateAddress = None\\n self.peerAddress = None \\n self.peerUserName = None\\n\\n #talk to handshake server\\n if iAmServer:\\n data = {\\n 'registering-server': True,\\n 'user-name': userName,\\n 'private-ip': myPrivateIp, \\n 'private-port': myPrivatePort\\n }\\n else:\\n data = {\\n 'registering-server': False,\\n 'user-name': userName,\\n 'private-ip': myPrivateIp, \\n 'private-port': myPrivatePort,\\n 'server-name' : serverName,\\n 'server-password': serverPassword,\\n }\\n self.transport.write(json.dumps(data).encode(), (HANDSHAKE_SERVER_IP, HANDSHAKE_SERVER_PORT))\\n print(\\\"sent initial message to server \\\" + HANDSHAKE_SERVER_IP + \\\":\\\" + str(HANDSHAKE_SERVER_PORT))\\n self.initialMessageSentToServer = True\",\n \"def _decode(self, input_dict):\\n pass\",\n \"def _read_header_line_2(lines: list) -> dict:\\n fields = (\\n \\\"detection_status\\\",\\n \\\"warning\\\",\\n \\\"cloud_base_data\\\",\\n \\\"warning_flags\\\",\\n )\\n values = [[line[0], line[1], line[3:20], line[21:].strip()] for line in lines]\\n return values_to_dict(fields, values)\",\n \"def __init__(self, fileName):\\n self.recordDict = {}\\n for line in open(fileName, 'r') :\\n sipRecord = json.loads(line)\\n self.recordDict[sipRecord['addressOfRecord']] = line\",\n \"def __process_ethframe(self, eth_header: bytes) -> Dict[str, Any]:\\n eth = struct.unpack('!6s6sH', eth_header)\\n eth_protocol = socket.ntohs(eth[2])\\n\\n return {\\n 'header_length': Sniffer.ETH_HEADER_LENGTH,\\n 'protocol': eth_protocol,\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5554169","0.5521527","0.53812873","0.5335025","0.5277362","0.5266372","0.5250536","0.52459896","0.5201471","0.5174532","0.5169621","0.5158002","0.5134929","0.5060775","0.5059112","0.5053946","0.50465447","0.50403374","0.50372404","0.50230026","0.5013707","0.49840298","0.49820694","0.4975421","0.4965126","0.4963513","0.49616337","0.49530494","0.49451962","0.49432674","0.49310958","0.49284548","0.492647","0.49049306","0.48948961","0.48936507","0.4893332","0.4893026","0.48888153","0.48815712","0.4877547","0.48764375","0.48679805","0.48677358","0.48607337","0.4859309","0.48580712","0.48528638","0.48472285","0.48445553","0.48437163","0.48431298","0.48375133","0.48353112","0.48173434","0.48115897","0.48106772","0.48067665","0.48040423","0.4801262","0.48003197","0.4799278","0.4794196","0.47918835","0.47916383","0.47877154","0.47851872","0.47802532","0.47771934","0.47771934","0.47771934","0.47759876","0.47702926","0.47677368","0.47675332","0.47671244","0.47659585","0.47612363","0.4756934","0.4755744","0.47514","0.47491455","0.47451773","0.47420615","0.47401464","0.47389933","0.47360614","0.4734958","0.47304857","0.47236165","0.4721751","0.47178397","0.47090822","0.4702159","0.46964377","0.4692878","0.46821427","0.46793064","0.46718496","0.46713755","0.46675187"],"string":"[\n \"0.5554169\",\n \"0.5521527\",\n \"0.53812873\",\n \"0.5335025\",\n \"0.5277362\",\n \"0.5266372\",\n \"0.5250536\",\n \"0.52459896\",\n \"0.5201471\",\n \"0.5174532\",\n \"0.5169621\",\n \"0.5158002\",\n \"0.5134929\",\n \"0.5060775\",\n \"0.5059112\",\n \"0.5053946\",\n \"0.50465447\",\n \"0.50403374\",\n \"0.50372404\",\n \"0.50230026\",\n \"0.5013707\",\n \"0.49840298\",\n \"0.49820694\",\n \"0.4975421\",\n \"0.4965126\",\n \"0.4963513\",\n \"0.49616337\",\n \"0.49530494\",\n \"0.49451962\",\n \"0.49432674\",\n \"0.49310958\",\n \"0.49284548\",\n \"0.492647\",\n \"0.49049306\",\n \"0.48948961\",\n \"0.48936507\",\n \"0.4893332\",\n \"0.4893026\",\n \"0.48888153\",\n \"0.48815712\",\n \"0.4877547\",\n \"0.48764375\",\n \"0.48679805\",\n \"0.48677358\",\n \"0.48607337\",\n \"0.4859309\",\n \"0.48580712\",\n \"0.48528638\",\n \"0.48472285\",\n \"0.48445553\",\n \"0.48437163\",\n \"0.48431298\",\n \"0.48375133\",\n \"0.48353112\",\n \"0.48173434\",\n \"0.48115897\",\n \"0.48106772\",\n \"0.48067665\",\n \"0.48040423\",\n \"0.4801262\",\n \"0.48003197\",\n \"0.4799278\",\n \"0.4794196\",\n \"0.47918835\",\n \"0.47916383\",\n \"0.47877154\",\n \"0.47851872\",\n \"0.47802532\",\n \"0.47771934\",\n \"0.47771934\",\n \"0.47771934\",\n \"0.47759876\",\n \"0.47702926\",\n \"0.47677368\",\n \"0.47675332\",\n \"0.47671244\",\n \"0.47659585\",\n \"0.47612363\",\n \"0.4756934\",\n \"0.4755744\",\n \"0.47514\",\n \"0.47491455\",\n \"0.47451773\",\n \"0.47420615\",\n \"0.47401464\",\n \"0.47389933\",\n \"0.47360614\",\n \"0.4734958\",\n \"0.47304857\",\n \"0.47236165\",\n \"0.4721751\",\n \"0.47178397\",\n \"0.47090822\",\n \"0.4702159\",\n \"0.46964377\",\n \"0.4692878\",\n \"0.46821427\",\n \"0.46793064\",\n \"0.46718496\",\n \"0.46713755\",\n \"0.46675187\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":1397,"cells":{"query":{"kind":"string","value":"Called by the GUI clock at regular intervals according to self.sampling_rate. Send a data request signal to the Arduino and interpret the json output. Return the entire history of all recorded data (regardless of whether or not a null value was read or if the data series are not 'checked' in the GUI)."},"document":{"kind":"string","value":"def sample(self):\n print(\"sampling bluetooth arduino\")\n self.sock.send(b'B')\n data = b''\n '''while True:\n data += self.sock.recv(1024)\n if data.endswith(b'\\n'):\n break\n '''\n #self.sock.settimeout(2)\n try:\n while True:\n d = self.sock.recv(255)\n data += d\n if d.find(b'\\n') != -1:\n break\n except Exception as err:\n print(err)\n pass\n print(data)\n data = json.loads(data.decode())\n if not any(x == 0 for x in data.values()):\n for label in self.data_labels:\n self.data[label].append(data[label])\n #self.data[\"time\"].append(time.time() - self.start)\n print(data)\n #print(self.data)\n #return self.data"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def recive_data(self):\n # read all available data\n while self.ser.inWaiting() > self.INPUT_DATA_SIZE+1:\n data = array.array('c')\n # search the header\n data.append(self.ser.read(1))\n while data[0] != chr(1):\n data[0] = self.ser.read(1)\n \n # wait for all available data\n while self.ser.inWaiting() < (self.INPUT_DATA_SIZE-1):\n time.sleep(0.03);\n \n # recives data\n data = self.ser.read(self.INPUT_DATA_SIZE-1)\n \n # prove if you want graphical data\n if self.pushButton_monitor.isChecked():\n # decodes the data\n t = struct.unpack('I', data[3]+data[2]+data[1]+data[0])\n r = struct.unpack('f', data[4]+data[5]+data[6]+data[7])\n x0 = struct.unpack('f', data[8]+data[9]+data[10]+data[11])\n x1 = struct.unpack('f', data[12]+data[13]+data[14]+data[15])\n u = struct.unpack('f', data[16]+data[17]+data[18]+data[19])\n \n self.time = t[0]*25e-9\n \n # prepare the string output\n aux_str = \" t = \"+str(self.time)+\"\\t\"\n aux_str += \" r = \"+str(r[0])+\"\\t\"\n aux_str += \" u = \"+str(u[0])+\"\\t\"\n aux_str += \" x1 = \"+str(x1[0])+\"\\t\"\n aux_str += \" x0 = \"+str(x0[0])+\"\\n\"\n # print string output\n self.textBrowser.insertPlainText(aux_str)\n \n # append data to the arrays\n self.graf_t.append(self.time)\n self.graf_r.append(r[0])\n self.graf_x0.append(x0[0])\n self.graf_x1.append(x1[0])\n self.graf_u.append(u[0])\n \n # remove one value if the arrays have maximum length\n if self.graf_t.buffer_info()[1] >= NUM_SAMPLES:\n self.graf_t.pop(0)\n self.graf_r.pop(0)\n self.graf_x0.pop(0)\n self.graf_x1.pop(0)\n self.graf_u.pop(0)\n \n # reload number of samples lavel\n self.label_samples_value.setText(str(self.graf_t.buffer_info()[1]))\n # reload number of waiting chars in serial rx buffer\n self.label_rx_buff_value.setText(str(self.ser.inWaiting()))\n\n # reload mutex area\n self.updated_data = 1\n \n # prove if there are available id's\n if (self.actionPC_Monitor.isChecked() and data[20] == chr(2)):\n # if it is true, looks how much id's\n i = struct.unpack('B', data[21])\n\n if i[0] < STACK_SIZE:\n for z in range(i[0]):\n new_device = struct.unpack('B', data[z+22])\n new_string = str(new_device[0])\n \n llista = self.listWidget_link.findItems(new_string, QtCore.Qt.MatchExactly)\n if len(llista) == 0:\n self.listWidget_link.addItem(new_string)","def run(self):\n while(not self.stop_event.is_set()):\n # read values until stop is sent\n response1 = _read_once(1,self.serial)\n response2 = _read_once(2,self.serial)\n #print(response)\n self.data1[\"d\"].append(response1) # Push response to the data list for later\n self.data2[\"d\"].append(response2) # Push response to the data list for later\n curTime = time.time()\n self.data1[\"t\"].append(curTime)\n self.data2[\"t\"].append(curTime)\n #sleep(0.0001) # I need to be small enough to capture peaks.\n return","def record_data(self, no_of_samples, interval):\r\n\r\n #tempory storage while function is completing\r\n temp_return_list = []\r\n\r\n #colec\r\n for i in range(0,no_of_samples):\r\n\r\n print(i)\r\n sensor_value = self.sen.get_sensor_value()\r\n\r\n temp_return_list.append([sensor_value,(i*interval)])\r\n\r\n time.sleep(interval)\r\n\r\n \r\n \r\n self.return_data = temp_return_list","def gather_data(self, *args, **kwargs):\n instrument_arg = kwargs.get('instrument', 'EUR_USD')\n granularity_arg = kwargs.get('granularity', 'M1')\n candle_format = kwargs.get('candleFormat', 'bidask')\n start_time = kwargs.get('start', '2014-10-01T00:00:00.000000Z')\n count_arg = kwargs.get('count', 5000)\n out_data = []\n data_complete = False\n while(not data_complete):\n response = self.oanda.get_history(instrument=instrument_arg,\n granularity=granularity_arg,\n candleFormat=candle_format,\n start=start_time,\n count=count_arg)\n raw_data = response['candles']\n if (len(out_data) == 0):\n out_data = out_data + raw_data\n elif (len(out_data) > 1):\n # raw_data[0] is already in out_data as raw_data[-1] from last\n # iteration\n out_data = out_data + raw_data[1:]\n start_time = raw_data[-1]['time']\n if (len(raw_data) < 5000):\n data_complete = True\n\n out_data = self._list_to_df(out_data)\n return out_data","def result(self):\n\n chart_series = [] # will hold all the series created\n\n # determine the sensor to plot from the sensor selected by the user.\n the_sensor = bmsapp.models.Sensor.objects.get(pk=self.request_params['select_sensor'])\n\n # get the requested averaging interval in hours\n averaging_hours = float(self.request_params['averaging_time'])\n\n # determine the start time for selecting records\n st_ts, end_ts = self.get_ts_range()\n\n # get the database records\n df = self.reading_db.dataframeForOneID(the_sensor.sensor_id, st_ts, end_ts, pytz.timezone(self.timezone))\n\n if not df.empty:\n\n # info needed to create each series (selection list, series name, visible)\n if self.schedule:\n occupied_times = df.ts.apply(self.schedule.is_occupied)\n unoccupied_times = -occupied_times\n\n series_info = [(None, 'All Data', True),\n (occupied_times, 'Occupied Periods', False),\n (unoccupied_times, 'Unoccupied Periods', False)]\n else:\n # no schedule, so just return the 'All Data' series\n series_info = [(None, 'All Data', True)]\n\n for mask, series_name, visibility in series_info:\n if mask is None:\n select_df = df\n else:\n select_df = df[mask]\n\n if averaging_hours:\n select_df = bmsapp.data_util.resample_timeseries(select_df, averaging_hours)\n\n histogram_series = bmsapp.data_util.histogram_from_series(select_df.val)\n\n chart_series.append({'x': [x for x,y in histogram_series],\n 'y': [y for x,y in histogram_series],\n 'type': 'scatter',\n 'mode': 'lines', \n 'name': series_name, \n 'visible': 'true' if visibility else 'legendonly'\n })\n\n opt = self.get_chart_options('plotly')\n opt['data'] = chart_series\n opt['layout']['title'] = the_sensor.title + ' Histogram: ' + self.building.title\n opt['layout']['xaxis']['title'] = the_sensor.unit.label\n opt['layout']['xaxis']['type'] = 'linear'\n opt['layout']['yaxis']['title'] = '% of Readings'\n opt['layout']['yaxis']['rangemode'] = 'tozero'\n\n html = basechart.chart_config.chart_container_html(opt['layout']['title'])\n\n return {'html': html, 'objects': [('plotly', opt)]}","def processData(self):\n recordSet = AresChartsService.toMultiSeries(self.vals, self.chartKeys, self.selectedX , self.chartVals, extKeys=self.extKeys)\n self.aresObj.jsGlobal.add(\"data_%s = %s\" % (self.htmlId, json.dumps(recordSet)))","def get_all(self):\n try:\n return self.current_data\n except:\n print('No data received from sensor')","def reqData(self):\r\n #self.reqGlobalCancel()\r\n #self.add_historical(\"Stock('TSLA', 'SMART', 'USD')\")\r\n #self.add_historical(\"Stock('IBM', 'SMART', 'USD')\")\r\n #self.add_historical(\"Stock('MSFT', 'SMART', 'USD')\")\r\n self.add_historical(\"Stock('FB', 'SMART', 'USD')\")","async def request_data(\r\n self,\r\n **kwargs, # pylint: disable=unused-argument\r\n ) -> None:\r\n await self._send(\"report 2\")\r\n\r\n if self.device_info.is_meter_integrated():\r\n await self._send(\"report 3\")\r\n\r\n if self.device_info.is_data_logger_integrated():\r\n await self._send(\"report 100\")","def automatic_meter_reading_demo():\n\n\t#Get sensor data from ellitrack\n\tserial = 17112915\n\n\t#get period dates\n\tfirst_day_of_the_month = datetime.datetime.today().replace(day=1)\n\tyesterday = datetime.datetime.now().date() - datetime.timedelta(days=1)\n\t#seven_days_earlier = yesterday - datetime.timedelta(days=7)\n\n\tperiod_from = yesterday.strftime(\"%d-%m-%Y\")\n\tperiod_from = period_from + ' +00:00:00'\n\tperiod_to = yesterday.strftime(\"%d-%m-%Y\")\n\tperiod_to = period_to + \" +23:59:59\"\n\n\t#print(period_from, period_to)\n\n\t#initialize request session\n\tlogin_url = \"http://www.ellitrack.nl/auth/login/\"\n\n\t#authenticate session\n\tellitrack_session = requests.Session()\n\tellitrack_session.post(login_url, data={'username': \"markdeblois\", 'password': \"upandegani\"})\n\n\t#get data for pure fresh ellitrack\n\tdata_url = \"http://www.ellitrack.nl/measurement/downloadexport/serialnumber/%s/type/period/n/0\" \\\n \"/periodtype/date/periodfrom/%s/periodto/%s/format/json\" % (serial, period_from, period_to)\n\tresp = ellitrack_session.get(data_url)\n\n\tif resp.status_code == 200:\n\t\toutput = StringIO(resp.text)\n\t\tell_df = pandas.read_csv(output, sep=\"\\t\")\n\n\t\t#unnecessary columns removed\n\t\tell_df_stripped = ell_df[ell_df.columns[0:2]]\n\n\t\t#get prev and curr readings\n\t\tprev_reading = ell_df_stripped['1 Energie'].min()\n\t\tcurr_reading = ell_df_stripped['1 Energie'].max()\n\n\t\t#Insert data into Meter Reading Sheet Doctype\n\t\tdata = {\n\t\t\t\"doctype\": \"Meter Reading Capture\",\n\t\t\t\"reading_date\": first_day_of_the_month,\n\t\t}\n\t\t\n\t\t#billing month\n\t\tget_curr_month = first_day_of_the_month.strftime(\"%B\")\n\n\t\tautomatic_readings_data = {\n\t\t\t\t\"doctype\": \"Meter Reading Sheet\",\n\t\t\t\t\"automatic_meter_id\": \"%s\" %serial,\n\t\t\t\t\"previous_automatic_readings\": \"%s\" %prev_reading,\n\t\t\t\t\"current_automatic_readings\": \"%s\" %curr_reading,\n\t\t\t\t\"parent\": \"All Territories %s 2018\" %get_curr_month,\n\t\t\t\t\"parenttype\": \"Meter Reading Capture\",\n\t\t\t\t\"parentfield\": \"meter_reading_sheet\"\n\t\t\t}\n\n\t\t#check if doc exists\n\t\tname = \"All Territories \"+get_curr_month+\" 2018\"\n\t\tdoc_list = frappe.get_list(\"Meter Reading Capture\", filters={'name':name})\n\t\tif doc_list:\n\t\t\tmdoc = frappe.get_doc(\"Meter Reading Capture\", name)\n\n\t\t\ttry:\n\t\t\t\tmrs_doc = frappe.get_doc(automatic_readings_data)\n\t\t\t\tmrs_doc.insert()\n\t\t\t\tfrappe.db.commit()\n\t\t\texcept Exception as err:\n\t\t\t\treturn err\n\t\telse:\n\t\t\t#create new doc\n\t\t\tdoc = frappe.new_doc(\"Meter Reading Capture\")\n\t\t\tdoc.reading_date = first_day_of_the_month\n\t\t\tdoc.billing_period = get_curr_month+\" 2018\"\n\t\t\tdoc.route = \"All Territories\"\n\t\t\tdoc.route_and_billing_period = name\n\n\t\t\ttry:\n\t\t\t\tdoc.insert()\n\t\t\t\tfrappe.db.commit()\n\t\t\texcept Exception as err:\n\t\t\t\treturn err\n\n\t\t\ttry:\n\t\t\t\t#update doc with the meter readings\n\t\t\t\tmrs_doc = frappe.get_doc(automatic_readings_data)\n\t\t\t\tmrs_doc.insert()\n\t\t\t\tfrappe.db.commit()\n\t\t\texcept Exception as err:\n\t\t\t\treturn err","def read(self):\n # return previous data if read() was already called less than 1 second ago\n time_since_last_read = (\n time.time_ns()*self.NS_TO_MS - self.query_time) * self.MS_TO_SEC\n if time_since_last_read < 1:\n return self.readings\n\n data_bytes = self.sensor.readline()\n data = data_bytes.decode('utf-8')\n\n # extract wind direction (deg) data\n min_direction = float(data[7:10])\n avg_direction = float(data[15:18])\n max_direction = float(data[23:26])\n\n # extract wind speed (m/s) data\n min_speed = float(data[31:34])\n avg_speed = float(data[39:42])\n max_speed = float(data[47:50])\n\n self.readings = [\n {\n \"type\": \"windDirection\",\n \"value\": {\n \"minDirection\": min_direction,\n \"avgDirection\": avg_direction,\n \"maxDirection\": max_direction\n }\n },\n {\n \"type\": \"windSpeed\",\n \"value\": {\n \"minSpeed\": min_speed,\n \"avgSpeed\": avg_speed,\n \"maxSpeed\": max_speed\n }\n }\n ]\n\n # update the last time of read() being called\n self.query_time = time.time_ns() * self.NS_TO_MS\n\n return self.readings","def get_data(self):\n try:\n data_string = self.ser.readline().decode()\n except UnicodeDecodeError as e:\n return self.get_data()\n \n if not data_string: # check for empty string\n return self.get_data()\n \n if data_string[0] == '|' and data_string[-1] == '\\n' and\\\n self.reset_confirmed:\n # if the data_string is valid, process it\n try:\n data_string = data_string.strip() \n data = data_string.split(',')\n assert len(data) == 7, \"Bad data Length\" \n data = [float(val) for val in data[1:]]\n data[0] /= 1000\n if self.ser.in_waiting: self.ser.reset_input_buffer()\n return data\n except (AssertionError, ValueError) as e:\n print(\"Error:\", type(e), e)\n if self.ser.in_waiting: self.ser.reset_input_buffer()\n return self.get_data()\n\n\n elif data_string[0] == '+' and data_string[-1] == '\\n' and\\\n self.reset_confirmed:\n # if the data_string is a valid time stamp, process it\n # self.system_timestamp = \"\\nSystem start time is: \"\\\n # \"%s\" % strftime(\"%Y/%m/%d %H:%M:%S\", localtime())\n self.arduino_timestamp = data_string.strip()\n print(self.arduino_timestamp)\n return self.get_data()\n \n elif data_string[0] == '/' and data_string[-1] == '\\n':\n # if string begins with / then it is a debug message and should\n # just be returned\n if \"setup finished\" in data_string.lower(): \n self.reset_confirmed = True\n print(data_string.strip())\n return self.get_data()\n else:\n # if the data_string is invalid try again\n return self.get_data()","def stremingData(self):\n ports = com_select()\n self.comport = None\n if not ports:\n QMessageBox.warning(self, 'No Connection',\n \"No unit found please verify that the IMU is connected\")\n else:\n for port in ports:\n if test_con(port):\n self.comport = port\n break\n if self.comport:\n if self.ui.qtBStream.text() == 'Stream':\n self.ui.qtBStream.setText('Stop')\n self.streamData = GetValue(self.comport)\n self.streamData.start()\n iter(self.streamData)\n self.timer = QTimer()\n self.timer.timeout.connect(self.graphupdate)\n self.i = 0\n self.__x = []\n if self.recF:\n if self.ui.qtBrowse.text() == '':\n self.file_select()\n if self.ui.qtBrowse.text() == '':\n QMessageBox.warning(self,\n 'No file',\n 'No file selected')\n self.stremingData()\n return 0\n self.timer.start()\n elif self.ui.qtBStream.text() == 'Stop':\n self.ui.qtBStream.setText('Stream')\n self.timer.stop()\n self.streamData.stop()\n self.data = [[] for i in range(8)]\n else:\n QMessageBox.warning(self, 'No Connection com search',\n \"No unit found please verify that the IMU is connected\")","def readOneData(self):\n\n\t\tif self._mt5Client is not None:\n\t\t\tdatas = self._mt5Client.getData()\n\n\t\t\tif datas is not None:\n\t\t\t\tPERIOD = int(self._config['data']['predict'])\n\t\t\t\tHALF_PERIOD = int(PERIOD/2)\n\n\t\t\t\tdata = []\n\n\t\t\t\t#Time Got\n\t\t\t\tself._LAST_PERIOD_PREDICTED_END = datas['time']\n\n\t\t\t\t#time open high low close tick_volume spread real_\n\t\t\t\t#Switch the price type calucation\n\n\t\t\t\tw_p = self._config['data']['price']\n\t\t\t\tv = 0\n\n\t\t\t\tif(w_p == CHART_PRICES_TYPE['O']):\n\t\t\t\t\tv = float(datas['open']) \n\n\t\t\t\telif(w_p == CHART_PRICES_TYPE['C']):\n\t\t\t\t\t\n\t\t\t\t\tv = float(datas['close']) \n\n\t\t\t\telif(w_p == CHART_PRICES_TYPE['H']):\n\t\t\t\t\t\n\t\t\t\t\tv = float(datas['high'])\n\n\t\t\t\telif(w_p == CHART_PRICES_TYPE['L']):\n\n\t\t\t\t\tv = float(datas['low']) \n\n\t\t\t\telif(w_p == CHART_PRICES_TYPE['HL/2']):\n\t\t\t\t\tv = ( float(datas['low']) + float(datas['high']) ) /2\n\t\t\t\t\n\t\t\t\tself.notify(msg={\n\t\t\t\t\t\t\t\t\t'prices': {\n\t\t\t\t\t\t\t\t\t\t'values': {\n\t\t\t\t\t\t\t\t\t\t\t'RP': str(v)\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t} \n\t\t\t\t\t\t\t\t} \n\t\t\t\t)\n\n\t\t\t\tdata.append(100000 * v ) \n\n\t\t\t\tself._TEMPORARY_GLOBAL_DATA.append(data[-1])\n\n\t\t\t\tself._GLOBAL_DATA.append(data[-1])\n\n\t\t\t\treturn data","def data_process():\n global localtime\n global value_dict\n sensor_types = sEtting.sensor_types\n sensor_values = []\n msg = None\n value_dict = collections.OrderedDict.fromkeys(sEtting.payload_header)\n value_dict[\"ver_format\"] = sEtting.ver_format\n value_dict[\"FAKE_GPS\"] = sEtting.fake_gps\n value_dict[\"app\"] = sEtting.app\n value_dict[\"ver_app\"] = sEtting.ver_app\n value_dict[\"device_id\"] = sEtting.device_id\n value_dict[\"date\"] = localtime.strftime(\"%Y-%m-%d\")\n value_dict[\"time\"] = localtime.strftime(\"%H:%M:%S\")\n value_dict[\"device\"] = sEtting.device\n\n for sensor in sensor_types:\n if sensor == 'pm25-at':\n value_dict[\"s_d0\"] = get_reading_csv(sensor)\n elif sensor == 'temperature':\n value_dict[\"s_t0\"] = get_reading_csv(sensor)\n elif sensor == 'humidity':\n value_dict[\"s_h0\"] = get_reading_csv(sensor)\n elif sensor == 'pm10-at':\n value_dict[\"s_d1\"] = get_reading_csv(sensor)\n else:\n print 'Not support sensor type.'\n if sEtting.fake_gps == 1:\n value_dict[\"gps_lat\"] = sEtting.fgps_lat\n value_dict[\"gps_lon\"] = sEtting.fgps_lon\n value_dict[\"gps_alt\"] = sEtting.fgps_alt\n value_dict[\"gps_fix\"] = 0\n else:\n value_dict[\"gps_lat\"] = get_gps()[0]\n value_dict[\"gps_lon\"] = get_gps()[1]\n value_dict[\"gps_alt\"] = get_gps()[2]\n value_dict[\"gps_fix\"] = gpsd.fix.mode\n value_dict[\"gps_num\"] = 0\n #if debug_enable == '0':\n msg = \"|\" + \"|\".join([\"=\".join([key, str(val)])\n for key, val in value_dict.items()])\n return msg\n #elif debug_enable == '1':\n # msg_debug = \",\".join([\"=\".join([key, str(val)]) for key, val in value_dict.items()])\n # return msg_debug","def recive_data(self, data_waveformreceived):\r\n self.adcollector.save_as_binary(self.savedirectory)\r\n self.channel_number = len(data_waveformreceived)\r\n if self.channel_number == 1: \r\n if 'Vp' in self.readinchan:\r\n self.data_collected_0 = data_waveformreceived[0]\r\n \r\n self.PlotDataItem_patch_voltage = PlotDataItem(self.xlabelhere_all, self.data_collected_0)\r\n #use the same color as before, taking advantages of employing same keys in dictionary\r\n self.PlotDataItem_patch_voltage.setPen('w')\r\n self.pw_data.addItem(self.PlotDataItem_patch_voltage)\r\n \r\n self.textitem_patch_voltage = pg.TextItem(('Vp'), color=('w'), anchor=(1, 1))\r\n self.textitem_patch_voltage.setPos(0, 1)\r\n self.pw_data.addItem(self.textitem_patch_voltage)\r\n elif 'Ip' in self.readinchan:\r\n self.data_collected_0 = data_waveformreceived[0]\r\n \r\n self.PlotDataItem_patch_current = PlotDataItem(self.xlabelhere_all, self.data_collected_0)\r\n #use the same color as before, taking advantages of employing same keys in dictionary\r\n self.PlotDataItem_patch_current.setPen('c')\r\n self.pw_data.addItem(self.PlotDataItem_patch_current)\r\n \r\n self.textitem_patch_current = pg.TextItem(('Ip'), color=('w'), anchor=(1, 1))\r\n self.textitem_patch_current.setPos(0, 1)\r\n self.pw_data.addItem(self.textitem_patch_current) \r\n elif 'PMT' in self.readinchan: # repeatnum, PMT_data_index_array, averagenum, ScanArrayXnum\r\n self.data_collected_0 = data_waveformreceived[0]*-1\r\n self.data_collected_0 = self.data_collected_0[0:len(self.data_collected_0)-1]\r\n \r\n # pmt data could come from raster scanning mode or from contour scanning mode.\r\n try:\r\n for i in range(self.repeatnum):\r\n self.PMT_image_reconstructed_array = self.data_collected_0[np.where(self.PMT_data_index_array_repeated == i+1)]\r\n Dataholder_average = np.mean(self.PMT_image_reconstructed_array.reshape(self.averagenum, -1), axis=0)\r\n Value_yPixels = int(len(self.samples_1)/self.ScanArrayXnum)\r\n self.PMT_image_reconstructed = np.reshape(Dataholder_average, (Value_yPixels, self.ScanArrayXnum))\r\n \r\n # Stack the arrays into a 3d array\r\n if i == 0:\r\n self.PMT_image_reconstructed_stack = self.PMT_image_reconstructed\r\n else:\r\n self.PMT_image_reconstructed_stack = np.concatenate((self.PMT_image_reconstructed_stack, self.PMT_image_reconstructed), axis=0)\r\n \r\n Localimg = Image.fromarray(self.PMT_image_reconstructed) #generate an image object\r\n Localimg.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+str(i)+'.tif')) #save as tif\r\n \r\n plt.figure()\r\n plt.imshow(self.PMT_image_reconstructed, cmap = plt.cm.gray)\r\n plt.show()\r\n except:\r\n np.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+'flatten'), self.data_collected_0)\r\n \r\n elif self.channel_number == 2: \r\n if 'PMT' not in self.readinchan:\r\n self.data_collected_0 = data_waveformreceived[0]\r\n \r\n self.PlotDataItem_patch_voltage = PlotDataItem(self.xlabelhere_all, self.data_collected_0)\r\n #use the same color as before, taking advantages of employing same keys in dictionary\r\n self.PlotDataItem_patch_voltage.setPen('w')\r\n self.pw_data.addItem(self.PlotDataItem_patch_voltage)\r\n \r\n self.textitem_patch_voltage = pg.TextItem(('Vp'), color=('w'), anchor=(1, 1))\r\n self.textitem_patch_voltage.setPos(0, 1)\r\n self.pw_data.addItem(self.textitem_patch_voltage) \r\n \r\n self.data_collected_1 = data_waveformreceived[1]\r\n \r\n self.PlotDataItem_patch_current = PlotDataItem(self.xlabelhere_all, self.data_collected_1)\r\n #use the same color as before, taking advantages of employing same keys in dictionary\r\n self.PlotDataItem_patch_current.setPen('c')\r\n self.pw_data.addItem(self.PlotDataItem_patch_current)\r\n \r\n self.textitem_patch_current = pg.TextItem(('Ip'), color=('w'), anchor=(1, 1))\r\n self.textitem_patch_current.setPos(0, 1)\r\n self.pw_data.addItem(self.textitem_patch_current) \r\n elif 'PMT' in self.readinchan:\r\n self.data_collected_0 = data_waveformreceived[0]*-1\r\n self.data_collected_0 = self.data_collected_0[0:len(self.data_collected_0)-1]\r\n \r\n try:\r\n for i in range(self.repeatnum):\r\n self.PMT_image_reconstructed_array = self.data_collected_0[np.where(self.PMT_data_index_array_repeated == i+1)]\r\n Dataholder_average = np.mean(self.PMT_image_reconstructed_array.reshape(self.averagenum, -1), axis=0)\r\n Value_yPixels = int(len(self.samples_1)/self.ScanArrayXnum)\r\n self.PMT_image_reconstructed = np.reshape(Dataholder_average, (Value_yPixels, self.ScanArrayXnum))\r\n \r\n # Stack the arrays into a 3d array\r\n if i == 0:\r\n self.PMT_image_reconstructed_stack = self.PMT_image_reconstructed\r\n else:\r\n self.PMT_image_reconstructed_stack = np.concatenate((self.PMT_image_reconstructed_stack, self.PMT_image_reconstructed), axis=0)\r\n \r\n Localimg = Image.fromarray(self.PMT_image_reconstructed) #generate an image object\r\n Localimg.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+str(i)+'.tif')) #save as tif\r\n \r\n plt.figure()\r\n plt.imshow(self.PMT_image_reconstructed, cmap = plt.cm.gray)\r\n plt.show()\r\n except:\r\n np.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+'contourscanning'), self.data_collected_0)\r\n \r\n if 'Vp' in self.readinchan:\r\n self.data_collected_1 = data_waveformreceived[1]\r\n \r\n self.PlotDataItem_patch_voltage = PlotDataItem(self.xlabelhere_all, self.data_collected_1)\r\n #use the same color as before, taking advantages of employing same keys in dictionary\r\n self.PlotDataItem_patch_voltage.setPen('w')\r\n self.pw_data.addItem(self.PlotDataItem_patch_voltage)\r\n \r\n self.textitem_patch_voltage = pg.TextItem(('Vp'), color=('w'), anchor=(1, 1))\r\n self.textitem_patch_voltage.setPos(0, 1)\r\n self.pw_data.addItem(self.textitem_patch_voltage)\r\n elif 'Ip' in self.readinchan:\r\n self.data_collected_1 = data_waveformreceived[1]\r\n \r\n self.PlotDataItem_patch_current = PlotDataItem(self.xlabelhere_all, self.data_collected_1)\r\n #use the same color as before, taking advantages of employing same keys in dictionary\r\n self.PlotDataItem_patch_current.setPen('c')\r\n self.pw_data.addItem(self.PlotDataItem_patch_current)\r\n \r\n self.textitem_patch_current = pg.TextItem(('Ip'), color=('w'), anchor=(1, 1))\r\n self.textitem_patch_current.setPos(0, 1)\r\n self.pw_data.addItem(self.textitem_patch_current)","def sample(self):\n timestamp = time.time()\n try:\n res = requests.get(self.url)\n except requests.exceptions.ConnectionError as error:\n LOG.warning(\"%s %s\", self, error)\n return\n if 199 < res.status_code < 300:\n self.data.append((timestamp, res.json()))\n LOG.debug(\"%s appended data sample\", self)\n else:\n LOG.warning(\"Error %s loading data from %s\", res.status_code, self)\n self.data = self.data[-self.max_samples:]","def getData(self):\n self.ser.write(b'g')\n readString = self.ser.readline()\n print(readString)\n readString = readString.decode(\"utf-8\")\n splittedString = readString.split('\\t')\n for i, num in enumerate(splittedString):\n try:\n splittedString[i] = int(float(num))\n except ValueError:\n pass\n self.accString.set('Accleration\\nX: %.5f\\nY: %.5f\\nZ: %.5f' %\n (splittedString[0], splittedString[1],\n splittedString[2]))\n self.logFile.write(readString)\n self.comJob = root.after(10, self.getData)","def get_values(self):\n if self.__work_state == work_state[\"Sleeping\"]:\n raise RuntimeError(\"{}: the sensor is sleeping and will not send any values. Will wake it up first.\".format(self.sensor_name))\n if self.__report_mode == report_mode[\"Passive\"]:\n raise RuntimeError(\"{}: the sensor is in passive report mode and will not automatically send values. You need to call request() to get values.\".format(self.sensor_name))\n\n self.__duty_cycle_start = time.time()\n while self.duty_cycle == 0 or time.time() < self.__duty_cycle_start + self.__read_timeout:\n response_data = self.__response()\n if len(response_data) > 0:\n self.logger.info(\"{}: received response from sensor {} bytes.\".format(self.sensor_name, len(response_data)))\n return self.__extract_values_from_response(response_data)\n raise IOError(\"{}: no data within read timeout of {} has been received.\".format(self.sensor_name, self.__read_timeout))","def collect_samples(serialPort,NO_SENSORS,NO_SAMPLES,log):\n run = '1'\n badSamples = 0\n count = 1\n log_temp = []\n temp = [0] * 20\n NO_FIELDS = (NO_SENSORS * 3) + 1\n \n while (run == '1'):\n # If the input buffer is not empty read the data out into rawData using \\n as a delimiter.\n if (serialPort.inWaiting()>0):\n rawData = serialPort.readline()\n print(rawData)\n \n # If invalid data is recieved this prevents program crash\n try:\n # Decode the bytes into a string\n data = rawData.decode()\n \n # Split x, y, z and newline values into a list\n if (count >= (NO_SAMPLES + 1)):\n endTime_temp = data.split(\" \", 2)\n if (len(endTime_temp) == 2 and '' not in endTime_temp):\n endTime = int(endTime_temp[0])\n else:\n endTime = 780\n print('Time not recieved')\n print('Lost Samples: ' + str(badSamples))\n run = '0'\n else:\n data_readings = data.split(\" \", NO_FIELDS)\n print(data_readings)\n \n # A correct sample should contain 16 values and not include null and so this is used\n # to validate the data and record any samples that are discarded in this way\n if (len(data_readings) == NO_FIELDS and '' not in data_readings):\n # Discard newline characters before saving data\n int_data_readings = list(map(int,data_readings[:(NO_FIELDS - 1)]))\n log_temp.append(int_data_readings)\n else:\n badSamples += 1\n except:\n print('Invalid data recieved')\n \n count += 1\n\n samplingPeriod = (endTime/NO_SAMPLES)/NO_SENSORS\n timeStamp = 0.0\n\n for i in range(0,len(log_temp)):\n for j in range(0,NO_SENSORS):\n temp[0+(j*4)] = log_temp[i][0+(j*3)]\n temp[1+(j*4)] = log_temp[i][1+(j*3)]\n temp[2+(j*4)] = log_temp[i][2+(j*3)]\n temp[3+(j*4)] = timeStamp\n timeStamp += samplingPeriod\n log.append(temp.copy())","def collect_data(self):\r\n self.vcp.read(self.vcp.inWaiting())\r\n while True:\r\n data = self.vcp.readline()\r\n data = data.decode(\"ASCII\")\r\n timestamp = \",\" + datetime.datetime.now().strftime(\"%H:%M:%S\")\r\n data_timestamp = data + timestamp\r\n if not self.data_pause:\r\n self.update_anemometer_log.emit(data_timestamp)\r\n if self.stop_timer:\r\n break","def send_data():\n range = request.args.get('range', '30')\n time = arrow.utcnow().replace(minutes=-int(range))\n data = Temperature.query\\\n .filter(Temperature.timestamp > time).order_by(Temperature.timestamp.desc()).all()\n return jsonify(results=[i.serialize for i in data])","def _obtain_data(self):\n (self.data_df, self.column_df, self.station_name, self.log_file, self.station_lat, self.station_lon,\n self.station_elev, self.ws_anemometer_height, self.missing_fill_value, self.script_mode,\n self.auto_mode, self.fill_mode, self.metadata_mode, self.generate_bokeh, self.metadata_df,\n metadata_series) = input_functions.obtain_data(self.config_path, self.metadata_path)\n\n if self.script_mode == 1: # correcting data\n self.mc_iterations = 1000 # Number of iters for MC simulation of thornton running solar radiation gen\n else:\n self.mc_iterations = 50 # if we're not correcting data then only do a few iterations to save time\n\n print(\"\\nSystem: Raw data successfully extracted from station file.\")\n\n # Extract individual variables from data frame back into to numpy arrays.\n self.data_year = np.array(self.data_df.year)\n self.data_month = np.array(self.data_df.month)\n self.data_day = np.array(self.data_df.day)\n self.data_tavg = np.array(self.data_df.tavg)\n self.data_tmax = np.array(self.data_df.tmax)\n self.data_tmin = np.array(self.data_df.tmin)\n self.data_tdew = np.array(self.data_df.tdew)\n self.data_ea = np.array(self.data_df.ea)\n self.data_rhavg = np.array(self.data_df.rhavg)\n self.data_rhmax = np.array(self.data_df.rhmax)\n self.data_rhmin = np.array(self.data_df.rhmin)\n self.data_rs = np.array(self.data_df.rs)\n self.data_ws = np.array(self.data_df.ws)\n self.data_precip = np.array(self.data_df.precip)\n\n self.output_file_path = \"correction_files/\" + self.station_name + \"_output\" + \".xlsx\"","def getSpectrumData(self):\n spectrum = []\n\n if not self.lastStatus.isHighSpeed:\n raise NotImplementedError('Full speed mode not implemented for {0}.'.format(self.model))\n\n packetCount = self.lastStatus.packetCount\n exposureTime = self.lastStatus.integrationTime\n\n for packet in range(packetCount):\n inputEndpoint = self.inputEndpoints[0]\n if self.idProduct == USB4000.classIdProduct and packet <= 3:\n inputEndpoint = self.inputEndpoints[1]\n\n values = self.readReply(inputEndpoint, unpackingFormat='<'+'H'*256, timeout=exposureTime*2)\n spectrum.extend(np.array(values))\n\n confirmation = self.readReply(inputEndpoint, size=1)\n if confirmation[0] != 0x69:\n self.flushEndpoints()\n raise RuntimeError('Spectrometer is desynchronized. Should disconnect')\n\n if self.discardTrailingSamples > 0:\n spectrum = spectrum[:-self.discardTrailingSamples]\n if self.discardLeadingSamples > 0:\n spectrum = spectrum[self.discardLeadingSamples:]\n\n return np.array(spectrum)","def logging_data(self):\n with open('sensor_data.log','w') as f:\n json.dump(self.read_continuous_data, f)","def linedata():\n get_values = request.args\n pc = get_values.get('pc') is not None # Per Capita\n gr = get_values.get('gr') is not None # Growth Rate\n place_args, _ = get_place_args(get_values)\n plot_data, _ = datachart_handler.get_plot_data(place_args, pc, gr)\n return json.dumps(plot_data)","def LoadingData(self, ticker, FullHistory=False):\r\n if FullHistory == False:\r\n url = \"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol={}&apikey={}\"\r\n else:\r\n url = \"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol={}&outputsize=full&apikey={}\"\r\n\r\n try:\r\n response = requests.get(url.format(ticker, self.key))\r\n response.raise_for_status()\r\n except requests.exceptions.RequestException as e:\r\n raise SystemExit(e)\r\n\r\n # The API returns 200 status even after you have a typo\r\n try:\r\n outputjson = response.json()['Time Series (Daily)']\r\n except:\r\n print(\"Please check ticker for typos or mismatches\")\r\n outputjson = None\r\n\r\n return outputjson, ticker","def getTemperatureMeasurements(self):\n # self.board.readline()\n self.stop = False\n times = []\n temps = [[], [], []]\n \n # A synchronisation string containing the characters tx is sent before each set of measurements,\n # we ensure correct reading of the measurements by waiting for this string\n while str(self.board.readline()).strip('b\\'\\\\rn') != 'tx':\n pass\n \n while not self.stop:\n # A synchronisation string containing the characters tx is sent before each set of measurements\n tx = self.board.readline()\n if str(tx).strip('b\\'\\\\rn') == 'tx':\n rawData1 = self.board.readline()\n rawData2 = self.board.readline()\n rawData3 = self.board.readline()\n rawData4 = self.board.readline()\n \n \n timeStamp = str(rawData1).strip('b\\'\\\\rn')\n temp1 = str(rawData2).strip('b\\'\\\\rn')\n temp2 = str(rawData3).strip('b\\'\\\\rn')\n temp3 = str(rawData4).strip('b\\'\\\\rn')\n try:\n times.append(float(timeStamp) / 1000)\n temps[0].append(float(temp1) / 128)\n temps[1].append(float(temp2) / 128)\n temps[2].append(float(temp3) / 128)\n # print(f'\\rtime: {float(timeStamp) / 1000:.2f} s, Temperature measured on sensor 1: {float(temp1) / 128:.2f} °C,'\n # f'sensor 2: {float(temp2) / 128:.2f} °C, sensor 3: {float(temp3) / 128:.2f} °C', sep='', end='', flush=True)\n except:\n print(rawData1, rawData2, rawData3, rawData4)\n \n \n if self.stop:\n print('\\nMeasurement finished...')\n \n self.data_stack[self.fetch_kinds[0]] = times\n self.data_stack[self.fetch_kinds[1]] = temps[0]\n self.data_stack[self.fetch_kinds[2]] = temps[1]\n self.data_stack[self.fetch_kinds[3]] = temps[2]\n \n if (len(self.data_stack['Sensor 1 Temp']) != len(times) or len(self.data_stack['Sensor 2 Temp']) != len(times) or len(self.data_stack['Sensor 3 Temp']) != len(times)):\n print(\"Warning: There may be some missing values!\")","def slot_fullhistory(self, dummy_sender, data):\r\n (history) = data\r\n\r\n if not len(history):\r\n self.debug(\"### history download was empty\")\r\n return\r\n\r\n def get_time_round(date):\r\n \"\"\"round timestamp to current candle timeframe\"\"\"\r\n return int(date / self.timeframe) * self.timeframe\r\n\r\n #remove existing recent candle(s) if any, we will create them fresh\r\n date_begin = get_time_round(int(history[0][\"date\"]))\r\n while len(self.candles) and self.candles[0].tim >= date_begin:\r\n self.candles.pop(0)\r\n\r\n new_candle = OHLCV(0, 0, 0, 0, 0, 0) #this is a dummy, not actually inserted\r\n count_added = 0\r\n for trade in history:\r\n date = int(trade[\"date\"])\r\n price = int(trade[\"price_int\"])\r\n volume = int(trade[\"amount_int\"])\r\n time_round = get_time_round(date)\r\n if time_round > new_candle.tim:\r\n if new_candle.tim > 0:\r\n self._add_candle(new_candle)\r\n count_added += 1\r\n new_candle = OHLCV(\r\n time_round, price, price, price, price, volume)\r\n new_candle.update(price, volume)\r\n\r\n # insert current (incomplete) candle\r\n self._add_candle(new_candle)\r\n count_added += 1\r\n self.debug(\"### got %d updated candle(s)\" % count_added)\r\n self.ready_history = True\r\n self.signal_fullhistory_processed(self, None)\r\n self.signal_changed(self, (self.length()))","def sample(self):\n logger.info(\"%s: collect sensor data\", self.__class__.__name__)\n samples = []\n self._fetch_data(samples)\n return samples","def AcquiredData (self, arguments=None) :\n\t\tself.OODriver.Wrapper_getSpectrum(self.wrapperHandle,self.spectrometerIndex,self.bufferHandle)\n\t\t\n\t\tif self.OODriver.Wrapper_isSaturated(self.wrapperHandle,self.spectrometerIndex) :\n\t\t\tprint \"Warning: OcenOptics spectrometer is saturated!\"\n\t\t\t\n\t\ttry : return self.buffer[self.spectral_interval]\n\t\texcept AttributeError : return self.buffer","def got_data(self, data):\n if self.get_current_state() == SBE37ProtocolState.DIRECT_ACCESS:\n # direct access mode\n if len(data) > 0:\n mi_logger.debug(\"SBE37Protocol._got_data(): <\" + data + \">\") \n if self._driver_event:\n self._driver_event(DriverAsyncEvent.DIRECT_ACCESS, data)\n # TODO: what about logging this as an event?\n return\n \n if len(data)>0:\n # Call the superclass to update line and prompt buffers.\n CommandResponseInstrumentProtocol.got_data(self, data)\n \n # If in streaming mode, process the buffer for samples to publish.\n cur_state = self.get_current_state()\n if cur_state == SBE37ProtocolState.AUTOSAMPLE:\n if SBE37_NEWLINE in self._linebuf:\n lines = self._linebuf.split(SBE37_NEWLINE)\n self._linebuf = lines[-1]\n for line in lines:\n self._extract_sample(line)","def get_data(self):\n self._send_command(self._adapter.get_data())","def sendHistoricAndPrediction(data):\n global df_hisotorical\n df_hisotorical = get_historical_data(data[\"UserID\"])\n data[\"seqMode\"] = 0\n data[\"versionline\"] = 0\n rounded_pred = predict(data)\n n = sendReport(data, rounded_pred, data[\"satzID\"], \"intv5\")\n\n return rounded_pred","def _log_data_received(self, timestamp, data, logconf):\n\n # Check so that the incoming data belongs to what we are currently\n # logging\n \n if self._previous_config:\n if self._previous_config.name == logconf.name:\n self._plot.add_data(data, timestamp)\n\n self.avgsumnumb=self.avgsumnumb+1;\n if self.avgsumnumb >= 50:\n print(\"Total:\", self.avgsumnumb)\n for name in data:\n print(\"Average\", name, self.avgsumvalue[name]/self.avgsumnumb)\n self.avgsumvalue[name]=0;\n self.avgsumnumb=0;\n for name in data:\n self.avgsumvalue[name]=self.avgsumvalue[name]+data[name];\n #print(self.avgsumvalue[name])\n #logger.info(\"Here %s\", data[name])\n #self._items[name].add_point(data[name], ts)\n #self.avgsumvalue[name]+=data[name];\n #logger.info(\"Here %s\", self.avgsumvalue[name])","def on_redraw_timer(self, event):\n \n if self.sampling_timer.IsRunning():\n self.daq.get_data()\n self.draw_plot()\n else:\n self.control_box.txt_info_box.SetLabel('Measurement complete')\n self.calculate()\n return","def get_new_data(self):\n\n # record bar parse performance\n self.logger.debug(\"Started parsing new ticks.\")\n start_parse = time.time()\n for exchange in self.exchanges:\n exchange.parse_ticks()\n end_parse = time.time()\n duration = round(end_parse - start_parse, 5)\n\n self.logger.debug(\n \"Parsed \" + str(self.total_instruments) +\n \" instruments' ticks in \" + str(duration) + \" seconds.\")\n self.track_tick_processing_performance(duration)\n\n # wrap new 1 min bars in market events\n new_market_events = []\n for exchange in self.exchanges:\n bars = exchange.get_new_bars()\n for symbol in exchange.get_symbols():\n for bar in bars[symbol]:\n event = MarketEvent(exchange.get_name(), bar)\n new_market_events.append(event)\n # add bars to save-to-db-later queue\n # TODO: store new bars concurrently with a processpool\n self.bars_save_to_db.put(event)\n return new_market_events","def get_data_sync(self, out_format: str='json', chk_interval=0.25, max_chks=65535):\n if self.data:\n return self.data\n check_cnt = 0\n while True:\n if check_cnt >= max_chks:\n break\n self.data_ready = self.check_available()\n if self.data_ready:\n break\n else:\n check_cnt += 1\n sleep(chk_interval)\n if not self.data_ready:\n raise DataNotReady(\"The run {} has not yet finished, data not available yet.\".format(self))\n resp = self.ph.conn.request(\n 'GET', self.ph.URLS['getdata'].format(self.run_token), dict(api_key=self.ph.api_key, format=out_format))\n data = resp.data.decode('utf-8')\n self.data = self.parse_json_data(data)\n return self.data","def generate_data(self):\n print(\"generate_data - init\")\n with open(self.input_file, \"r\") as f:\n\n # read JSON data from input file\n data = json.loads(f.read())\n\n for idx, row in enumerate(data): \n # serialize Python dict to string\n msg = self.serialize_json(row)\n #print(f\"Linha: {row}\")\n self.send(self.topic, msg)\n self.flush()\n #print(\"Sleeping\")\n time.sleep(1)","def getCurentData(self):\n if not self.labExperiment:\n super().getCurentData()\n else:\n return np.array(self.connection.query('get_actuator_data'))","def data():\n if request.method == 'POST':\n params = extract_variables(['temp', 'humid', 'pressure', 'light',\n 'smoke', 'time', 'sensor_id'], request)\n # Test to see if the minimum required variables were parsed\n # TODO: Make this smarter\n if not (params['temp'] or params['humid'] or params['pressure'])\\\n or not params[\"sensor_id\"]:\n # There's either no information or no sensor_id and time\n abort(400)\n # If there's no timestamp we'll assign one\n # This makes it possible to use micro controller based sensors\n # without RTC\n if not params['time']:\n params['time'] = time.time()\n # Make sure sensor id is a valid integer\n try:\n int(params[\"sensor_id\"])\n except ValueError:\n abort(400)\n\n try:\n # Try inserting values\n query_db('INSERT INTO climate VALUES (?, ?, ?, ?, ?, ?, ?)',\n [params['temp'], params['humid'], params['pressure'],\n params['light'], params['smoke'],\n params['time'], params[\"sensor_id\"]], commit=True)\n except sqlite3.IntegrityError:\n # Sensor not in database yet, add it with a temporary name\n query_db('INSERT INTO sensors VALUES (?, ?)',\n [params[\"sensor_id\"], str(uuid.uuid4())], commit=True)\n # Then insert values...\n query_db('INSERT INTO climate VALUES (?, ?, ?, ?, ?, ?, ?)',\n [params['temp'], params['humid'], params['pressure'],\n params['light'], params['smoke'],\n params['time'], params[\"sensor_id\"]], commit=True)\n return 'Sensor added and data saved'\n return 'Data saved'\n elif request.method == 'GET':\n params = extract_variables(['start_time', 'end_time', 'sensor_id'], request)\n data = query_climate_range(**params)\n return jsonify(results=data)","def read_and_display_data(hat, samples_per_channel, num_channels): \n \n # Read all of the available samples (up to the size of the read_buffer which\n # is specified by the user_buffer_size). Since the read_request_size is set\n # to -1 (READ_ALL_AVAILABLE), this function returns immediately with\n # whatever samples are available (up to user_buffer_size) and the timeout\n # parameter is ignored.\n total_samples_read = 0\n read_request_size = READ_ALL_AVAILABLE\n completeFlag = 0 \n timeout = 5.0\n \n # file switch: w = Write to a file\n # file switch: w+ = Write to a file, if it doesn't exist create it\n # file switch: a = Append to a file\n # file switch: a+ = Append to a file, if is doesn't exist create it.\n # file switch: x = will create a file, returns an error if the file exist\n \n\n # If the scan starts, create a file name based upon current date and time.\n # Retrieve the Current Working Directory and generate the full path \n # to where to write the collected data as a .csv file. Open the file \n # begin writing the data to the file. When done, close the file.\n \n try:\n if os.path.exists(basepath):\n if not (os.path.exists(mypath)):\n os.mkdir(mypath)\n else:\n os.mkdir(basepath)\n os.chdir(basepath)\n os.mkdir(mypath)\n except OSError as exc:\n raise\n \n os.chdir(mypath)\n fileDateTime = datetime.strftime(datetime.now(), \"(%m_%d_%Y)-(%H-%M-%S)\")\n #filePath = mypath + \"/\" + DAQ_NAME + \"_\" + fileName + \".csv\"\n filePath = mypath + \"/\" + DAQ_NAME + \"_\" + fileDateTime + \".csv\"\n csvfile = open(filePath, \"w+\")\n csvwriter = csv.writer(csvfile) \n \n # Recording LED\n GPIO.setmode(GPIO.BCM)\n GPIO.setup(RECORDING_LED, GPIO.OUT, initial=GPIO.LOW)\n GPIO.output(RECORDING_LED,GPIO.HIGH)\n \n while total_samples_read < samples_per_channel:\n read_result = hat.a_in_scan_read(read_request_size, timeout)\n\n # Check for an overrun error\n if read_result.hardware_overrun:\n print('\\n\\nHardware overrun\\n')\n break\n elif read_result.buffer_overrun:\n print('\\n\\nBuffer overrun\\n')\n break\n elif not (read_result.running and completeFlag == 0):\n completeFlag = 1\n print('\\n (2) Recording Completed - Buffer Draining')\n\n samples_read_per_channel = int(len(read_result.data) / num_channels)\n total_samples_read += samples_read_per_channel\n \n totalSamples = len(read_result.data) \n\n if samples_read_per_channel > 0:\n index = samples_read_per_channel * num_channels - num_channels\n \n new_index = 0\n myArray=[] #create an empty array\n for i in range(0, totalSamples, num_channels):\n myArray.append([]) #add a row to the array (COLUMN)\n for j in range(num_channels):\n\t\t\t\t\t#append a num_channels of data to the array (ROW)\n myArray[new_index].append(read_result.data[i + j]) \n new_index+=1\n\n csvwriter.writerows(myArray) #Write the array to file\n csvfile.flush\n\n # Cleanup\n csvfile.close() \n print('\\n (3) Buffer Drained - Data Saved to CSV File\\n')\n GPIO.cleanup()\n GPIO.setmode(GPIO.BCM)\n \n # Complete LED\n GPIO.setup(COMPLETE_LED, GPIO.OUT, initial=GPIO.LOW)\n GPIO.output(COMPLETE_LED,GPIO.HIGH)\n time.sleep(5)\n GPIO.cleanup()\n hat.a_in_scan_cleanup()\n global CMD_RECEIVED\n CMD_RECEIVED = 1\n \n # Restarts script to prepare for another recording\n main()","def _response_power_buffer(self, message):\n if message.logaddr.value == self._last_log_address:\n self._last_log_collected = True\n # Collect logged power usage\n for i in range(1, 5):\n if getattr(message, \"logdate%d\" % (i,)).value != None:\n dt = getattr(message, \"logdate%d\" % (i,)).value\n if getattr(message, \"pulses%d\" % (i,)).value == 0:\n self.power_history[dt] = 0.0\n else:\n self.power_history[dt] = self.pulses_to_kWs(\n getattr(message, \"pulses%d\" % (i,)).value, 3600\n )\n # Cleanup history for more than 2 day's ago\n if len(self.power_history.keys()) > 48:\n for dt in list(self.power_history.keys()):\n if (dt + self.stick.timezone_delta - timedelta(hours=1)).date() < (\n datetime.now().today().date() - timedelta(days=1)\n ):\n del self.power_history[dt]\n # Recalculate power use counters\n last_hour_usage = 0\n today_power = 0\n yesterday_power = 0\n for dt in self.power_history:\n if (dt + self.stick.timezone_delta) == datetime.now().today().replace(\n minute=0, second=0, microsecond=0\n ):\n last_hour_usage = self.power_history[dt]\n if (\n dt + self.stick.timezone_delta - timedelta(hours=1)\n ).date() == datetime.now().today().date():\n today_power += self.power_history[dt]\n if (dt + self.stick.timezone_delta - timedelta(hours=1)).date() == (\n datetime.now().today().date() - timedelta(days=1)\n ):\n yesterday_power += self.power_history[dt]\n if self.power_consumption_prev_hour != last_hour_usage:\n self.power_consumption_prev_hour = last_hour_usage\n self.do_callback(SENSOR_POWER_CONSUMPTION_PREVIOUS_HOUR[\"id\"])\n if self.power_consumption_today != today_power:\n self.power_consumption_today = today_power\n self.do_callback(SENSOR_POWER_CONSUMPTION_TODAY[\"id\"])\n if self.power_consumption_yesterday != yesterday_power:\n self.power_consumption_yesterday = yesterday_power\n self.do_callback(SENSOR_POWER_CONSUMPTION_YESTERDAY[\"id\"])","def get_data_from_api():\n s_date = datetime.now()\n uid = uuid.uuid1()\n start_time = time.time()\n cfl.logging.info(f'new session num {uid} was created at {s_date} ')\n\n functions_dict = {'graph' : get_stock_graph_in_range, 'holder': get_stock_holder, 'balance': get_balance,\n 'cash_flow': get_cash_flow, 'earning': get_earning}\n\n answers = inquirer.prompt(questions)\n symbol = answers.get(\"symbol\")\n\n func = functions_dict[answers.get('user_option')]\n\n if answers.get(\"user_option\") == \"graph\" :\n answer_graph = inquirer.prompt(question_graph)\n start_date = answer_graph.get(\"start_date\")\n end_date = answer_graph.get(\"end_date\")\n period = answer_graph.get(\"period\")\n e_date = datetime.now()\n end_time = time.time()\n print(f\"{func(symbol, start_date, end_date, period)}\\n\")\n cfl.logging.info(f' session {uid} end at : {e_date} ')\n cfl.logging.info(f'the time it took to get data from api for session {uid} is: {end_time - start_time} ')\n return\n\n else:\n end_time = time.time()\n e_date = datetime.now()\n print(f\"{func(symbol)}\\n\\n\")\n cfl.logging.info(f' session {uid} end at : {e_date} ')\n cfl.logging.info(f'the time it took to get data from api for session {uid} is: {end_time - start_time} ')\n return","def get_data(self):\n if self.ser.in_waiting:\n data_string = self.ser.readline().decode().strip()\n if not data_string: return self.data\n self.data = [\n float(element) for element in data_string.split()\n ]\n self.ser.reset_input_buffer()\n return self.data","def _stab_log_data(self, timestamp, data, logconf):\n\t\t#print strftime(\"%H:%M:%S \", gmtime())\n\t\tstr1=data['mb.distance']\n\t\tnum1=float(str1)\n\t\tnum1=30-num1\n\n\t\t#self.updateplot(num1)\n\t\t#print \"test: \",num1\n\t\t#self.databuffer.append(num1)\n\t\t#self.y[:] = self.databuffer\n\t\t#self.curve.setData(x,num1)\n\t\t#self.app.processEvents()\n\n\t\tresults.append(num1)\n\t\tresultspyqt.append(num1)\n\t\tself.x = list(range(0,len(resultspyqt)))\n\t\t\n\t\t\n\t\t\n\t\tprint \"[%d][%s]: %s\" % (timestamp, logconf.name, data)\n\t\t\n\t\t#if not data: break\n\t\tdata=self.serv_listen()\n\t\tif data>0:\n\t\t\tprint \"app: \",data\n\t\t\tif(int(data)<100):#we are in thrust\n\t\t\t\tprint \"thrust\"\n\t\t\t\tprint self.roll, self.pitch, self.yawrate, self.thrust \n\t\t\t\tself.thrust=int(data)*600\n\t\t\t\tself._cf.commander.send_setpoint(self.roll, self.pitch, self.yawrate, self.thrust)\n\t\t\t\t#time.sleep(0.1)\n\t\t\telif((int(data)>100)and(int(data)<200)):#we are in pitch\n\t\t\t\tprint roll, pitch, yawrate, thrust \n\t\t\t\tpitch=(int(data))/5-30\n\t\t\t\tself._cf.commander.send_setpoint(roll, (int(data))/5-30, yawrate, thrust)\n\t\t\t\t#time.sleep(0.1)\n\t\t\telif(int(data)>200):#we are in roll\n\t\t\t\tprint \"add roll: \",150-(int(data))*3/5\n\t\t\t\tprint roll, pitch, yawrate, thrust \n\t\t\t\troll=50-(int(data))/5\n\t\t\t\tself._cf.commander.send_setpoint(50-(int(data))/5, pitch, yawrate, thrust)\n\t\t\t\t#time.sleep(0.1) \n\t\tif data == 'Hover':\n\t\t\tprint \"app: \",data","def result(self):\n\n # determine the X and Y sensors to plot from those sensors selected by the user.\n sensorX = bmsapp.models.Sensor.objects.get(pk=self.request_params['select_sensor_x'])\n sensorY = bmsapp.models.Sensor.objects.get(pk=self.request_params['select_sensor_y'])\n\n # determine the averaging time\n averaging_hours = float(self.request_params['averaging_time_xy'])\n\n # get the building's timezone\n tz = pytz.timezone(self.timezone)\n\n # determine the start and end time for selecting records\n st_ts, end_ts = self.get_ts_range()\n\n # get the dividing date, if there is one\n div_datestring = self.request_params['div_date']\n div_dt = tz.localize(parser.parse(div_datestring)) if len(div_datestring) else None\n\n\n # The list that will hold each series\n series = []\n\n # get the X and Y sensor records and perform the requested averaging\n dfX = self.reading_db.dataframeForOneID(sensorX.sensor_id, st_ts, end_ts, tz)\n dfY = self.reading_db.dataframeForOneID(sensorY.sensor_id, st_ts, end_ts, tz)\n\n if not dfX.empty and not dfY.empty: # both sensors have some data, so proceed to average the data points\n \n dfX = bmsapp.data_util.resample_timeseries(dfX,averaging_hours)\n dfX.rename(columns = {'val':'X'}, inplace = True)\n\n dfY = bmsapp.data_util.resample_timeseries(dfY,averaging_hours)\n dfY.rename(columns = {'val':'Y','ts':'tsY'}, inplace = True)\n\n # Join the X and Y values for the overlapping time intervals and make\n # a list of points.\n df_all = dfX.join(dfY, how='inner') # inner join does intersection of timestamps\n\n # make sure there are matched records before continuing\n if len(df_all):\n\n # add a point name column to be used in the tooltip.\n df_all['name'] = df_all.index.strftime('%a %m/%d/%y %H:%M')\n\n # add a column identifying whether point is in occupied or unoccupied period.\n resolution = self.occupied_resolution()\n if (self.schedule is None) or (resolution is None):\n # no schedule or data doesn't lend itself to classifying\n # consider all points to be occupied\n df_all['occupied'] = 1\n else:\n df_all['occupied'] = [self.schedule.is_occupied(ts, resolution=resolution) for ts in df_all.ts]\n\n # Set up the parameters for the different series of data\n # Required Info is (starting datetime, ending datetime, occupied status (0 or 1), series name, \n # series color, series symbol, series radius, series zindex).\n now_dt = datetime.now()\n if div_dt:\n # A dividing date was provided by the user.\n div_dt = div_dt.replace(tzinfo=None) # needs to be naive\n ser_params = ( (datetime(1970,1,1), div_dt, 1, 'Prior to %s' % div_datestring, '#2f7ed8', 'circle', 4.5),\n (datetime(1970,1,1), div_dt, 0, 'Prior to %s, Unoccupied' % div_datestring, '#2f7ed8', 'triangle-up', 3),\n (div_dt, now_dt, 1, '%s and beyond' % div_datestring, '#FF0000', 'circle', 4.5),\n (div_dt, now_dt, 0, '%s and beyond, Unoccupied' % div_datestring, '#FF0000', 'triangle-up', 3) )\n else:\n # Divide data by how recent it is.\n ser_params = ( (now_dt - timedelta(days=1), now_dt, 1, 'Last 24 Hours', '#FF0000', 'circle', 4.5),\n (now_dt - timedelta(days=1), now_dt, 0, 'Last 24 Hours, Unoccupied', '#FF0000', 'triangle-up', 3),\n (now_dt - timedelta(days=7), now_dt - timedelta(days=1), 1, 'Last 7 Days', '#00CC00', 'circle', 4.5),\n (now_dt - timedelta(days=7), now_dt - timedelta(days=1), 0, 'Last 7 Days, Unoccupied', '#00CC00', 'triangle-up', 3),\n (datetime(1970,1,1), now_dt - timedelta(days=7), 1, '7+ Days Old', '#2f7ed8', 'circle', 4.5),\n (datetime(1970,1,1), now_dt - timedelta(days=7), 0, '7+ Days Old, Unoccupied', '#2f7ed8', 'triangle-up', 3),\n )\n\n for t_start, t_end, occup, ser_name, ser_color, ser_symbol, radius in reversed(ser_params):\n mask = (df_all.index >= t_start) & (df_all.index < t_end) & (df_all.occupied==occup)\n if mask.max():\n series.append( {'x': np.char.mod('%.4g',df_all[mask].X.values).astype(float).tolist(),\n 'y': np.char.mod('%.4g',df_all[mask].Y.values).astype(float).tolist(),\n 'text': df_all[mask].name.values.tolist(),\n 'type': 'scatter',\n 'mode': 'markers', \n 'name': ser_name,\n 'marker': { 'color': ser_color,\n 'symbol': ser_symbol,\n 'size': radius * 2\n }\n } )\n\n # create the X and Y axis labels and the series\n x_label = '%s, %s' % (sensorX.title, sensorX.unit.label)\n y_label = '%s, %s' % (sensorY.title, sensorY.unit.label)\n\n opt = self.get_chart_options('plotly')\n opt['data'] = series\n opt['layout']['title'] = sensorY.title + \" vs. \" + sensorX.title\n opt['layout']['xaxis']['title'] = x_label\n opt['layout']['yaxis']['title'] = y_label\n opt['layout']['legend']['traceorder'] = 'reversed'\n\n html = basechart.chart_config.chart_container_html(opt['layout']['title'])\n\n return {'html': html, 'objects': [('plotly', opt)]}","def realtimestreaming(self, **kwargs):\n url_path = 'realtimestreaming'\n self.logger.debug(f\"Get Realtime Streaming report data\")\n body = self._make_body(kwargs)\n return self._common_post(request_path=url_path, body=body)","def _send_data(self):\n \n # Do not send more than 100 datasets each time (totally arbitrary)\n MAX_DATA_SETS_PER_POST = 100\n data_to_send = self._data_buffer[0:MAX_DATA_SETS_PER_POST]\n data_to_keep = self._data_buffer[MAX_DATA_SETS_PER_POST:]\n\n # Prepare data string with the values in data buffer\n now = time.time()\n data_string = '[' \n for (timestamp, data) in data_to_send:\n data_string += '['\n data_string += str(round(timestamp-now,2))\n for sample in data:\n data_string += ','\n data_string += str(sample)\n data_string += '],'\n # Remove trailing comma and close bracket\n data_string = data_string[0:-1]+']'\n\n self._log.debug(\"Data string: \" + data_string)\n \n # Prepare URL string of the form\n # 'http://domain.tld/emoncms/input/bulk.json?apikey=\n # 12345&data=[[-10,10,1806],[-5,10,1806],[0,10,1806]]'\n url_string = self._settings['protocol'] + self._settings['domain'] + \\\n self._settings['path'] + \"/input/bulk_json?apikey=\" + \\\n self._settings['apikey'] + \"&data=\" + data_string\n self._log.debug(\"URL string: \" + url_string)\n\n # Send data to server\n self._log.info(\"Sending to \" + \n self._settings['domain'] + self._settings['path'])\n try:\n result = urllib2.urlopen(url_string, timeout=60)\n except urllib2.HTTPError as e:\n self._log.warning(\"Couldn't send to server, HTTPError: \" + \n str(e.code))\n except urllib2.URLError as e:\n self._log.warning(\"Couldn't send to server, URLError: \" + \n str(e.reason))\n except httplib.HTTPException:\n self._log.warning(\"Couldn't send to server, HTTPException\")\n except Exception:\n import traceback\n self._log.warning(\"Couldn't send to server, Exception: \" + \n traceback.format_exc())\n else:\n if (result.readline() == 'ok'):\n self._log.debug(\"Send ok\")\n # Send ok -> empty buffer\n self._data_buffer = data_to_keep\n return True\n else:\n self._log.warning(\"Send failure\")","def giveHistoricalData(stockName):\n now = datetime.datetime.fromtimestamp(getTime())\n fiveDaysAgo = datetime.datetime.fromtimestamp(\n getTime() - daysToSeconds(5)\n )\n\n resp = json.dumps(\n getHistoricalData(stockName, fiveDaysAgo)\n )\n return resp","async def last_read(self):\n try:\n asyncio.set_event_loop(self.loop)\n asyncio.get_event_loop().create_task(self.browse())\n await self.browse()\n\n # parse the return reads and extract the most recent one\n # (i.e. last not None)\n jsonResponse = json.loads(self.raw_data)\n lastRead = None\n for read in jsonResponse['reads']:\n if read['value'] is None:\n break\n lastRead = read\n _LOGGER.debug(\"lastRead = %s\", lastRead)\n\n self.startTime = lastRead['startTime']\n self.endTime = lastRead['endTime']\n self.last_read_val = lastRead['value']\n self.unit_of_measurement = jsonResponse['unit']\n\n _LOGGER.debug(\"last read = %s %s %s %s\", self.startTime, self.endTime, self.last_read_val, self.unit_of_measurement)\n\n return self.startTime, self.endTime, self.last_read_val, self.unit_of_measurement\n except:\n raise MeterError(\"Error requesting meter data\")","def GetData(self):\r\n if self.Error == False:\r\n Extra = {}\r\n try:\r\n result = {}\r\n temp = self.ScrapeMainWebpage()\r\n if temp != None:\r\n result.update(temp)\r\n temp = self.ScrapeParameters1Webpage()\r\n if temp != None:\r\n result.update(temp)\r\n temp = self.ScrapeParameters2Webpage()\r\n if temp != None:\r\n result.update(temp)\r\n temp = self.ScrapeStatusWebpage()\r\n if temp != None:\r\n result.update(temp)\r\n sqlArray = {}\r\n sqlArray[self.deviceDescr] = {}\r\n sqlArray[self.deviceDescr][self.devNumber] = {}\r\n sqlArray[self.deviceDescr][self.devNumber][\"General\"] = result\r\n sqlArray[self.deviceDescr][self.devNumber][\"_ExtractInfo\"] = {}\r\n sqlArray[self.deviceDescr][self.devNumber][\"_ExtractInfo\"][\"ExtractTime\"] = time.time()\r\n sqlArray[\"ReadError\"] = False \r\n return sqlArray\r\n \r\n except Exception as e: \r\n self.log.printError(\"ERROR in Retreiving Seatel VSAT Data,%s Module Error\" % sys._getframe().f_code.co_name) \r\n self.log.printError( str(e))\r\n self.Error = True\r\n Extra[\"ReadError\"] = True\r\n return Extra\r\n else:\r\n self.log.printWarning(\"%s skipped due to previous failure\" % sys._getframe().f_code.co_name)\r\n return None","def get_raw_data(self, dataset):\n\t\tprint(\"Getting raw data for\", dataset)\n\t\tself.raw_documents[dataset] = []\n\t\tself.Y[dataset] = []\n\n\t\twith open(self.jsons[dataset]) as handle:\n\t\t\tfor line in handle:\n\t\t\t\tjson_obj = json.loads(line)\n\t\t\t\tstars = json_obj[\"stars\"]\n\t\t\t\tif stars != 3:\n\t\t\t\t\tself.raw_documents[dataset].append(json_obj[\"text\"])\n\t\t\t\t\tself.Y[dataset].append(int(stars > 3))","def request_realtime_info(self):\n self.socket_datastream.sendto(b\"!r\", self.ip_port_arduino_datastream)\n self.socket_datastream.sendto(b\"!s\", self.ip_port_arduino_datastream)","def update_data():\n values = temp_serial_placeholder()\n time = current_time_milli() - __start\n points = [ [time, values[0]], [time, values[1]] ]\n __data.append(points)\n return points","def process_data(self, data):\n parsed = json.loads(data)\n current = parsed[\"current\"]\n future = parsed[\"hourly\"]\n current_res = self.get_columns(current)\n self.database_conn(\"current\", -1, current_res)\n for hour, data in enumerate(future):\n current_res = self.get_columns(data)\n self.database_conn(\"current\", hour, current_res)","def get_data(stream_url, count, is_graph):\n data = requests.get(stream_url + '/Data' + '?count=' + str(count) + '&Startindex=1970-01-01T00:00:00Z', headers=headers)\n Values = []\n for event in data.json():\n Values.append(event['Value'])\n if is_graph:\n terminalplot.plot(range(len(Values)), Values)\n else:\n print(Values)\n input(\"Press any key to continue...\")\n return","def _plot_data(self, data):\r\n # only send data if xqueue exists\r\n if self.capa_system.xqueue is None:\r\n return {'success': False, 'message': 'Cannot connect to the queue'}\r\n\r\n # pull relevant info out of get\r\n response = data['submission']\r\n\r\n # construct xqueue headers\r\n qinterface = self.capa_system.xqueue['interface']\r\n qtime = datetime.utcnow().strftime(xqueue_interface.dateformat)\r\n callback_url = self.capa_system.xqueue['construct_callback']('ungraded_response')\r\n anonymous_student_id = self.capa_system.anonymous_student_id\r\n # TODO: Why is this using self.capa_system.seed when we have self.seed???\r\n queuekey = xqueue_interface.make_hashkey(str(self.capa_system.seed) + qtime +\r\n anonymous_student_id +\r\n self.input_id)\r\n xheader = xqueue_interface.make_xheader(\r\n lms_callback_url=callback_url,\r\n lms_key=queuekey,\r\n queue_name=self.queuename)\r\n\r\n # construct xqueue body\r\n student_info = {\r\n 'anonymous_student_id': anonymous_student_id,\r\n 'submission_time': qtime\r\n }\r\n contents = {\r\n 'grader_payload': self.plot_payload,\r\n 'student_info': json.dumps(student_info),\r\n 'student_response': response\r\n }\r\n\r\n (error, msg) = qinterface.send_to_queue(header=xheader,\r\n body=json.dumps(contents))\r\n # save the input state if successful\r\n if error == 0:\r\n self.input_state['queuekey'] = queuekey\r\n self.input_state['queuestate'] = 'queued'\r\n self.input_state['queuetime'] = time.time()\r\n\r\n return {'success': error == 0, 'message': msg}","def test_get_measurement_history(self):\n device = DeviceFactory(node=Node.objects.first(), external_id='123', type__code=SecureDeviceType.SRT321,\n device_param__type__code=SecureDeviceParameterType.MEASURED_TEMPERATURE)\n d_id_1 = device.external_id\n\n now_loc = datetime.datetime.now(bst)\n ts_loc = now_loc - datetime.timedelta(seconds=30)\n ts_str = ts_loc.strftime('%Y-%m-%dT%H:%M:%S')\n\n data = self.create_secure_server_push_data(d_id_1, ts_str)\n\n SecureClient.process_push_data(data)\n time.sleep(.5)\n\n # get newer timestamp\n ts_str = now_loc.strftime('%Y-%m-%dT%H:%M:%S')\n data = self.create_secure_server_push_data(d_id_1, ts_str, value=\"23.5\")\n\n SecureClient.process_push_data(data)\n\n token = Token.objects.get(user__username=email)\n device_param = device.parameters.first()\n client = APIClient()\n client.credentials(HTTP_AUTHORIZATION='Token ' + token.key)\n url = reverse('api:device_measurements', kwargs={'device_parameter_id': device_param.id})\n\n time.sleep(.5)\n\n response = client.get(url, format='json')\n\n self.assertTrue(response.status_code == 200)\n self.assertTrue(len(response.data) >= 2)","def get_com_data(self):\n self.form_url_str()\n if self.__print_url: print self.com_data_full_url\n self.download_json()\n self.get_datalist_fr_json()","def measurements():\n print(\"server received request for precipitation data...\")\n return jsonify(measurements_data)","def read_live_data(wearable_port):\r\n IMU1_num = []\r\n IMU2_num = []\r\n IMU3_num = []\r\n\r\n try:\r\n wearable = serial.Serial(wearable_port, baudrate=115200, timeout=5)\r\n #arduino = serial.Serial(arduino_port, timeout=1)\r\n # Delay for 2 seconds to wait for serial port to be ready.\r\n print(\"Waiting 2 seconds for serial to be ready.\")\r\n time.sleep(2)\r\n except Exception as e:\r\n print(e)\r\n print('Please check the port')\r\n return\r\n\r\n input(\"Press Enter to continue...\")\r\n str(wearable.write(bytes(33)))\r\n # Open file to store the data; filename includes date and time; format: data-YYYYMMDDHHmmss.csv\r\n filename = \"data-\" + str(dt.datetime.now().strftime(\"%Y%m%d%H%M%S\")) + \".csv\"\r\n filenamplot = \"plot-\" + str(dt.datetime.now().strftime(\"%Y%m%d%H%M%S\")) + \".png\"\r\n print(\"Opening %s\" % filename)\r\n f = open(filename, \"a+\")\r\n # f.write(\"power,rpm\\n\")\r\n count = 1000\r\n # Get data and continuously yield Power and RPM as integers\r\n\r\n while (count >0):\r\n count = count -1\r\n #if arduino.in_waiting > 0:\r\n wearable.flushInput()\r\n\r\n '''\r\n arduino_output = arduino.readline().decode(\"utf_8\", \"strict\")\r\n print(\"Distance: %s\" % arduino_output)\r\n f.writelines(\"%s\" % arduino_output)\r\n if arduino_output == \"Hard Stop\\r\\n\":\r\n break\r\n arduino_output = arduino_output.replace(\"\\r\\n\", \"\")\r\n Distance.append(int(float(arduino_output)))\r\n '''\r\n\r\n try:\r\n data = wearable.readline().decode(\"utf_8\", \"strict\")\r\n data = data.replace(\"\\r\\n\", \"\\n\").split()\r\n IMU1= data[2].replace(\"\\n\", \"\")\r\n IMU1_num.append(int(IMU1))\r\n IMU2 = data[3].replace(\"\\n\", \"\")\r\n IMU2_num.append(int(IMU2))\r\n IMU3 = data[4].replace(\"\\n\", \"\")\r\n IMU3_num.append(int(IMU3))\r\n print(\"IMU1: %s\\t IMU2: %s\\t IMU3: %s\\t\" % (IMU1, IMU2, IMU3))\r\n f.writelines(\"%s,%s,%s,%s\\n\" % (IMU1, IMU2, IMU3))\r\n yield int(IMU1), int(IMU2), int(IMU3)\r\n except Exception as e:\r\n print('error')\r\n f.writelines(\"Error\\n\")\r\n\r\n print('Program ended.')\r\n t = numpy.linspace(1, len(IMU1_num), len(IMU1_num))\r\n fig, (ax1) = plt.subplots(nrows=1, ncols=1, figsize=(16.0, 9.0)) # create figure & 1 axis\r\n ax1.plot(t, IMU1_num, t, IMU2_num,t, IMU3_num)\r\n ax1.set_title('IMU')\r\n ax1.legend(('IMU1', 'IMU2', 'IMU3'))\r\n # manager = plt.get_current_fig_manager()\r\n # manager.resize(*manager.window.maxsize())\r\n fig.savefig(filenamplot)\r\n plt.show()\r\n\r\n f.close()\r\n #arduino.close()\r\n wearable.close()","def loop(self) -> None:\n while True:\n # Sleep before running code to ensure that the sensor is\n # initialized on first run, as per the specifications.\n sleep(config.SLEEP)\n\n self.setup_quiet_hours()\n\n if self.quiet_setup:\n if self.in_quiet_hours():\n if config.DC_QH:\n self.sensor.close()\n self.sleep_quiet_hours()\n continue\n\n # In the case that quiet hours were established during first run\n # and removed from the endpoint afterwards, the sensor may not\n # be in the open state. Because serial.Serial.open() may raise\n # an exception if the sensor is already open, just check prior.\n if not self.sensor.isOpen():\n self.sensor.open()\n\n config.LOGGER.info('Woke up after sleeping. Running loop()')\n self.data = []\n for _ in range(10):\n datum = self.sensor.read()\n self.data.append(datum)\n\n for pm, start in self._SLICES.items():\n # Might be necessary to give the endpoint some time\n # between responses\n sleep(10)\n reading = self.read_data_from_bytes(start)\n aq_dict = air_quality.AQS[pm].get_range(reading)\n\n sections = [\n {\n 'type': 'text',\n 'color': aq_dict['color'],\n 'value': f'Quality: {aq_dict[\"label\"]}'\n },\n {\n 'type': 'gauge',\n 'color': [aq_dict['color']],\n 'range': [aq_dict['lower'], aq_dict['upper']],\n 'value': reading,\n },\n {\n 'type': 'gauge',\n 'color': air_quality.COLORS,\n 'range': air_quality.AQS[pm].get_all_ranges(),\n 'value': reading,\n }\n ]\n\n data = {\n 'module': f'photo-dash-sds011-pm{pm}',\n 'title': f'Air Quality - PM{pm}',\n 'sections': sections,\n }\n\n try:\n r = requests.put(config.ENDPOINT, json=data)\n except Exception as e: # Catching broad Exceptions for now\n config.LOGGER.error(e)\n config.LOGGER.info(r.status_code)","def get_data(last):\n Table = \"ServerRoom\"\n filter = \"\"\n if last == \"lastone\":\n data = request_meteodata(\"SELECT * from `ServerRoom` ORDER BY id DESC LIMIT 1 \")\n if len(data) == 0:\n return [SensorData(datetime.datetime.now(), 0, 0)]\n res = []\n for d in data:\n res.append(SensorData(d[1], d[2], d[3]))\n return res\n if last != \"All\":\n limit = datetime.datetime.now().astimezone(utz)\n if last == \"24hours\":\n limit -= datetime.timedelta(hours=24)\n else:\n limit = limit.replace(hour=0, minute=0, second=0, microsecond=0)\n if last == \"3days\":\n limit -= datetime.timedelta(days=3)\n elif last == \"7days\":\n limit -= datetime.timedelta(days=7)\n elif last == \"month\":\n limit = limit.replace(day=1)\n elif last == \"30days\":\n limit -= datetime.timedelta(days=30)\n elif last == \"year\":\n limit = limit.replace(day=1, month=1)\n filter = \" WHERE `date` > '\" + str(limit) + \"'\"\n order = \" ORDER BY `date` ASC\"\n req = \"SELECT * FROM `\" + Table + \"`\" + filter + order\n data = request_meteodata(req)\n if len(data) == 0:\n print(\"no data: get all\")\n req = \"SELECT * FROM `\" + Table + \"`\" + order\n data = request_meteodata(req)\n res = []\n for d in data:\n res.append(SensorData(d[1], d[2], d[3]))\n return res","def pull_data(stop_event):\r\n logger = logging.getLogger(__name__)\r\n\r\n # List of current formats supported\r\n currency_list = ['https://www.bitstamp.net/api/v2/ticker_hour/btceur', 'https://www.bitstamp.net/api/v2/ticker_hour/btcusd',\r\n 'https://www.bitstamp.net/api/v2/ticker_hour/ethusd', 'https://www.bitstamp.net/api/v2/ticker_hour/etheur']\r\n\r\n # Loop until told otherwise!\r\n while not stop_event.is_set():\r\n for currency in currency_list:\r\n res = requests.get(currency)\r\n try:\r\n res.raise_for_status()\r\n except requests.exceptions.HTTPError as e:\r\n # Not 200\r\n logger.error(str(e))\r\n continue\r\n\r\n # Get the end characters to dertermine the type e.g. btceur, ethusd, etc...\r\n currency_type = (currency.rpartition('/')[-1])\r\n logger.info('The Curreny type: ' + currency_type)\r\n\r\n if currency_type == 'btceur':\r\n table = 'btceur'\r\n elif currency_type == 'btcusd':\r\n table = 'btcusd'\r\n elif currency_type == 'ethusd':\r\n table = 'ethusd'\r\n elif currency_type == 'etheur':\r\n table = 'etheur'\r\n else:\r\n table = None\r\n\r\n # Extract Data and Fields\r\n data = res.json()\r\n field_list = data.keys()\r\n logger.info(field_list)\r\n value_list = data.values()\r\n logger.info(value_list)\r\n\r\n # Write to DB\r\n db_commit(table, field_list, value_list)\r\n # Cannot make more than 600 requests per 10 minutes or they will ban your IP address.\r\n # Will in time get real time using their websocket API.\r\n time.sleep(5)","def loadData(self):\r\n self.samplerate = self.app.samplerate\r\n self.sensors = self.app.sensors\r\n self.sensorMask = self.app.sensorMask\r\n self.measurements = self.app.measurements\r\n\r\n # Get min and max data points\r\n for sens in self.sensor_ids:\r\n try:\r\n for i in range(1,self.measurements):\r\n if float(self.app.data[i][sens].text) < self.sensor_range[0]:\r\n self.sensor_range[0] = float(self.app.data[i][sens].text)\r\n elif float(self.app.data[i][sens].text) > self.sensor_range[1]:\r\n self.sensor_range[1] = float(self.app.data[i][sens].text)\r\n except:\r\n print(self.app.data)\r\n \r\n # Set x scale from 0 to end of track\r\n self.scalex = [0,self.measurements]\r\n## self.scalex = [0,self.w/2]\r\n # Set y scale to maximum sensor measurement\r\n self.setScaleY(self.sensor_range[0], self.sensor_range[1])","def get_data(self):\n\n self.set_query_string()\n self.realtime_data = super().get_data()\n self.set_coordinate()\n return self.realtime_data","def get_json(self):\r\n self.get_recordrange()\r\n [\r\n self.json_data.setter(n, self.get_data(\"json\", x))\r\n for n, x in enumerate(tqdm(self.iterlist))\r\n ]","def getDataParsed():\r\n serialConsole.flush()\r\n rawData = serialConsole.readline().decode(\"utf-8\").rstrip()\r\n parsedJson = json.loads(rawData)\r\n return parsedJson","def test():\n temp_data = fetch_temp_data(\n (\"https://opendata-download-metobs.smhi.se/api/version/\" +\n \"latest/parameter/1/station/52350/period/latest-day/data.json\"))\n data = temp_series(temp_data)\n print(data)","def plot(accessToken, collection):\n \n plt.xlabel('Date/Time')\n plt.ylabel('Sensor Value')\n plt.title(\"Sensors Monitor\")\n \n # to save png files\n i = 0\n \n # set interactive mode on\n plt.ion()\n \n # set figure to full screen\n mng = plt.get_current_fig_manager()\n mng.full_screen_toggle()\n\n while True:\n jsondata = getJsonData(accessToken)\n if jsondata:\n #limit date string\n jsondata[DATE] = jsondata[DATE][8:13]\n appendJsonData(jsondata, collection)\n \n # clear figure\n plt.clf()\n \n # limit samples to be viewed\n if (len(collection[DATE]) > SAMPLE_SIZE_LIMIT):\n plt.xticks(range(SAMPLE_SIZE_LIMIT), collection[DATE][-SAMPLE_SIZE_LIMIT:])\n plt.plot(collection[SENSOR1][-SAMPLE_SIZE_LIMIT:], 'k', label='sensor 1')\n plt.plot(collection[SENSOR2][-SAMPLE_SIZE_LIMIT:], 'b', label='sensor 2')\n plt.plot(collection[SENSOR3][-SAMPLE_SIZE_LIMIT:], 'g', label='sensor 3')\n plt.plot(collection[SENSOR4][-SAMPLE_SIZE_LIMIT:], 'r', label='sensor 4')\n else:\n plt.xticks(range(len(collection[DATE])), collection[DATE])\n plt.plot(collection[SENSOR1], 'k', label='sensor 1')\n plt.plot(collection[SENSOR2], 'b', label='sensor 2')\n plt.plot(collection[SENSOR3], 'g', label='sensor 3')\n plt.plot(collection[SENSOR4], 'r', label='sensor 4')\n \n plt.legend(loc='upper left')\n plt.show()\n \n # Take a screenshot on Gnome desktop\n if os.environ.get(\"XDG_MENU_PREFIX\").startswith(\"gnome\"):\n os.system(\"gnome-screenshot -f screenshot{}.png\".format(i))\n i = i+1\n \n #plt.pause(1)\n plt.pause(60*60) # one hour\n else:\n print(str(datetime.datetime.now()) + \" Empty json data\")","def getSamples(self,limit=None):\n theseReadings = self.readings\n if limit:\n theseReadings = theseReadings[:limit]\n return [x.asJSON() for x in theseReadings]","def readData(self, duration_s, toV=True, maxAI=1024, maxV=5.0,\n updateFunc=None, nPntsUpdate=1, trigger=[]):\n isDone = False\n nLines = 0\n empty = numpy.array([])\n \n if self.rate_ms >= 0:\n nPnts = round(duration_s *1000.0 /self.rate_ms)\n print(\"{0:.3f} s duration = {1} samples\".format(duration_s, nPnts))\n else: \n nPnts = 100\n print(\"Sample rate invalid, {0} samples will be recorded\".format(nPnts))\n\n if not(self.isOpen): \n print(\"ERROR: Link not open\")\n return (-1, empty, empty, empty)\n \n # Create empty arrays for the data\n #\n np_data_0 = numpy.zeros([nPnts], dtype=float)\n np_data_1 = numpy.zeros([nPnts], dtype=float)\n np_data_t = numpy.zeros([nPnts], dtype=float)\n np_dt_ms = numpy.zeros([nPnts], dtype=float)\n \n # Attempt to read data\n #\n while not(isDone):\n # Read a line\n #\n (errC, parts) = self.__readLine()\n if not(errC == 0):\n return (errC, empty, empty, empty)\n \n else: \n np_data_0[nLines] = float(parts[2])\n np_data_1[nLines] = float(parts[3])\n np_data_t[nLines] = float(parts[0])/1000.0\n np_dt_ms[nLines] = float(parts[1]) /1000.0\n \"\"\"\n print(\"{0:.3f} {1} {2}\".format(int(parts[0])/1000.0, \n int(parts[2]), int(parts[3])))\n \"\"\"\n # Update plot of data, if requested\n #\n if updateFunc and ((nLines % nPntsUpdate) == 0):\n updateFunc(nLines, np_data_t[nLines], np_data_0[nLines], \n np_data_1[nLines])\n \n if nLines < (nPnts-1):\n sys.stdout.write(\"\\r{0:.0f}% {1:.3f} s: {2:.3f} {3:.3f} ...\"\n .format(nLines/float(nPnts) *100, \n np_data_t[nLines]/1000.0,\n np_data_0[nLines], np_data_1[nLines]))\n else: \n sys.stdout.write(\"\\r100% done\" +\" \"*40 +\"\\n\")\n \n nLines += 1\n isDone = (nLines == nPnts)\n \n print(\"SUCCESS\") \n print(\"{0} data points recorded\".format(nLines))\n print(\"Rate = {0:.3f} +/- {1:.3f} ms\".format(numpy.mean(np_dt_ms), \n numpy.std(np_dt_ms)))\n\n if toV: \n np_data_0 = np_data_0 /float(maxAI -1) *maxV\n np_data_1 = np_data_1 /float(maxAI -1) *maxV\n \n return (0, np_data_t, np_data_0, np_data_1)","def collect_data(self):\n self.lines = []\n\n while True:\n self._process_serial_data()","def update(self):\r\n mc = self._motor_controllers[0]\r\n lj = self._labjacks[0]\r\n r = None\r\n\r\n lj._finished = False\r\n errors = 0\r\n missed = 0\r\n # Read from Queue until there is no data.\r\n try:\r\n # get([block[, timeout]])¶\r\n # Remove and return an item from the queue. If optional\r\n # args block is true and timeout is None (the default),\r\n # block if necessary until an item is available. If timeout\r\n # is a positive number, it blocks at most timeout seconds\r\n # and raises the Empty exception if no item was available\r\n # within that time. Otherwise (block is false), return an\r\n # item if one is immediately available, else raise the\r\n # Empty exception (timeout is ignored in that case).\r\n # Pull results out of the Queue in a blocking manner.\r\n result = lj.raw_data.get(False) # (True, 0.0001)\r\n if result[\"errors\"] != 0:\r\n errors += result[\"errors\"]\r\n missed += result[\"missed\"]\r\n logging.warning(\r\n \"Total Errors: {}, Total Missed: \"\r\n \"{}\".format(errors, missed),\r\n extra=self.extra)\r\n # Convert the raw bytes (result['result']) to voltage data.\r\n r = lj.device.processStreamData(result['result'])\r\n lj.raw_data.task_done()\r\n lj.raw_data_ready.clear()\r\n except lj.raw_data.Empty:\r\n if lj._finished:\r\n logging.info(\"Done reading from the Queue.\", extra=self.extra)\r\n else:\r\n logging.error(\"Queue is empty. Stopping...\", extra=self.extra)\r\n lj._finished = True\r\n except Exception as e:\r\n logging.error(\"{}: {}\".format(e), extra=self.extra)\r\n lj._finished = True\r\n\r\n with lj.raw_data.mutex:\r\n lj.raw_data.queue.clear()\r\n current_time = self._times[-1] + self._dt\r\n self._times.append(current_time)\r\n self._data[\"time (s)\"] = self._times\r\n\r\n for s in lj.sensors():\r\n name = '{} {} ({})'.format(s.parent().name,\r\n s.name,\r\n s.signal.units)\r\n if r is not None:\r\n # Get the average, make sure the length of the list\r\n # is a float for float division.\r\n voltage = (\r\n (sum(r[AIN.upper() + str(s.channel)]) /\r\n float(len(r[AIN.upper() + str(s.channel)])))\r\n )\r\n # convert to physical quantity\r\n v = Q_(np.asarray([voltage]), 'V')\r\n if s.name == 'p1':\r\n quantity = convert_pressure_px119(\r\n v, r_shunt=Q_(470.0, 'ohm'),\r\n value_range=Q_(np.array([0, 30]), 'psi'), zero=Q_(1.375, 'kPa')\r\n ).magnitude[0]\r\n elif s.name == 'p2':\r\n quantity = convert_pressure_px119(\r\n v, r_shunt=Q_(470.0, 'ohm'),\r\n value_range=Q_(np.array([0, 30]), 'psi'), zero=Q_(1.7, 'kPa')\r\n ).magnitude[0]\r\n elif s.name == 'p3':\r\n quantity = convert_pressure_px119(\r\n v, r_shunt=Q_(470.0, 'ohm'),\r\n value_range=Q_(np.array([0, 30]), 'psi'), zero=Q_(1.85, 'kPa')\r\n ).magnitude[0]\r\n elif s.name == 'T1':\r\n # logging.debug(\"T sensor voltage {}\".format(v[0]), extra=self.extra)\r\n quantity = convert_temperature_rtd(\r\n v, v_in=Q_(2.5, 'V'),\r\n r1=Q_(100., 'ohm'), filename='pt100.txt', zero=Q_(0.29, 'degC')\r\n ).magnitude[0]\r\n elif s.name == 'T2':\r\n # logging.debug(\"T sensor voltage {}\".format(v[0]), extra=self.extra)\r\n quantity = convert_temperature_rtd(\r\n v, v_in=Q_(2.5, 'V'),\r\n r1=Q_(100., 'ohm'), filename='pt100.txt', zero=Q_(-0.05, 'degC')\r\n ).magnitude[0]\r\n elif s.name == 'T3':\r\n # logging.debug(\"T sensor voltage {}\".format(v[0]), extra=self.extra)\r\n quantity = convert_temperature_rtd(\r\n v, v_in=Q_(2.5, 'V'),\r\n r1=Q_(100., 'ohm'), filename='pt100.txt'\r\n ).magnitude[0]\r\n elif s.name == 'T4':\r\n # logging.debug(\"T sensor voltage {}\".format(v[0]), extra=self.extra)\r\n quantity = convert_temperature_rtd(\r\n v, v_in=Q_(2.5, 'V'),\r\n r1=Q_(100., 'ohm'), filename='pt100.txt'\r\n ).magnitude[0]\r\n elif s.name == 'frate': # flow rate\r\n # logging.debug(\"magmeter voltage {}\".format(v[0]), extra=self.extra)\r\n quantity = convert_flow_rate_magmeter(\r\n v, r_shunt=Q_(465.2, 'ohm'),\r\n value_range=Q_(np.array([0, 80]), 'l/min')\r\n ).magnitude[0]\r\n if quantity < 0.0:\r\n quantity = 0.0\r\n else:\r\n quantity = voltage\r\n s.signal.field.setText('{:3.1f}'.format(quantity))\r\n self._data[name].append(quantity)\r\n\r\n for i, m in enumerate(mc.children()):\r\n if m is not None:\r\n mc.r_lock.acquire()\r\n for s in m.sensors():\r\n value = s.read()\r\n name = '{} {} ({})'.format(s.parent().name,\r\n s.name,\r\n s.signal.units)\r\n s.signal.field.setText('{:3.2f}'.format(value))\r\n self._data[name].append(value)\r\n mc.r_lock.release()\r\n d = {}\r\n for k, v in self._data.items():\r\n d[k] = '{:3.10f}'.format(v[-1])\r\n self._csv_writer.writerow(d)\r\n self._line_plot.setData(self._times, self._data[self._signal])","async def _get_data(self):\n coros = []\n results = []\n for series_ids in self.series_ids:\n response = self._post(data={\"series_id\": series_ids})\n coros.append(response)\n if len(coros) == 5: # throttle at 5\n _ = await asyncio.gather(*coros)\n results.extend(_)\n coros = [] # Reset accumulator\n if coros:\n results.extend(await asyncio.gather(*coros))\n\n return filter(None, results)","def sensor_history(self, sensor_name, start_time_sec, end_time_sec,\n include_value_ts=False, timeout_sec=0):\n\n if timeout_sec != 0:\n self._logger.warn(\n \"timeout_sec is no longer supported. Default tornado timeout is used\")\n\n params = {\n 'sensor': sensor_name,\n 'start_time': start_time_sec,\n 'end_time': end_time_sec,\n 'limit': MAX_SAMPLES_PER_HISTORY_QUERY,\n 'include_value_time': include_value_ts\n }\n\n url = url_concat(\n (yield self.get_sitemap())['historic_sensor_values'] + '/query', params)\n self._logger.debug(\"Sensor history request: %s\", url)\n response = yield self._http_client.fetch(url)\n data_json = json.loads(response.body)\n if 'data' not in data_json:\n raise SensorHistoryRequestError(\"Error requesting sensor history: {}\"\n .format(response.body))\n data = []\n for item in data_json['data']:\n if 'value_time' in item:\n sample = SensorSampleValueTime(item['sample_time'],\n item['value_time'],\n item['value'],\n item['status'])\n else:\n sample = SensorSample(item['sample_time'],\n item['value'],\n item['status'])\n data.append(sample)\n result = sorted(data, key=_sort_by_sample_time)\n raise tornado.gen.Return(result)","def get_data_logic():\r\n global input_exchange\r\n global input_symbols\r\n global all_symbols\r\n global input_timeframe\r\n\r\n # create exchange connection\r\n exchange = Exchange(input_exchange)\r\n\r\n # perform check that exchange can grab price data\r\n if exchange.connection.has['fetchOHLCV']:\r\n\r\n # user ticked 'All Symbols?', so includes all symbols in\r\n # exchange_tickers.py for the particular exchange\r\n if all_symbols:\r\n symbol_list = SymbolList(symbols='auto', exchange=exchange)\r\n # user didn't tick 'All Symbols?', so create unpopulated symbol list\r\n else:\r\n symbol_list = SymbolList(exchange=exchange)\r\n # add all symbols user inputted\r\n for s in input_symbols:\r\n symbol_list.input_symbol(s)\r\n\r\n # get auto timeframe and check it is valid\r\n timeframe = Timeframe(timeframe=input_timeframe, exchange=exchange)\r\n while not timeframe.check_timeframe():\r\n timeframe.input_timeframe() # default to asking for input\r\n\r\n print(f\"Pulling data on the {timeframe.tf} timeframe for...\")\r\n print(symbol_list.symbols)\r\n\r\n # get current time in UTC in milliseconds\r\n now = datetime.now().astimezone(pytz.timezone('UTC'))\r\n now = int(now.timestamp()*1000)\r\n\r\n # loop over each symbol and pull new data\r\n for sym in symbol_list.symbols:\r\n # create csv filename and path\r\n file_sym = sym.replace('/', '')\r\n file_sym = file_sym.replace('-', '')\r\n filename = f\"{exchange.name}_{file_sym}_{timeframe.tf}.csv\" # generate filename from given information\r\n csv_path = f\"{exchange.name}/{timeframe.tf}/{filename}\"\r\n\r\n # get most recent price data and append it to existing data\r\n # (if it exists)\r\n price_data = PriceData(exchange=exchange, tf=timeframe.tf,\r\n sym=sym, now=now, path=csv_path)\r\n\r\n # check if price data csv already exists\r\n if price_data.exists():\r\n price_data.get_current()\r\n # get new data as far back as possible if csv does not exist\r\n else:\r\n price_data.get_new()\r\n\r\n # keep updating price_data until current time\r\n price_data.update()\r\n\r\n # write to csv\r\n price_data.write()\r\n\r\n print(\"Finished writing files!\")","def main():\n data_file = 'shrec_timer.json'\n\n if len(sys.argv) == 2:\n generate_data(data_file, sys.argv[1])\n\n plot_data(data_file)","def startDataAcq(self):\r\n\t\tglobal payload, control, output_settings, serials, datfiles\r\n\t\t# INITIALIZE THE OUTPUT FOLDER STRUCTURE\r\n\t\tcheck_dir(output_settings['folder'], output_settings['cruise'], payload)\r\n\t\tconfirm_dir(output_settings['folder'], output_settings['cruise'])\r\n\t\t# FIND THE START TIME\r\n\t\toutput_settings['start_time'] = init_time()\r\n\t\t# PRINT THE START TIME\r\n\t\tprint_spacer()\r\n\t\tprint 'Local Time: ', time.ctime(output_settings['start_time'])\r\n\t\tprint 'UTC: ', time.asctime(time.gmtime(output_settings['start_time']))\r\n\t\t\r\n\t\t# LOOP THROUGH THE SCIENTIFIC PAYLOAD\r\n\t\tfor k in payload.keys():\r\n\t\t\ttry:\r\n\t\t\t\tif serials[k].isOpen():\r\n\t\t\t\t\tclose_serial(serials[k])\r\n\t\t\texcept KeyError:\r\n\t\t\t\tprint ' '\r\n\t\t\t\t# print 'Serial port connected to '+k+' was not previously open.'\r\n\t\t\t# open the serial port\r\n\t\t\tserials[k] = init_serial(payload[k])\r\n\t\t\tif serials[k].isOpen():\t\t\t\t\r\n\t\t\t\t# print the serial info\r\n\t\t\t\tprint 'Receiving data from '+k\r\n\t\t\t\t# initialize the data file\r\n\t\t\t\tdatfiles[k] = init_datafile(output_settings, payload[k])\r\n\t\t\t\t# read one line because the first one after opening a port is usually gibberish\r\n\t\t\t\tline = serials[k].readline()\r\n\t\t\telse: \r\n\t\t\t\tprint 'Unable to connect to serial port '+payload[k]['port']+' connected to '+k\r\n\t\t\t# pause get everything setup\r\n\t\t\ttime.sleep(1)\r\n\t\t# start the loop \r\n\t\tcontrol.combine()","async def get_api_data(self) -> dict:\n if not self.bos.is_set():\n self.lit = False\n return self.messages\n try:\n # get all data and split it up\n all_data = await self.send_api_cmd(\"devs+temps+fans\")\n devs_raw = all_data['devs'][0]\n temps_raw = all_data['temps'][0]\n fans_raw = all_data['fans'][0]\n\n # parse temperature data\n temps_data = {}\n for board in range(len(temps_raw['TEMPS'])):\n temps_data[f\"board_{temps_raw['TEMPS'][board]['ID']}\"] = {}\n temps_data[f\"board_{temps_raw['TEMPS'][board]['ID']}\"][\"Board\"] = temps_raw['TEMPS'][board]['Board']\n temps_data[f\"board_{temps_raw['TEMPS'][board]['ID']}\"][\"Chip\"] = temps_raw['TEMPS'][board]['Chip']\n\n # parse individual board and chip temperature data\n for board in temps_data.keys():\n if \"Board\" not in temps_data[board].keys():\n temps_data[board][\"Board\"] = 0\n if \"Chip\" not in temps_data[board].keys():\n temps_data[board][\"Chip\"] = 0\n\n # parse hashrate data\n hr_data = {}\n for board in range(len(devs_raw['DEVS'])):\n hr_data[f\"board_{devs_raw['DEVS'][board]['ID']}\"] = {}\n hr_data[f\"board_{devs_raw['DEVS'][board]['ID']}\"][\"HR\"] = round(\n devs_raw['DEVS'][board]['MHS 5s'] / 1000000,\n 2)\n\n # parse fan data\n fans_data = {}\n for fan in range(len(fans_raw['FANS'])):\n fans_data[f\"fan_{fans_raw['FANS'][fan]['ID']}\"] = {}\n fans_data[f\"fan_{fans_raw['FANS'][fan]['ID']}\"]['RPM'] = fans_raw['FANS'][fan]['RPM']\n\n # set the miner data\n miner_data = {'IP': self.ip, \"Light\": \"show\", 'Fans': fans_data, 'HR': hr_data, 'Temps': temps_data}\n\n # save stats for later\n self.stats = miner_data\n\n # return stats\n return miner_data\n except:\n # if it fails, return install data\n # usually fails on getting None from API\n self.lit = False\n data = self.messages\n data['Light'] = \"show\"\n return data","def run(self):\n\n if self.transport == 'any':\n devs = kromek.discover()\n else:\n devs = kromek.discover(self.transport)\n\n print('Discovered %s' % devs)\n\n if len(devs) <= 0:\n return\n\n filtered = []\n\n for dev in devs:\n if self.device == 'all' or dev[0] in self.device:\n filtered.append(dev)\n\n devs = filtered\n if len(devs) <= 0:\n return\n\n done_devices = set()\n try:\n while self.running:\n print(\"Plot_manager.run: getting data\")\n with kromek.Controller(devs, self.interval) as controller:\n for reading in controller.read():\n if self.create_structures:\n self.total = np.array(reading[4])\n self.lst = np.array([reading[4]])\n self.create_structures = False\n else:\n self.total += np.array(reading[4])\n self.lst = np.concatenate(\n (self.lst, [np.array(reading[4])]))\n serial = reading[0]\n dev_count = reading[1]\n if serial not in done_devices:\n this_start, this_end = self.get_interval(\n time.time() - self.interval)\n\n self.handle_spectra(\n this_start, this_end, reading[4])\n if dev_count >= self.count > 0:\n done_devices.add(serial)\n controller.stop_collector(serial)\n if len(done_devices) >= len(devs):\n break\n except KeyboardInterrupt:\n self.vprint(1, '\\nKeyboardInterrupt: stopping Manager run')\n self.takedown()\n except SystemExit:\n self.vprint(1, '\\nSystemExit: taking down Manager')\n self.takedown()","def receive_data(self):\n while True:\n\n data = self.recv_end()\n\n if len(data) > 0:\n\n try:\n self.current_data = json.loads(data)\n self.current_3D_points = base64.b64decode(self.current_data['points'])\n self.is_new_data = True\n\n except:\n # print('cannot load DepthCamera data')\n pass","def get_data(self):\n logging.info(\n \"[IEXIntervalDataSource] started: fetching every %d seconds\",\n self._interval,\n )\n\n def _get(self):\n data = self._iex_source(**self._iex_source_kwargs)\n if data:\n should_update = True\n if self._should_hash:\n hashed = str_to_float(json.dumps(data, sort_keys=True))\n should_update = hashed != self._last_hash\n if should_update:\n self._last_hash = hashed\n if should_update:\n if self._data_cleaner:\n data = self._data_cleaner(data)\n self.table.update(data)\n \n callback = tornado.ioloop.PeriodicCallback(callback=partial(_get, self), callback_time=self._interval)\n callback.start()","def log_data(self):\n\n assert self.tello is not None\n self.tello.subscribe(self.tello.EVENT_LOG_DATA, self.log_handler)\n self.tello.subscribe(self.tello.EVENT_FLIGHT_DATA, self.log_handler)\n self.tello.subscribe(self.tello.EVENT_FILE_RECEIVED, self.log_handler)","def update_live_data(n, last_time, id1, id2, power):\n if power:\n raise PreventUpdate\n\n timer_start = perf_counter()\n # 1 sec delay so server has time to add live data\n end_time = datetime.now(timezone.utc) - timedelta(seconds=1)\n\n # Initialization and lag prevention\n if last_time is None or end_time - strptime_fix(last_time) > timedelta(seconds=3):\n logging.warning('Falling behind! Start %s End %s', last_time, end_time)\n return dash.no_update, dash.no_update, end_time.isoformat(), dash.no_update\n\n # Query data from SMIP\n logging.info(f'start_time {last_time} end_time {end_time}')\n timer_query_start = perf_counter()\n r = conn.get_data(last_time, end_time.isoformat(),\n [id1, id2], timeout=1)\n timer_query_end = perf_counter()\n response_json: dict = r.json()\n logging.debug(response_json.keys())\n if 'errors' in response_json:\n logging.error(response_json)\n raise Exception()\n data = response_json['data']['getRawHistoryDataWithSampling']\n logging.info('Got %s responses in %s seconds', len(\n data), timer_query_end - timer_query_start)\n\n # Used for measuring performance\n start_processing = perf_counter()\n\n # Unpack data\n def unpack(id: int):\n \"\"\"Unpacks return data into time and value lists\"\"\"\n id = int(id)\n time_list = [i['ts'] for i in data if int(i['id']) == id]\n val_list = [i['floatvalue'] for i in data if int(i['id']) == id]\n # SMIP always returns one entry before the start time for each ID, we don't need this\n if len(time_list) < 2 or len(val_list) < 2:\n return dash.no_update\n time_list.pop(0)\n val_list.pop(0)\n # Measure sampling rate\n rate = nan\n if len(time_list) > 1:\n rate = (strptime_fix(time_list[1])\n - strptime_fix(time_list[0])).total_seconds()\n return {'time_list': time_list, 'val_list': val_list, 'rate': rate}\n\n # Used for measuring performance\n data_processed = perf_counter()\n logging.info('Total %s Query %s Processing %s', data_processed - timer_start, timer_query_end - timer_query_start,\n data_processed - start_processing)\n\n return unpack(id1), unpack(id2), end_time.isoformat(), \\\n [f'Last updated {end_time.astimezone()},',\n html.Br(),\n f'received {len(data)} samples in {round(data_processed - timer_start, 3)} seconds']","def on_timer(self):\n self.read_serial_data()\n # self.update_monitor()","def _after_connect(self):\r\n _debug('GUISignalGenerator: _after_connect()')\r\n # Update the controls\r\n self.button_sweep.enable()\r\n self.button_send_list.enable()\r\n self.button_reset.enable()\r\n \r\n # Update the RF button.\r\n rf_on = self.api.get_output()\r\n if rf_on == None: self.button_rf.set_checked(True, block_events=True).enable()\r\n else: self.button_rf.set_checked(rf_on, block_events=True).enable()\r\n \r\n # Update the combo; we block first just in case the value doesn't \"change\"\r\n if self.api == None: self.label_instrument_name.set_text('Simulation')\r\n else:\r\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\r\n else: self.combo_mode.set_value(1, block_events=True).enable()\r\n self._combo_mode_changed()\r\n \r\n # Update the list plot\r\n self.query_list()","def get_last_data(request):\n\n return_list = []\n if request.POST:\n try:\n conn = psycopg2.connect(dbname=DB_NAME,\n user=DB_USER,\n password=DB_PASSWORD,\n host=DB_HOST)\n cur = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)\n\n cur.execute(\"SELECT sn, time, icsmain, icsz1, icsz2, icsz3, icsboiler, t1, t2, t3, t4, t5, t6, t7,\"\n \"rt1, rt2, rt3, endswitch, weather FROM devicedata \"\n \"WHERE sn='BRANDON_SN_US' \"\n \"ORDER BY id DESC LIMIT 5\")\n\n get_device_data = cur.fetchall()\n\n cur.close()\n conn.close()\n\n for info in get_device_data:\n item_dict = {\"sn\": info[0], \"time\": str(info[1]), \"icsmain\": info[2], \"icsz1\": info[3], \"icsz2\": info[4],\n \"icsz3\": info[5], \"icsboiler\": info[6], \"t1\": info[7], \"t2\": info[8], \"t3\": info[9],\n \"t4\": info[10], \"t5\": info[11], \"t6\": info[12], \"t7\": info[13], \"rt1\": info[14], \"rt2\": info[15],\n \"rt3\": info[16], \"endswitch\": info[17]}\n return_list.append(item_dict)\n except:\n pass\n\n return JsonResponse(return_list, safe=False)","def handle_spectra(self, this_start, this_end, spectra):\n\n self.rt_plot.add_data(self.rt_plot.queue, spectra, self.maxspectra)\n\n if self.plot:\n\n '''\n Plot the data.\n '''\n self.plot_waterfall(1)\n self.plot_spectrum(2)\n # self.plot_fitter()\n\n '''\n Uncomment 3 lines below to plot the spectra fitter plots.\n '''\n else:\n self.data_handler.main(\n self.datalog, self.calibrationlog, spectra, this_start, this_end)","def data_received(self, data):\n self.log.debug('data_received: {!r}'.format(data))\n self._last_received = datetime.datetime.now()\n for byte in (bytes([value]) for value in data):\n\n try:\n self.stream.feed_byte(byte)\n except (ValueError, AssertionError):\n e_type, e_value, _ = sys.exc_info()\n map(self.log.warn,\n traceback.format_exception_only(e_type, e_value))\n continue\n\n if self.stream.is_oob:\n continue\n\n # self.reader.feed_byte()\n self.shell.feed_byte(byte)","def query_list(self):\r\n self.plot_list.clear()\r\n self.settings.send_to_databox_header(self.plot_list)\r\n \r\n self.label_list_status.set_text('Getting frequencies and powers.')\r\n self.window.process_events()\r\n \r\n fs = self.api.get_list_frequencies()\r\n ps = self.api.get_list_powers()\r\n if fs == None or ps == None: return\r\n \r\n if not len(fs) == len(ps):\r\n print(\"ERROR query_list(): List lengths do not match. len(fs)=\"+str(len(fs))+' len(ps)='+str(len(ps)) )\r\n \r\n N = len(fs)\r\n self.plot_list['n'] = _n.linspace(0, N-1, N)\r\n self.plot_list['f_Hz'] = fs\r\n self.plot_list['P_dBm'] = ps\r\n \r\n self.label_list_status.set_text(str(N) + ' points in list memory')\r\n self.plot_list.plot()\r\n self.button_send_list.disable()\r\n self.window.process_events()","def get_history():\n return response_texts_to_entries(make_post_request(HISTORY_API, data={\"k\": config[\"api_key\"]}))","def start(self):\n record_list_count = 0\n item_count = 0\n output_list = []\n record_in_range = False\n\n if not self.trim:\n print PROMPT + \"Getting Voltage readings that arrived at the server from device \" + \\\n self.name,\n if self.start_time is not None:\n print(\"after around UTC \" + date.strftime(self.start_time, \"%Y-%m-%d %H:%M\")),\n if self.end_time is not None:\n print(\"and before around UTC \" + date.strftime(self.end_time, \"%Y-%m-%d %H:%M\")),\n stdout.write('\\n')\n print PROMPT + \"V_BAT_OK, V_IN, V_PRIMARY (all in milliVolts)\"\n\n # Set some default start and end times if they are None\n if self.start_time is None:\n self.start_time = datetime.strptime('Jan 1 1970', '%b %d %Y').replace(tzinfo=utc)\n if self.end_time is None:\n self.end_time = datetime.strptime('Jan 1 2038', '%b %d %Y').replace(tzinfo=utc)\n\n # Create some dummy object IDs from the dates/times to use with PyMongo\n object_id_start_time = ObjectId.from_datetime(self.start_time)\n object_id_end_time = ObjectId.from_datetime(self.end_time)\n\n # Retrieve all the records that match the given name in the order they were created\n record_list = self.collection.find({\"n\": self.name, \\\n \"_id\": {\"$gte\": object_id_start_time, \\\n \"$lte\": object_id_end_time}}). \\\n sort([[\"_id\", 1]])\n for record in record_list:\n record_in_range = record[\"_id\"].generation_time > self.start_time\n if record_in_range:\n record_list_count += 1\n # Find the index in the record, just to be sure it's a record\n if \"i\" in record:\n # Find the report items in the record\n if \"r\" in record:\n r_list = record[\"r\"]\n # Go through the list\n for r_item in r_list:\n # See if there's a voltages item in it\n if \"vlt\" in r_item:\n voltages_item = r_item[\"vlt\"]\n item_count += 1\n # Decode the voltages and add them to our list\n voltages_struct = self.get_voltages_item(voltages_item)\n output_list.append(voltages_struct)\n # Having got everything, sort it in time order\n output_list.sort(key=sort_func)\n # Now print it\n for item in output_list:\n time_string = datetime.utcfromtimestamp(item.timestamp) \\\n .strftime(\"%Y-%m-%d_%H:%M:%S\")\n print(\"%s %d %d %d\" % (time_string, item.v_bat_ok_mv,\n item.v_in_mv, item.v_primary_mv))\n if not self.trim:\n print(PROMPT + \"%r record(s) returned containing %r voltage reading(s)\"\n % (record_list_count, item_count))","def slot_history_changed(self, _sender, _data):\r\n last_candle = self.history.last_candle()\r\n if last_candle:\r\n self.client.history_last_candle = last_candle.tim","def __flight_data_handler(self, event, sender, data):\n self.battery = data.battery_percentage\n self.fly_mode = data.fly_mode\n self.throw_fly_timer = data.throw_fly_timer\n self.throw_ongoing = data.throw_fly_timer > 0\n\n if self.prev_flight_data != str(data):\n print(data)\n self.prev_flight_data = str(data)\n self.flight_data = data\n\n if self.is_flying != data.em_sky:\n self.is_flying = data.em_sky\n log.debug(f\"FLYING : {self.is_flying}\")\n if not self.is_flying:\n self.reset()\n else:\n if self.tracking_after_takeoff:\n log.info(\"Tracking on after takeoff\")\n self.toggle_tracking(True)\n\n # if self.write_header_log:\n # self.write_header_log = False\n # self.log_file_log.write(f\"{data.format_cvs_header()}\\n\")\n # self.log_file_log.write(f\"{data.format_cvs(0)}\\n\")","def get_data(self):\n return self.read_sample_win()","def listen(self):\n\n if not self.key_data:\n self.key_data = {}\n for i in range(1024):\n self.key_data[i] = False\n\n if not self.axis_data:\n self.axis_data = {}\n for i in range(self.controller.get_numaxes()):\n self.axis_data[i] = 0.0\n\n if not self.button_data:\n self.button_data = {}\n for i in range(self.controller.get_numbuttons()):\n self.button_data[i] = False\n\n if not self.hat_data:\n self.hat_data = {}\n for i in range(self.controller.get_numhats()):\n self.hat_data[i] = (0, 0)\n\n debug_toggle = True\n print_state_toggle = True\n\n # These parameters define how frequesnt speed setting sent over serial to arduino\n speed_threshold = 10.0 # sets update threshold\n speed_step = 1 # sets acceleration\n speed_delay = 0.01 # delay per 1 step in sec\n\n mode_switch = \"j\" # control mode: k - keyboard, j - joystick\n\n # Parameters for keyboard control mode\n speed = 0.0\n speed_current = 0\n direction = \"r\" # r - release, f - forward, b - backward\n direction_current = \"r\"\n\n # Parameters for joystick control mode\n speed_l = 0\n speed_r = 0\n prev_speed_l = 0\n prev_speed_r = 0\n prev_btn = False\n\n while True:\n prev = self.axis_data\n for event in pygame.event.get():\n if event.type == pygame.KEYDOWN:\n self.key_data[event.key] = True\n elif event.type == pygame.KEYUP:\n self.key_data[event.key] = False\n if event.type == pygame.JOYAXISMOTION:\n self.axis_data[event.axis] = round(event.value,2)\n elif event.type == pygame.JOYBUTTONDOWN:\n self.button_data[event.button] = True\n elif event.type == pygame.JOYBUTTONUP:\n self.button_data[event.button] = False\n elif event.type == pygame.JOYHATMOTION:\n self.hat_data[event.hat] = event.value\n\n # check for exit command\n if self.button_data[9] or self.key_data[pygame.QUIT] or self.key_data[pygame.K_ESCAPE]:\n pygame.quit()\n break\n\n # toggle debug\n if self.key_data[pygame.K_d]:\n if debug_toggle:\n print(\"Toggle debug\")\n self.ser.write(b'd')\n debug_toggle = False\n else:\n debug_toggle = True\n\n # print out motors status\n if self.key_data[pygame.K_p]:\n if print_state_toggle:\n self.ser.write(b'p')\n if self.ser.in_waiting:\n print (self.ser.readline())\n print_state_toggle = False\n else:\n print_state_toggle = True\n\n if self.key_data[pygame.K_1] and mode_switch != \"k\":\n mode_switch = \"k\"\n\n if self.key_data[pygame.K_2] and mode_switch != \"j\":\n print(\"Joystick mode: ON\")\n mode_switch = \"j\"\n\n if mode_switch == \"k\": # keyboard control mode\n # accelearte forward\n if self.key_data[pygame.K_a] and direction != \"r\":\n if speed < 255.0:\n speed = speed + speed_step\n sleep(speed_delay)\n # accelerate backward\n if self.key_data[pygame.K_z] and direction != \"r\":\n if speed > 0.0:\n speed = speed - speed_step\n sleep(speed_delay)\n\n if self.key_data[pygame.K_UP] and direction != \"f\":\n direction = \"f\"\n if self.key_data[pygame.K_DOWN] and direction != \"b\":\n direction = \"b\"\n if self.key_data[pygame.K_UP] == False and direction == \"f\":\n direction = \"r\"\n if self.key_data[pygame.K_DOWN] == False and direction == \"b\":\n direction = \"r\"\n\n if math.fabs(speed - speed_current) > speed_threshold or direction != direction_current:\n # print(\"{0}, {1}, {2}, {3}\".format(speed, speed_current, direction, direction_current))\n direction_current = direction\n if direction == \"r\":\n speed = 0.0\n speed_current = int(speed)\n str_r = \"sr\" + direction_current + str(speed_current) + \"e\"\n str_l = \"sl\" + direction_current + str(speed_current) + \"e\"\n print(str_l)\n print(str_r)\n self.ser.write(str_r.encode())\n self.ser.write(str_l.encode())\n\n if(self.key_data[pygame.K_LEFT]):\n str_rf = \"srf\" + str(speed_current) + \"e\"\n self.ser.write(str_rf.encode())\n str_lf = \"slf\" + str(int(speed_current*0.9)) + \"e\"\n self.ser.write(str_lf.encode())\n elif(self.key_data[pygame.K_RIGHT]):\n str_rb = \"srf\" + str(int(speed_current*0.9)) + \"e\"\n self.ser.write(str_rb.encode())\n str_lb = \"slf\" + str(speed_current) + \"e\"\n self.ser.write(str_lb.encode())\n\n if (self.key_data[pygame.K_UP] == False and self.key_data[pygame.K_DOWN] == False) and (self.key_data[pygame.K_a] == False and self.key_data[pygame.K_z] == False):\n speed = 0\n speed_current = speed\n direction = \"r\"\n direction_current = direction\n self.ser.write(b'srze')\n self.ser.write(b'slze')\n\n if mode_switch == \"j\": # joystick control mode\n if self.ser.in_waiting:\n data = str(self.ser.readline().strip())\n data = data[2 :len(data)-1]\n print(data)\n #self.aio.send('Team Hacky Slackers', data)\n\n prev_speed_l = speed_l\n prev_speed_r = speed_r\n speed_threshold = 1\n\n #simplified linear mapping for controller\n speed_l = int((self.axis_data[0]*(-50)) + 90)\n speed_r = int(math.fabs(self.axis_data[3]*255))\n #print(self.axis_data)\n #print(\"curr_l: {0}, perv_l: {1}, curr_r:{2}, perv_r:{3}\".format(speed_l, prev_speed_l, speed_r,prev_speed_r))\n\n if self.axis_data[0] < -0.05 and math.fabs(speed_l - prev_speed_l) > speed_threshold:\n str_lf = \"slf\" + str(speed_l) + \"e\"\n self.ser.write(str_lf.encode())\n elif self.axis_data[0] > 0.05 and math.fabs(speed_l - prev_speed_l) > speed_threshold:\n str_lb = \"slb\" + str(speed_l) + \"e\"\n self.ser.write(str_lb.encode())\n\n\n if self.axis_data[3] < -0.03 and math.fabs(speed_r - prev_speed_r) > speed_threshold:\n str_rf = \"srf\" + str(speed_r) + \"e\"\n self.ser.write(str_rf.encode())\n elif self.axis_data[3] > 0.03 and math.fabs(speed_r - prev_speed_r) > speed_threshold:\n str_rb = \"srb\" + str(speed_r) + \"e\"\n self.ser.write(str_rb.encode())\n\n if ( self.axis_data[0] >= -0.05 and self.axis_data[0] <= 0.05 ) and ( self.axis_data[3] >= -0.05 and self.axis_data[3] <= 0.05 ):\n speed_l = 90\n speed_r = 0\n self.ser.write(b'srze')\n self.ser.write(b'slze')\n\n #Logic to call RFID scan only once per click of R1 button\n # if(prev_btn != self.button_data[5]):\n # prev_btn = self.button_data[5]\n # if self.button_data[5] :\n # print(\"Scanning for RFID Card\")\n # self.ser.write(\"i\".encode())\n\n # clear()\n # pprint.pprint(self.button_data)\n # pprint.pprint(self.axis_data)\n # pprint.pprint(self.hat_data)","def receive_data():\n\n while True:\n try:\n bytes_to_read = ser.readline()\n print(bytes_to_read)\n data = json.loads(bytes_to_read.decode('utf-8'))\n distance = data['distance']\n print(f'distance: {distance}')\n except Exception as e:\n print(f'Error in reading bytes from the \\'duino: {e}')","def sendPreviousDataPoints(self):\n if self.ioLoopInst is not None:\n cmd = {'cmd': 'setDataPoints', 'value': self.dataPoints}\n self._sendMessageToWeb(cmd)\n else:\n print(\"sendPreviousDataPoints: \" + self.dataPoints)"],"string":"[\n \"def recive_data(self):\\n # read all available data\\n while self.ser.inWaiting() > self.INPUT_DATA_SIZE+1:\\n data = array.array('c')\\n # search the header\\n data.append(self.ser.read(1))\\n while data[0] != chr(1):\\n data[0] = self.ser.read(1)\\n \\n # wait for all available data\\n while self.ser.inWaiting() < (self.INPUT_DATA_SIZE-1):\\n time.sleep(0.03);\\n \\n # recives data\\n data = self.ser.read(self.INPUT_DATA_SIZE-1)\\n \\n # prove if you want graphical data\\n if self.pushButton_monitor.isChecked():\\n # decodes the data\\n t = struct.unpack('I', data[3]+data[2]+data[1]+data[0])\\n r = struct.unpack('f', data[4]+data[5]+data[6]+data[7])\\n x0 = struct.unpack('f', data[8]+data[9]+data[10]+data[11])\\n x1 = struct.unpack('f', data[12]+data[13]+data[14]+data[15])\\n u = struct.unpack('f', data[16]+data[17]+data[18]+data[19])\\n \\n self.time = t[0]*25e-9\\n \\n # prepare the string output\\n aux_str = \\\" t = \\\"+str(self.time)+\\\"\\\\t\\\"\\n aux_str += \\\" r = \\\"+str(r[0])+\\\"\\\\t\\\"\\n aux_str += \\\" u = \\\"+str(u[0])+\\\"\\\\t\\\"\\n aux_str += \\\" x1 = \\\"+str(x1[0])+\\\"\\\\t\\\"\\n aux_str += \\\" x0 = \\\"+str(x0[0])+\\\"\\\\n\\\"\\n # print string output\\n self.textBrowser.insertPlainText(aux_str)\\n \\n # append data to the arrays\\n self.graf_t.append(self.time)\\n self.graf_r.append(r[0])\\n self.graf_x0.append(x0[0])\\n self.graf_x1.append(x1[0])\\n self.graf_u.append(u[0])\\n \\n # remove one value if the arrays have maximum length\\n if self.graf_t.buffer_info()[1] >= NUM_SAMPLES:\\n self.graf_t.pop(0)\\n self.graf_r.pop(0)\\n self.graf_x0.pop(0)\\n self.graf_x1.pop(0)\\n self.graf_u.pop(0)\\n \\n # reload number of samples lavel\\n self.label_samples_value.setText(str(self.graf_t.buffer_info()[1]))\\n # reload number of waiting chars in serial rx buffer\\n self.label_rx_buff_value.setText(str(self.ser.inWaiting()))\\n\\n # reload mutex area\\n self.updated_data = 1\\n \\n # prove if there are available id's\\n if (self.actionPC_Monitor.isChecked() and data[20] == chr(2)):\\n # if it is true, looks how much id's\\n i = struct.unpack('B', data[21])\\n\\n if i[0] < STACK_SIZE:\\n for z in range(i[0]):\\n new_device = struct.unpack('B', data[z+22])\\n new_string = str(new_device[0])\\n \\n llista = self.listWidget_link.findItems(new_string, QtCore.Qt.MatchExactly)\\n if len(llista) == 0:\\n self.listWidget_link.addItem(new_string)\",\n \"def run(self):\\n while(not self.stop_event.is_set()):\\n # read values until stop is sent\\n response1 = _read_once(1,self.serial)\\n response2 = _read_once(2,self.serial)\\n #print(response)\\n self.data1[\\\"d\\\"].append(response1) # Push response to the data list for later\\n self.data2[\\\"d\\\"].append(response2) # Push response to the data list for later\\n curTime = time.time()\\n self.data1[\\\"t\\\"].append(curTime)\\n self.data2[\\\"t\\\"].append(curTime)\\n #sleep(0.0001) # I need to be small enough to capture peaks.\\n return\",\n \"def record_data(self, no_of_samples, interval):\\r\\n\\r\\n #tempory storage while function is completing\\r\\n temp_return_list = []\\r\\n\\r\\n #colec\\r\\n for i in range(0,no_of_samples):\\r\\n\\r\\n print(i)\\r\\n sensor_value = self.sen.get_sensor_value()\\r\\n\\r\\n temp_return_list.append([sensor_value,(i*interval)])\\r\\n\\r\\n time.sleep(interval)\\r\\n\\r\\n \\r\\n \\r\\n self.return_data = temp_return_list\",\n \"def gather_data(self, *args, **kwargs):\\n instrument_arg = kwargs.get('instrument', 'EUR_USD')\\n granularity_arg = kwargs.get('granularity', 'M1')\\n candle_format = kwargs.get('candleFormat', 'bidask')\\n start_time = kwargs.get('start', '2014-10-01T00:00:00.000000Z')\\n count_arg = kwargs.get('count', 5000)\\n out_data = []\\n data_complete = False\\n while(not data_complete):\\n response = self.oanda.get_history(instrument=instrument_arg,\\n granularity=granularity_arg,\\n candleFormat=candle_format,\\n start=start_time,\\n count=count_arg)\\n raw_data = response['candles']\\n if (len(out_data) == 0):\\n out_data = out_data + raw_data\\n elif (len(out_data) > 1):\\n # raw_data[0] is already in out_data as raw_data[-1] from last\\n # iteration\\n out_data = out_data + raw_data[1:]\\n start_time = raw_data[-1]['time']\\n if (len(raw_data) < 5000):\\n data_complete = True\\n\\n out_data = self._list_to_df(out_data)\\n return out_data\",\n \"def result(self):\\n\\n chart_series = [] # will hold all the series created\\n\\n # determine the sensor to plot from the sensor selected by the user.\\n the_sensor = bmsapp.models.Sensor.objects.get(pk=self.request_params['select_sensor'])\\n\\n # get the requested averaging interval in hours\\n averaging_hours = float(self.request_params['averaging_time'])\\n\\n # determine the start time for selecting records\\n st_ts, end_ts = self.get_ts_range()\\n\\n # get the database records\\n df = self.reading_db.dataframeForOneID(the_sensor.sensor_id, st_ts, end_ts, pytz.timezone(self.timezone))\\n\\n if not df.empty:\\n\\n # info needed to create each series (selection list, series name, visible)\\n if self.schedule:\\n occupied_times = df.ts.apply(self.schedule.is_occupied)\\n unoccupied_times = -occupied_times\\n\\n series_info = [(None, 'All Data', True),\\n (occupied_times, 'Occupied Periods', False),\\n (unoccupied_times, 'Unoccupied Periods', False)]\\n else:\\n # no schedule, so just return the 'All Data' series\\n series_info = [(None, 'All Data', True)]\\n\\n for mask, series_name, visibility in series_info:\\n if mask is None:\\n select_df = df\\n else:\\n select_df = df[mask]\\n\\n if averaging_hours:\\n select_df = bmsapp.data_util.resample_timeseries(select_df, averaging_hours)\\n\\n histogram_series = bmsapp.data_util.histogram_from_series(select_df.val)\\n\\n chart_series.append({'x': [x for x,y in histogram_series],\\n 'y': [y for x,y in histogram_series],\\n 'type': 'scatter',\\n 'mode': 'lines', \\n 'name': series_name, \\n 'visible': 'true' if visibility else 'legendonly'\\n })\\n\\n opt = self.get_chart_options('plotly')\\n opt['data'] = chart_series\\n opt['layout']['title'] = the_sensor.title + ' Histogram: ' + self.building.title\\n opt['layout']['xaxis']['title'] = the_sensor.unit.label\\n opt['layout']['xaxis']['type'] = 'linear'\\n opt['layout']['yaxis']['title'] = '% of Readings'\\n opt['layout']['yaxis']['rangemode'] = 'tozero'\\n\\n html = basechart.chart_config.chart_container_html(opt['layout']['title'])\\n\\n return {'html': html, 'objects': [('plotly', opt)]}\",\n \"def processData(self):\\n recordSet = AresChartsService.toMultiSeries(self.vals, self.chartKeys, self.selectedX , self.chartVals, extKeys=self.extKeys)\\n self.aresObj.jsGlobal.add(\\\"data_%s = %s\\\" % (self.htmlId, json.dumps(recordSet)))\",\n \"def get_all(self):\\n try:\\n return self.current_data\\n except:\\n print('No data received from sensor')\",\n \"def reqData(self):\\r\\n #self.reqGlobalCancel()\\r\\n #self.add_historical(\\\"Stock('TSLA', 'SMART', 'USD')\\\")\\r\\n #self.add_historical(\\\"Stock('IBM', 'SMART', 'USD')\\\")\\r\\n #self.add_historical(\\\"Stock('MSFT', 'SMART', 'USD')\\\")\\r\\n self.add_historical(\\\"Stock('FB', 'SMART', 'USD')\\\")\",\n \"async def request_data(\\r\\n self,\\r\\n **kwargs, # pylint: disable=unused-argument\\r\\n ) -> None:\\r\\n await self._send(\\\"report 2\\\")\\r\\n\\r\\n if self.device_info.is_meter_integrated():\\r\\n await self._send(\\\"report 3\\\")\\r\\n\\r\\n if self.device_info.is_data_logger_integrated():\\r\\n await self._send(\\\"report 100\\\")\",\n \"def automatic_meter_reading_demo():\\n\\n\\t#Get sensor data from ellitrack\\n\\tserial = 17112915\\n\\n\\t#get period dates\\n\\tfirst_day_of_the_month = datetime.datetime.today().replace(day=1)\\n\\tyesterday = datetime.datetime.now().date() - datetime.timedelta(days=1)\\n\\t#seven_days_earlier = yesterday - datetime.timedelta(days=7)\\n\\n\\tperiod_from = yesterday.strftime(\\\"%d-%m-%Y\\\")\\n\\tperiod_from = period_from + ' +00:00:00'\\n\\tperiod_to = yesterday.strftime(\\\"%d-%m-%Y\\\")\\n\\tperiod_to = period_to + \\\" +23:59:59\\\"\\n\\n\\t#print(period_from, period_to)\\n\\n\\t#initialize request session\\n\\tlogin_url = \\\"http://www.ellitrack.nl/auth/login/\\\"\\n\\n\\t#authenticate session\\n\\tellitrack_session = requests.Session()\\n\\tellitrack_session.post(login_url, data={'username': \\\"markdeblois\\\", 'password': \\\"upandegani\\\"})\\n\\n\\t#get data for pure fresh ellitrack\\n\\tdata_url = \\\"http://www.ellitrack.nl/measurement/downloadexport/serialnumber/%s/type/period/n/0\\\" \\\\\\n \\\"/periodtype/date/periodfrom/%s/periodto/%s/format/json\\\" % (serial, period_from, period_to)\\n\\tresp = ellitrack_session.get(data_url)\\n\\n\\tif resp.status_code == 200:\\n\\t\\toutput = StringIO(resp.text)\\n\\t\\tell_df = pandas.read_csv(output, sep=\\\"\\\\t\\\")\\n\\n\\t\\t#unnecessary columns removed\\n\\t\\tell_df_stripped = ell_df[ell_df.columns[0:2]]\\n\\n\\t\\t#get prev and curr readings\\n\\t\\tprev_reading = ell_df_stripped['1 Energie'].min()\\n\\t\\tcurr_reading = ell_df_stripped['1 Energie'].max()\\n\\n\\t\\t#Insert data into Meter Reading Sheet Doctype\\n\\t\\tdata = {\\n\\t\\t\\t\\\"doctype\\\": \\\"Meter Reading Capture\\\",\\n\\t\\t\\t\\\"reading_date\\\": first_day_of_the_month,\\n\\t\\t}\\n\\t\\t\\n\\t\\t#billing month\\n\\t\\tget_curr_month = first_day_of_the_month.strftime(\\\"%B\\\")\\n\\n\\t\\tautomatic_readings_data = {\\n\\t\\t\\t\\t\\\"doctype\\\": \\\"Meter Reading Sheet\\\",\\n\\t\\t\\t\\t\\\"automatic_meter_id\\\": \\\"%s\\\" %serial,\\n\\t\\t\\t\\t\\\"previous_automatic_readings\\\": \\\"%s\\\" %prev_reading,\\n\\t\\t\\t\\t\\\"current_automatic_readings\\\": \\\"%s\\\" %curr_reading,\\n\\t\\t\\t\\t\\\"parent\\\": \\\"All Territories %s 2018\\\" %get_curr_month,\\n\\t\\t\\t\\t\\\"parenttype\\\": \\\"Meter Reading Capture\\\",\\n\\t\\t\\t\\t\\\"parentfield\\\": \\\"meter_reading_sheet\\\"\\n\\t\\t\\t}\\n\\n\\t\\t#check if doc exists\\n\\t\\tname = \\\"All Territories \\\"+get_curr_month+\\\" 2018\\\"\\n\\t\\tdoc_list = frappe.get_list(\\\"Meter Reading Capture\\\", filters={'name':name})\\n\\t\\tif doc_list:\\n\\t\\t\\tmdoc = frappe.get_doc(\\\"Meter Reading Capture\\\", name)\\n\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tmrs_doc = frappe.get_doc(automatic_readings_data)\\n\\t\\t\\t\\tmrs_doc.insert()\\n\\t\\t\\t\\tfrappe.db.commit()\\n\\t\\t\\texcept Exception as err:\\n\\t\\t\\t\\treturn err\\n\\t\\telse:\\n\\t\\t\\t#create new doc\\n\\t\\t\\tdoc = frappe.new_doc(\\\"Meter Reading Capture\\\")\\n\\t\\t\\tdoc.reading_date = first_day_of_the_month\\n\\t\\t\\tdoc.billing_period = get_curr_month+\\\" 2018\\\"\\n\\t\\t\\tdoc.route = \\\"All Territories\\\"\\n\\t\\t\\tdoc.route_and_billing_period = name\\n\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tdoc.insert()\\n\\t\\t\\t\\tfrappe.db.commit()\\n\\t\\t\\texcept Exception as err:\\n\\t\\t\\t\\treturn err\\n\\n\\t\\t\\ttry:\\n\\t\\t\\t\\t#update doc with the meter readings\\n\\t\\t\\t\\tmrs_doc = frappe.get_doc(automatic_readings_data)\\n\\t\\t\\t\\tmrs_doc.insert()\\n\\t\\t\\t\\tfrappe.db.commit()\\n\\t\\t\\texcept Exception as err:\\n\\t\\t\\t\\treturn err\",\n \"def read(self):\\n # return previous data if read() was already called less than 1 second ago\\n time_since_last_read = (\\n time.time_ns()*self.NS_TO_MS - self.query_time) * self.MS_TO_SEC\\n if time_since_last_read < 1:\\n return self.readings\\n\\n data_bytes = self.sensor.readline()\\n data = data_bytes.decode('utf-8')\\n\\n # extract wind direction (deg) data\\n min_direction = float(data[7:10])\\n avg_direction = float(data[15:18])\\n max_direction = float(data[23:26])\\n\\n # extract wind speed (m/s) data\\n min_speed = float(data[31:34])\\n avg_speed = float(data[39:42])\\n max_speed = float(data[47:50])\\n\\n self.readings = [\\n {\\n \\\"type\\\": \\\"windDirection\\\",\\n \\\"value\\\": {\\n \\\"minDirection\\\": min_direction,\\n \\\"avgDirection\\\": avg_direction,\\n \\\"maxDirection\\\": max_direction\\n }\\n },\\n {\\n \\\"type\\\": \\\"windSpeed\\\",\\n \\\"value\\\": {\\n \\\"minSpeed\\\": min_speed,\\n \\\"avgSpeed\\\": avg_speed,\\n \\\"maxSpeed\\\": max_speed\\n }\\n }\\n ]\\n\\n # update the last time of read() being called\\n self.query_time = time.time_ns() * self.NS_TO_MS\\n\\n return self.readings\",\n \"def get_data(self):\\n try:\\n data_string = self.ser.readline().decode()\\n except UnicodeDecodeError as e:\\n return self.get_data()\\n \\n if not data_string: # check for empty string\\n return self.get_data()\\n \\n if data_string[0] == '|' and data_string[-1] == '\\\\n' and\\\\\\n self.reset_confirmed:\\n # if the data_string is valid, process it\\n try:\\n data_string = data_string.strip() \\n data = data_string.split(',')\\n assert len(data) == 7, \\\"Bad data Length\\\" \\n data = [float(val) for val in data[1:]]\\n data[0] /= 1000\\n if self.ser.in_waiting: self.ser.reset_input_buffer()\\n return data\\n except (AssertionError, ValueError) as e:\\n print(\\\"Error:\\\", type(e), e)\\n if self.ser.in_waiting: self.ser.reset_input_buffer()\\n return self.get_data()\\n\\n\\n elif data_string[0] == '+' and data_string[-1] == '\\\\n' and\\\\\\n self.reset_confirmed:\\n # if the data_string is a valid time stamp, process it\\n # self.system_timestamp = \\\"\\\\nSystem start time is: \\\"\\\\\\n # \\\"%s\\\" % strftime(\\\"%Y/%m/%d %H:%M:%S\\\", localtime())\\n self.arduino_timestamp = data_string.strip()\\n print(self.arduino_timestamp)\\n return self.get_data()\\n \\n elif data_string[0] == '/' and data_string[-1] == '\\\\n':\\n # if string begins with / then it is a debug message and should\\n # just be returned\\n if \\\"setup finished\\\" in data_string.lower(): \\n self.reset_confirmed = True\\n print(data_string.strip())\\n return self.get_data()\\n else:\\n # if the data_string is invalid try again\\n return self.get_data()\",\n \"def stremingData(self):\\n ports = com_select()\\n self.comport = None\\n if not ports:\\n QMessageBox.warning(self, 'No Connection',\\n \\\"No unit found please verify that the IMU is connected\\\")\\n else:\\n for port in ports:\\n if test_con(port):\\n self.comport = port\\n break\\n if self.comport:\\n if self.ui.qtBStream.text() == 'Stream':\\n self.ui.qtBStream.setText('Stop')\\n self.streamData = GetValue(self.comport)\\n self.streamData.start()\\n iter(self.streamData)\\n self.timer = QTimer()\\n self.timer.timeout.connect(self.graphupdate)\\n self.i = 0\\n self.__x = []\\n if self.recF:\\n if self.ui.qtBrowse.text() == '':\\n self.file_select()\\n if self.ui.qtBrowse.text() == '':\\n QMessageBox.warning(self,\\n 'No file',\\n 'No file selected')\\n self.stremingData()\\n return 0\\n self.timer.start()\\n elif self.ui.qtBStream.text() == 'Stop':\\n self.ui.qtBStream.setText('Stream')\\n self.timer.stop()\\n self.streamData.stop()\\n self.data = [[] for i in range(8)]\\n else:\\n QMessageBox.warning(self, 'No Connection com search',\\n \\\"No unit found please verify that the IMU is connected\\\")\",\n \"def readOneData(self):\\n\\n\\t\\tif self._mt5Client is not None:\\n\\t\\t\\tdatas = self._mt5Client.getData()\\n\\n\\t\\t\\tif datas is not None:\\n\\t\\t\\t\\tPERIOD = int(self._config['data']['predict'])\\n\\t\\t\\t\\tHALF_PERIOD = int(PERIOD/2)\\n\\n\\t\\t\\t\\tdata = []\\n\\n\\t\\t\\t\\t#Time Got\\n\\t\\t\\t\\tself._LAST_PERIOD_PREDICTED_END = datas['time']\\n\\n\\t\\t\\t\\t#time open high low close tick_volume spread real_\\n\\t\\t\\t\\t#Switch the price type calucation\\n\\n\\t\\t\\t\\tw_p = self._config['data']['price']\\n\\t\\t\\t\\tv = 0\\n\\n\\t\\t\\t\\tif(w_p == CHART_PRICES_TYPE['O']):\\n\\t\\t\\t\\t\\tv = float(datas['open']) \\n\\n\\t\\t\\t\\telif(w_p == CHART_PRICES_TYPE['C']):\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tv = float(datas['close']) \\n\\n\\t\\t\\t\\telif(w_p == CHART_PRICES_TYPE['H']):\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tv = float(datas['high'])\\n\\n\\t\\t\\t\\telif(w_p == CHART_PRICES_TYPE['L']):\\n\\n\\t\\t\\t\\t\\tv = float(datas['low']) \\n\\n\\t\\t\\t\\telif(w_p == CHART_PRICES_TYPE['HL/2']):\\n\\t\\t\\t\\t\\tv = ( float(datas['low']) + float(datas['high']) ) /2\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tself.notify(msg={\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t'prices': {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t'values': {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t'RP': str(v)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t)\\n\\n\\t\\t\\t\\tdata.append(100000 * v ) \\n\\n\\t\\t\\t\\tself._TEMPORARY_GLOBAL_DATA.append(data[-1])\\n\\n\\t\\t\\t\\tself._GLOBAL_DATA.append(data[-1])\\n\\n\\t\\t\\t\\treturn data\",\n \"def data_process():\\n global localtime\\n global value_dict\\n sensor_types = sEtting.sensor_types\\n sensor_values = []\\n msg = None\\n value_dict = collections.OrderedDict.fromkeys(sEtting.payload_header)\\n value_dict[\\\"ver_format\\\"] = sEtting.ver_format\\n value_dict[\\\"FAKE_GPS\\\"] = sEtting.fake_gps\\n value_dict[\\\"app\\\"] = sEtting.app\\n value_dict[\\\"ver_app\\\"] = sEtting.ver_app\\n value_dict[\\\"device_id\\\"] = sEtting.device_id\\n value_dict[\\\"date\\\"] = localtime.strftime(\\\"%Y-%m-%d\\\")\\n value_dict[\\\"time\\\"] = localtime.strftime(\\\"%H:%M:%S\\\")\\n value_dict[\\\"device\\\"] = sEtting.device\\n\\n for sensor in sensor_types:\\n if sensor == 'pm25-at':\\n value_dict[\\\"s_d0\\\"] = get_reading_csv(sensor)\\n elif sensor == 'temperature':\\n value_dict[\\\"s_t0\\\"] = get_reading_csv(sensor)\\n elif sensor == 'humidity':\\n value_dict[\\\"s_h0\\\"] = get_reading_csv(sensor)\\n elif sensor == 'pm10-at':\\n value_dict[\\\"s_d1\\\"] = get_reading_csv(sensor)\\n else:\\n print 'Not support sensor type.'\\n if sEtting.fake_gps == 1:\\n value_dict[\\\"gps_lat\\\"] = sEtting.fgps_lat\\n value_dict[\\\"gps_lon\\\"] = sEtting.fgps_lon\\n value_dict[\\\"gps_alt\\\"] = sEtting.fgps_alt\\n value_dict[\\\"gps_fix\\\"] = 0\\n else:\\n value_dict[\\\"gps_lat\\\"] = get_gps()[0]\\n value_dict[\\\"gps_lon\\\"] = get_gps()[1]\\n value_dict[\\\"gps_alt\\\"] = get_gps()[2]\\n value_dict[\\\"gps_fix\\\"] = gpsd.fix.mode\\n value_dict[\\\"gps_num\\\"] = 0\\n #if debug_enable == '0':\\n msg = \\\"|\\\" + \\\"|\\\".join([\\\"=\\\".join([key, str(val)])\\n for key, val in value_dict.items()])\\n return msg\\n #elif debug_enable == '1':\\n # msg_debug = \\\",\\\".join([\\\"=\\\".join([key, str(val)]) for key, val in value_dict.items()])\\n # return msg_debug\",\n \"def recive_data(self, data_waveformreceived):\\r\\n self.adcollector.save_as_binary(self.savedirectory)\\r\\n self.channel_number = len(data_waveformreceived)\\r\\n if self.channel_number == 1: \\r\\n if 'Vp' in self.readinchan:\\r\\n self.data_collected_0 = data_waveformreceived[0]\\r\\n \\r\\n self.PlotDataItem_patch_voltage = PlotDataItem(self.xlabelhere_all, self.data_collected_0)\\r\\n #use the same color as before, taking advantages of employing same keys in dictionary\\r\\n self.PlotDataItem_patch_voltage.setPen('w')\\r\\n self.pw_data.addItem(self.PlotDataItem_patch_voltage)\\r\\n \\r\\n self.textitem_patch_voltage = pg.TextItem(('Vp'), color=('w'), anchor=(1, 1))\\r\\n self.textitem_patch_voltage.setPos(0, 1)\\r\\n self.pw_data.addItem(self.textitem_patch_voltage)\\r\\n elif 'Ip' in self.readinchan:\\r\\n self.data_collected_0 = data_waveformreceived[0]\\r\\n \\r\\n self.PlotDataItem_patch_current = PlotDataItem(self.xlabelhere_all, self.data_collected_0)\\r\\n #use the same color as before, taking advantages of employing same keys in dictionary\\r\\n self.PlotDataItem_patch_current.setPen('c')\\r\\n self.pw_data.addItem(self.PlotDataItem_patch_current)\\r\\n \\r\\n self.textitem_patch_current = pg.TextItem(('Ip'), color=('w'), anchor=(1, 1))\\r\\n self.textitem_patch_current.setPos(0, 1)\\r\\n self.pw_data.addItem(self.textitem_patch_current) \\r\\n elif 'PMT' in self.readinchan: # repeatnum, PMT_data_index_array, averagenum, ScanArrayXnum\\r\\n self.data_collected_0 = data_waveformreceived[0]*-1\\r\\n self.data_collected_0 = self.data_collected_0[0:len(self.data_collected_0)-1]\\r\\n \\r\\n # pmt data could come from raster scanning mode or from contour scanning mode.\\r\\n try:\\r\\n for i in range(self.repeatnum):\\r\\n self.PMT_image_reconstructed_array = self.data_collected_0[np.where(self.PMT_data_index_array_repeated == i+1)]\\r\\n Dataholder_average = np.mean(self.PMT_image_reconstructed_array.reshape(self.averagenum, -1), axis=0)\\r\\n Value_yPixels = int(len(self.samples_1)/self.ScanArrayXnum)\\r\\n self.PMT_image_reconstructed = np.reshape(Dataholder_average, (Value_yPixels, self.ScanArrayXnum))\\r\\n \\r\\n # Stack the arrays into a 3d array\\r\\n if i == 0:\\r\\n self.PMT_image_reconstructed_stack = self.PMT_image_reconstructed\\r\\n else:\\r\\n self.PMT_image_reconstructed_stack = np.concatenate((self.PMT_image_reconstructed_stack, self.PMT_image_reconstructed), axis=0)\\r\\n \\r\\n Localimg = Image.fromarray(self.PMT_image_reconstructed) #generate an image object\\r\\n Localimg.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+str(i)+'.tif')) #save as tif\\r\\n \\r\\n plt.figure()\\r\\n plt.imshow(self.PMT_image_reconstructed, cmap = plt.cm.gray)\\r\\n plt.show()\\r\\n except:\\r\\n np.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+'flatten'), self.data_collected_0)\\r\\n \\r\\n elif self.channel_number == 2: \\r\\n if 'PMT' not in self.readinchan:\\r\\n self.data_collected_0 = data_waveformreceived[0]\\r\\n \\r\\n self.PlotDataItem_patch_voltage = PlotDataItem(self.xlabelhere_all, self.data_collected_0)\\r\\n #use the same color as before, taking advantages of employing same keys in dictionary\\r\\n self.PlotDataItem_patch_voltage.setPen('w')\\r\\n self.pw_data.addItem(self.PlotDataItem_patch_voltage)\\r\\n \\r\\n self.textitem_patch_voltage = pg.TextItem(('Vp'), color=('w'), anchor=(1, 1))\\r\\n self.textitem_patch_voltage.setPos(0, 1)\\r\\n self.pw_data.addItem(self.textitem_patch_voltage) \\r\\n \\r\\n self.data_collected_1 = data_waveformreceived[1]\\r\\n \\r\\n self.PlotDataItem_patch_current = PlotDataItem(self.xlabelhere_all, self.data_collected_1)\\r\\n #use the same color as before, taking advantages of employing same keys in dictionary\\r\\n self.PlotDataItem_patch_current.setPen('c')\\r\\n self.pw_data.addItem(self.PlotDataItem_patch_current)\\r\\n \\r\\n self.textitem_patch_current = pg.TextItem(('Ip'), color=('w'), anchor=(1, 1))\\r\\n self.textitem_patch_current.setPos(0, 1)\\r\\n self.pw_data.addItem(self.textitem_patch_current) \\r\\n elif 'PMT' in self.readinchan:\\r\\n self.data_collected_0 = data_waveformreceived[0]*-1\\r\\n self.data_collected_0 = self.data_collected_0[0:len(self.data_collected_0)-1]\\r\\n \\r\\n try:\\r\\n for i in range(self.repeatnum):\\r\\n self.PMT_image_reconstructed_array = self.data_collected_0[np.where(self.PMT_data_index_array_repeated == i+1)]\\r\\n Dataholder_average = np.mean(self.PMT_image_reconstructed_array.reshape(self.averagenum, -1), axis=0)\\r\\n Value_yPixels = int(len(self.samples_1)/self.ScanArrayXnum)\\r\\n self.PMT_image_reconstructed = np.reshape(Dataholder_average, (Value_yPixels, self.ScanArrayXnum))\\r\\n \\r\\n # Stack the arrays into a 3d array\\r\\n if i == 0:\\r\\n self.PMT_image_reconstructed_stack = self.PMT_image_reconstructed\\r\\n else:\\r\\n self.PMT_image_reconstructed_stack = np.concatenate((self.PMT_image_reconstructed_stack, self.PMT_image_reconstructed), axis=0)\\r\\n \\r\\n Localimg = Image.fromarray(self.PMT_image_reconstructed) #generate an image object\\r\\n Localimg.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+str(i)+'.tif')) #save as tif\\r\\n \\r\\n plt.figure()\\r\\n plt.imshow(self.PMT_image_reconstructed, cmap = plt.cm.gray)\\r\\n plt.show()\\r\\n except:\\r\\n np.save(os.path.join(self.savedirectory, datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'_PMT_'+self.saving_prefix+'_'+'contourscanning'), self.data_collected_0)\\r\\n \\r\\n if 'Vp' in self.readinchan:\\r\\n self.data_collected_1 = data_waveformreceived[1]\\r\\n \\r\\n self.PlotDataItem_patch_voltage = PlotDataItem(self.xlabelhere_all, self.data_collected_1)\\r\\n #use the same color as before, taking advantages of employing same keys in dictionary\\r\\n self.PlotDataItem_patch_voltage.setPen('w')\\r\\n self.pw_data.addItem(self.PlotDataItem_patch_voltage)\\r\\n \\r\\n self.textitem_patch_voltage = pg.TextItem(('Vp'), color=('w'), anchor=(1, 1))\\r\\n self.textitem_patch_voltage.setPos(0, 1)\\r\\n self.pw_data.addItem(self.textitem_patch_voltage)\\r\\n elif 'Ip' in self.readinchan:\\r\\n self.data_collected_1 = data_waveformreceived[1]\\r\\n \\r\\n self.PlotDataItem_patch_current = PlotDataItem(self.xlabelhere_all, self.data_collected_1)\\r\\n #use the same color as before, taking advantages of employing same keys in dictionary\\r\\n self.PlotDataItem_patch_current.setPen('c')\\r\\n self.pw_data.addItem(self.PlotDataItem_patch_current)\\r\\n \\r\\n self.textitem_patch_current = pg.TextItem(('Ip'), color=('w'), anchor=(1, 1))\\r\\n self.textitem_patch_current.setPos(0, 1)\\r\\n self.pw_data.addItem(self.textitem_patch_current)\",\n \"def sample(self):\\n timestamp = time.time()\\n try:\\n res = requests.get(self.url)\\n except requests.exceptions.ConnectionError as error:\\n LOG.warning(\\\"%s %s\\\", self, error)\\n return\\n if 199 < res.status_code < 300:\\n self.data.append((timestamp, res.json()))\\n LOG.debug(\\\"%s appended data sample\\\", self)\\n else:\\n LOG.warning(\\\"Error %s loading data from %s\\\", res.status_code, self)\\n self.data = self.data[-self.max_samples:]\",\n \"def getData(self):\\n self.ser.write(b'g')\\n readString = self.ser.readline()\\n print(readString)\\n readString = readString.decode(\\\"utf-8\\\")\\n splittedString = readString.split('\\\\t')\\n for i, num in enumerate(splittedString):\\n try:\\n splittedString[i] = int(float(num))\\n except ValueError:\\n pass\\n self.accString.set('Accleration\\\\nX: %.5f\\\\nY: %.5f\\\\nZ: %.5f' %\\n (splittedString[0], splittedString[1],\\n splittedString[2]))\\n self.logFile.write(readString)\\n self.comJob = root.after(10, self.getData)\",\n \"def get_values(self):\\n if self.__work_state == work_state[\\\"Sleeping\\\"]:\\n raise RuntimeError(\\\"{}: the sensor is sleeping and will not send any values. Will wake it up first.\\\".format(self.sensor_name))\\n if self.__report_mode == report_mode[\\\"Passive\\\"]:\\n raise RuntimeError(\\\"{}: the sensor is in passive report mode and will not automatically send values. You need to call request() to get values.\\\".format(self.sensor_name))\\n\\n self.__duty_cycle_start = time.time()\\n while self.duty_cycle == 0 or time.time() < self.__duty_cycle_start + self.__read_timeout:\\n response_data = self.__response()\\n if len(response_data) > 0:\\n self.logger.info(\\\"{}: received response from sensor {} bytes.\\\".format(self.sensor_name, len(response_data)))\\n return self.__extract_values_from_response(response_data)\\n raise IOError(\\\"{}: no data within read timeout of {} has been received.\\\".format(self.sensor_name, self.__read_timeout))\",\n \"def collect_samples(serialPort,NO_SENSORS,NO_SAMPLES,log):\\n run = '1'\\n badSamples = 0\\n count = 1\\n log_temp = []\\n temp = [0] * 20\\n NO_FIELDS = (NO_SENSORS * 3) + 1\\n \\n while (run == '1'):\\n # If the input buffer is not empty read the data out into rawData using \\\\n as a delimiter.\\n if (serialPort.inWaiting()>0):\\n rawData = serialPort.readline()\\n print(rawData)\\n \\n # If invalid data is recieved this prevents program crash\\n try:\\n # Decode the bytes into a string\\n data = rawData.decode()\\n \\n # Split x, y, z and newline values into a list\\n if (count >= (NO_SAMPLES + 1)):\\n endTime_temp = data.split(\\\" \\\", 2)\\n if (len(endTime_temp) == 2 and '' not in endTime_temp):\\n endTime = int(endTime_temp[0])\\n else:\\n endTime = 780\\n print('Time not recieved')\\n print('Lost Samples: ' + str(badSamples))\\n run = '0'\\n else:\\n data_readings = data.split(\\\" \\\", NO_FIELDS)\\n print(data_readings)\\n \\n # A correct sample should contain 16 values and not include null and so this is used\\n # to validate the data and record any samples that are discarded in this way\\n if (len(data_readings) == NO_FIELDS and '' not in data_readings):\\n # Discard newline characters before saving data\\n int_data_readings = list(map(int,data_readings[:(NO_FIELDS - 1)]))\\n log_temp.append(int_data_readings)\\n else:\\n badSamples += 1\\n except:\\n print('Invalid data recieved')\\n \\n count += 1\\n\\n samplingPeriod = (endTime/NO_SAMPLES)/NO_SENSORS\\n timeStamp = 0.0\\n\\n for i in range(0,len(log_temp)):\\n for j in range(0,NO_SENSORS):\\n temp[0+(j*4)] = log_temp[i][0+(j*3)]\\n temp[1+(j*4)] = log_temp[i][1+(j*3)]\\n temp[2+(j*4)] = log_temp[i][2+(j*3)]\\n temp[3+(j*4)] = timeStamp\\n timeStamp += samplingPeriod\\n log.append(temp.copy())\",\n \"def collect_data(self):\\r\\n self.vcp.read(self.vcp.inWaiting())\\r\\n while True:\\r\\n data = self.vcp.readline()\\r\\n data = data.decode(\\\"ASCII\\\")\\r\\n timestamp = \\\",\\\" + datetime.datetime.now().strftime(\\\"%H:%M:%S\\\")\\r\\n data_timestamp = data + timestamp\\r\\n if not self.data_pause:\\r\\n self.update_anemometer_log.emit(data_timestamp)\\r\\n if self.stop_timer:\\r\\n break\",\n \"def send_data():\\n range = request.args.get('range', '30')\\n time = arrow.utcnow().replace(minutes=-int(range))\\n data = Temperature.query\\\\\\n .filter(Temperature.timestamp > time).order_by(Temperature.timestamp.desc()).all()\\n return jsonify(results=[i.serialize for i in data])\",\n \"def _obtain_data(self):\\n (self.data_df, self.column_df, self.station_name, self.log_file, self.station_lat, self.station_lon,\\n self.station_elev, self.ws_anemometer_height, self.missing_fill_value, self.script_mode,\\n self.auto_mode, self.fill_mode, self.metadata_mode, self.generate_bokeh, self.metadata_df,\\n metadata_series) = input_functions.obtain_data(self.config_path, self.metadata_path)\\n\\n if self.script_mode == 1: # correcting data\\n self.mc_iterations = 1000 # Number of iters for MC simulation of thornton running solar radiation gen\\n else:\\n self.mc_iterations = 50 # if we're not correcting data then only do a few iterations to save time\\n\\n print(\\\"\\\\nSystem: Raw data successfully extracted from station file.\\\")\\n\\n # Extract individual variables from data frame back into to numpy arrays.\\n self.data_year = np.array(self.data_df.year)\\n self.data_month = np.array(self.data_df.month)\\n self.data_day = np.array(self.data_df.day)\\n self.data_tavg = np.array(self.data_df.tavg)\\n self.data_tmax = np.array(self.data_df.tmax)\\n self.data_tmin = np.array(self.data_df.tmin)\\n self.data_tdew = np.array(self.data_df.tdew)\\n self.data_ea = np.array(self.data_df.ea)\\n self.data_rhavg = np.array(self.data_df.rhavg)\\n self.data_rhmax = np.array(self.data_df.rhmax)\\n self.data_rhmin = np.array(self.data_df.rhmin)\\n self.data_rs = np.array(self.data_df.rs)\\n self.data_ws = np.array(self.data_df.ws)\\n self.data_precip = np.array(self.data_df.precip)\\n\\n self.output_file_path = \\\"correction_files/\\\" + self.station_name + \\\"_output\\\" + \\\".xlsx\\\"\",\n \"def getSpectrumData(self):\\n spectrum = []\\n\\n if not self.lastStatus.isHighSpeed:\\n raise NotImplementedError('Full speed mode not implemented for {0}.'.format(self.model))\\n\\n packetCount = self.lastStatus.packetCount\\n exposureTime = self.lastStatus.integrationTime\\n\\n for packet in range(packetCount):\\n inputEndpoint = self.inputEndpoints[0]\\n if self.idProduct == USB4000.classIdProduct and packet <= 3:\\n inputEndpoint = self.inputEndpoints[1]\\n\\n values = self.readReply(inputEndpoint, unpackingFormat='<'+'H'*256, timeout=exposureTime*2)\\n spectrum.extend(np.array(values))\\n\\n confirmation = self.readReply(inputEndpoint, size=1)\\n if confirmation[0] != 0x69:\\n self.flushEndpoints()\\n raise RuntimeError('Spectrometer is desynchronized. Should disconnect')\\n\\n if self.discardTrailingSamples > 0:\\n spectrum = spectrum[:-self.discardTrailingSamples]\\n if self.discardLeadingSamples > 0:\\n spectrum = spectrum[self.discardLeadingSamples:]\\n\\n return np.array(spectrum)\",\n \"def logging_data(self):\\n with open('sensor_data.log','w') as f:\\n json.dump(self.read_continuous_data, f)\",\n \"def linedata():\\n get_values = request.args\\n pc = get_values.get('pc') is not None # Per Capita\\n gr = get_values.get('gr') is not None # Growth Rate\\n place_args, _ = get_place_args(get_values)\\n plot_data, _ = datachart_handler.get_plot_data(place_args, pc, gr)\\n return json.dumps(plot_data)\",\n \"def LoadingData(self, ticker, FullHistory=False):\\r\\n if FullHistory == False:\\r\\n url = \\\"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol={}&apikey={}\\\"\\r\\n else:\\r\\n url = \\\"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol={}&outputsize=full&apikey={}\\\"\\r\\n\\r\\n try:\\r\\n response = requests.get(url.format(ticker, self.key))\\r\\n response.raise_for_status()\\r\\n except requests.exceptions.RequestException as e:\\r\\n raise SystemExit(e)\\r\\n\\r\\n # The API returns 200 status even after you have a typo\\r\\n try:\\r\\n outputjson = response.json()['Time Series (Daily)']\\r\\n except:\\r\\n print(\\\"Please check ticker for typos or mismatches\\\")\\r\\n outputjson = None\\r\\n\\r\\n return outputjson, ticker\",\n \"def getTemperatureMeasurements(self):\\n # self.board.readline()\\n self.stop = False\\n times = []\\n temps = [[], [], []]\\n \\n # A synchronisation string containing the characters tx is sent before each set of measurements,\\n # we ensure correct reading of the measurements by waiting for this string\\n while str(self.board.readline()).strip('b\\\\'\\\\\\\\rn') != 'tx':\\n pass\\n \\n while not self.stop:\\n # A synchronisation string containing the characters tx is sent before each set of measurements\\n tx = self.board.readline()\\n if str(tx).strip('b\\\\'\\\\\\\\rn') == 'tx':\\n rawData1 = self.board.readline()\\n rawData2 = self.board.readline()\\n rawData3 = self.board.readline()\\n rawData4 = self.board.readline()\\n \\n \\n timeStamp = str(rawData1).strip('b\\\\'\\\\\\\\rn')\\n temp1 = str(rawData2).strip('b\\\\'\\\\\\\\rn')\\n temp2 = str(rawData3).strip('b\\\\'\\\\\\\\rn')\\n temp3 = str(rawData4).strip('b\\\\'\\\\\\\\rn')\\n try:\\n times.append(float(timeStamp) / 1000)\\n temps[0].append(float(temp1) / 128)\\n temps[1].append(float(temp2) / 128)\\n temps[2].append(float(temp3) / 128)\\n # print(f'\\\\rtime: {float(timeStamp) / 1000:.2f} s, Temperature measured on sensor 1: {float(temp1) / 128:.2f} °C,'\\n # f'sensor 2: {float(temp2) / 128:.2f} °C, sensor 3: {float(temp3) / 128:.2f} °C', sep='', end='', flush=True)\\n except:\\n print(rawData1, rawData2, rawData3, rawData4)\\n \\n \\n if self.stop:\\n print('\\\\nMeasurement finished...')\\n \\n self.data_stack[self.fetch_kinds[0]] = times\\n self.data_stack[self.fetch_kinds[1]] = temps[0]\\n self.data_stack[self.fetch_kinds[2]] = temps[1]\\n self.data_stack[self.fetch_kinds[3]] = temps[2]\\n \\n if (len(self.data_stack['Sensor 1 Temp']) != len(times) or len(self.data_stack['Sensor 2 Temp']) != len(times) or len(self.data_stack['Sensor 3 Temp']) != len(times)):\\n print(\\\"Warning: There may be some missing values!\\\")\",\n \"def slot_fullhistory(self, dummy_sender, data):\\r\\n (history) = data\\r\\n\\r\\n if not len(history):\\r\\n self.debug(\\\"### history download was empty\\\")\\r\\n return\\r\\n\\r\\n def get_time_round(date):\\r\\n \\\"\\\"\\\"round timestamp to current candle timeframe\\\"\\\"\\\"\\r\\n return int(date / self.timeframe) * self.timeframe\\r\\n\\r\\n #remove existing recent candle(s) if any, we will create them fresh\\r\\n date_begin = get_time_round(int(history[0][\\\"date\\\"]))\\r\\n while len(self.candles) and self.candles[0].tim >= date_begin:\\r\\n self.candles.pop(0)\\r\\n\\r\\n new_candle = OHLCV(0, 0, 0, 0, 0, 0) #this is a dummy, not actually inserted\\r\\n count_added = 0\\r\\n for trade in history:\\r\\n date = int(trade[\\\"date\\\"])\\r\\n price = int(trade[\\\"price_int\\\"])\\r\\n volume = int(trade[\\\"amount_int\\\"])\\r\\n time_round = get_time_round(date)\\r\\n if time_round > new_candle.tim:\\r\\n if new_candle.tim > 0:\\r\\n self._add_candle(new_candle)\\r\\n count_added += 1\\r\\n new_candle = OHLCV(\\r\\n time_round, price, price, price, price, volume)\\r\\n new_candle.update(price, volume)\\r\\n\\r\\n # insert current (incomplete) candle\\r\\n self._add_candle(new_candle)\\r\\n count_added += 1\\r\\n self.debug(\\\"### got %d updated candle(s)\\\" % count_added)\\r\\n self.ready_history = True\\r\\n self.signal_fullhistory_processed(self, None)\\r\\n self.signal_changed(self, (self.length()))\",\n \"def sample(self):\\n logger.info(\\\"%s: collect sensor data\\\", self.__class__.__name__)\\n samples = []\\n self._fetch_data(samples)\\n return samples\",\n \"def AcquiredData (self, arguments=None) :\\n\\t\\tself.OODriver.Wrapper_getSpectrum(self.wrapperHandle,self.spectrometerIndex,self.bufferHandle)\\n\\t\\t\\n\\t\\tif self.OODriver.Wrapper_isSaturated(self.wrapperHandle,self.spectrometerIndex) :\\n\\t\\t\\tprint \\\"Warning: OcenOptics spectrometer is saturated!\\\"\\n\\t\\t\\t\\n\\t\\ttry : return self.buffer[self.spectral_interval]\\n\\t\\texcept AttributeError : return self.buffer\",\n \"def got_data(self, data):\\n if self.get_current_state() == SBE37ProtocolState.DIRECT_ACCESS:\\n # direct access mode\\n if len(data) > 0:\\n mi_logger.debug(\\\"SBE37Protocol._got_data(): <\\\" + data + \\\">\\\") \\n if self._driver_event:\\n self._driver_event(DriverAsyncEvent.DIRECT_ACCESS, data)\\n # TODO: what about logging this as an event?\\n return\\n \\n if len(data)>0:\\n # Call the superclass to update line and prompt buffers.\\n CommandResponseInstrumentProtocol.got_data(self, data)\\n \\n # If in streaming mode, process the buffer for samples to publish.\\n cur_state = self.get_current_state()\\n if cur_state == SBE37ProtocolState.AUTOSAMPLE:\\n if SBE37_NEWLINE in self._linebuf:\\n lines = self._linebuf.split(SBE37_NEWLINE)\\n self._linebuf = lines[-1]\\n for line in lines:\\n self._extract_sample(line)\",\n \"def get_data(self):\\n self._send_command(self._adapter.get_data())\",\n \"def sendHistoricAndPrediction(data):\\n global df_hisotorical\\n df_hisotorical = get_historical_data(data[\\\"UserID\\\"])\\n data[\\\"seqMode\\\"] = 0\\n data[\\\"versionline\\\"] = 0\\n rounded_pred = predict(data)\\n n = sendReport(data, rounded_pred, data[\\\"satzID\\\"], \\\"intv5\\\")\\n\\n return rounded_pred\",\n \"def _log_data_received(self, timestamp, data, logconf):\\n\\n # Check so that the incoming data belongs to what we are currently\\n # logging\\n \\n if self._previous_config:\\n if self._previous_config.name == logconf.name:\\n self._plot.add_data(data, timestamp)\\n\\n self.avgsumnumb=self.avgsumnumb+1;\\n if self.avgsumnumb >= 50:\\n print(\\\"Total:\\\", self.avgsumnumb)\\n for name in data:\\n print(\\\"Average\\\", name, self.avgsumvalue[name]/self.avgsumnumb)\\n self.avgsumvalue[name]=0;\\n self.avgsumnumb=0;\\n for name in data:\\n self.avgsumvalue[name]=self.avgsumvalue[name]+data[name];\\n #print(self.avgsumvalue[name])\\n #logger.info(\\\"Here %s\\\", data[name])\\n #self._items[name].add_point(data[name], ts)\\n #self.avgsumvalue[name]+=data[name];\\n #logger.info(\\\"Here %s\\\", self.avgsumvalue[name])\",\n \"def on_redraw_timer(self, event):\\n \\n if self.sampling_timer.IsRunning():\\n self.daq.get_data()\\n self.draw_plot()\\n else:\\n self.control_box.txt_info_box.SetLabel('Measurement complete')\\n self.calculate()\\n return\",\n \"def get_new_data(self):\\n\\n # record bar parse performance\\n self.logger.debug(\\\"Started parsing new ticks.\\\")\\n start_parse = time.time()\\n for exchange in self.exchanges:\\n exchange.parse_ticks()\\n end_parse = time.time()\\n duration = round(end_parse - start_parse, 5)\\n\\n self.logger.debug(\\n \\\"Parsed \\\" + str(self.total_instruments) +\\n \\\" instruments' ticks in \\\" + str(duration) + \\\" seconds.\\\")\\n self.track_tick_processing_performance(duration)\\n\\n # wrap new 1 min bars in market events\\n new_market_events = []\\n for exchange in self.exchanges:\\n bars = exchange.get_new_bars()\\n for symbol in exchange.get_symbols():\\n for bar in bars[symbol]:\\n event = MarketEvent(exchange.get_name(), bar)\\n new_market_events.append(event)\\n # add bars to save-to-db-later queue\\n # TODO: store new bars concurrently with a processpool\\n self.bars_save_to_db.put(event)\\n return new_market_events\",\n \"def get_data_sync(self, out_format: str='json', chk_interval=0.25, max_chks=65535):\\n if self.data:\\n return self.data\\n check_cnt = 0\\n while True:\\n if check_cnt >= max_chks:\\n break\\n self.data_ready = self.check_available()\\n if self.data_ready:\\n break\\n else:\\n check_cnt += 1\\n sleep(chk_interval)\\n if not self.data_ready:\\n raise DataNotReady(\\\"The run {} has not yet finished, data not available yet.\\\".format(self))\\n resp = self.ph.conn.request(\\n 'GET', self.ph.URLS['getdata'].format(self.run_token), dict(api_key=self.ph.api_key, format=out_format))\\n data = resp.data.decode('utf-8')\\n self.data = self.parse_json_data(data)\\n return self.data\",\n \"def generate_data(self):\\n print(\\\"generate_data - init\\\")\\n with open(self.input_file, \\\"r\\\") as f:\\n\\n # read JSON data from input file\\n data = json.loads(f.read())\\n\\n for idx, row in enumerate(data): \\n # serialize Python dict to string\\n msg = self.serialize_json(row)\\n #print(f\\\"Linha: {row}\\\")\\n self.send(self.topic, msg)\\n self.flush()\\n #print(\\\"Sleeping\\\")\\n time.sleep(1)\",\n \"def getCurentData(self):\\n if not self.labExperiment:\\n super().getCurentData()\\n else:\\n return np.array(self.connection.query('get_actuator_data'))\",\n \"def data():\\n if request.method == 'POST':\\n params = extract_variables(['temp', 'humid', 'pressure', 'light',\\n 'smoke', 'time', 'sensor_id'], request)\\n # Test to see if the minimum required variables were parsed\\n # TODO: Make this smarter\\n if not (params['temp'] or params['humid'] or params['pressure'])\\\\\\n or not params[\\\"sensor_id\\\"]:\\n # There's either no information or no sensor_id and time\\n abort(400)\\n # If there's no timestamp we'll assign one\\n # This makes it possible to use micro controller based sensors\\n # without RTC\\n if not params['time']:\\n params['time'] = time.time()\\n # Make sure sensor id is a valid integer\\n try:\\n int(params[\\\"sensor_id\\\"])\\n except ValueError:\\n abort(400)\\n\\n try:\\n # Try inserting values\\n query_db('INSERT INTO climate VALUES (?, ?, ?, ?, ?, ?, ?)',\\n [params['temp'], params['humid'], params['pressure'],\\n params['light'], params['smoke'],\\n params['time'], params[\\\"sensor_id\\\"]], commit=True)\\n except sqlite3.IntegrityError:\\n # Sensor not in database yet, add it with a temporary name\\n query_db('INSERT INTO sensors VALUES (?, ?)',\\n [params[\\\"sensor_id\\\"], str(uuid.uuid4())], commit=True)\\n # Then insert values...\\n query_db('INSERT INTO climate VALUES (?, ?, ?, ?, ?, ?, ?)',\\n [params['temp'], params['humid'], params['pressure'],\\n params['light'], params['smoke'],\\n params['time'], params[\\\"sensor_id\\\"]], commit=True)\\n return 'Sensor added and data saved'\\n return 'Data saved'\\n elif request.method == 'GET':\\n params = extract_variables(['start_time', 'end_time', 'sensor_id'], request)\\n data = query_climate_range(**params)\\n return jsonify(results=data)\",\n \"def read_and_display_data(hat, samples_per_channel, num_channels): \\n \\n # Read all of the available samples (up to the size of the read_buffer which\\n # is specified by the user_buffer_size). Since the read_request_size is set\\n # to -1 (READ_ALL_AVAILABLE), this function returns immediately with\\n # whatever samples are available (up to user_buffer_size) and the timeout\\n # parameter is ignored.\\n total_samples_read = 0\\n read_request_size = READ_ALL_AVAILABLE\\n completeFlag = 0 \\n timeout = 5.0\\n \\n # file switch: w = Write to a file\\n # file switch: w+ = Write to a file, if it doesn't exist create it\\n # file switch: a = Append to a file\\n # file switch: a+ = Append to a file, if is doesn't exist create it.\\n # file switch: x = will create a file, returns an error if the file exist\\n \\n\\n # If the scan starts, create a file name based upon current date and time.\\n # Retrieve the Current Working Directory and generate the full path \\n # to where to write the collected data as a .csv file. Open the file \\n # begin writing the data to the file. When done, close the file.\\n \\n try:\\n if os.path.exists(basepath):\\n if not (os.path.exists(mypath)):\\n os.mkdir(mypath)\\n else:\\n os.mkdir(basepath)\\n os.chdir(basepath)\\n os.mkdir(mypath)\\n except OSError as exc:\\n raise\\n \\n os.chdir(mypath)\\n fileDateTime = datetime.strftime(datetime.now(), \\\"(%m_%d_%Y)-(%H-%M-%S)\\\")\\n #filePath = mypath + \\\"/\\\" + DAQ_NAME + \\\"_\\\" + fileName + \\\".csv\\\"\\n filePath = mypath + \\\"/\\\" + DAQ_NAME + \\\"_\\\" + fileDateTime + \\\".csv\\\"\\n csvfile = open(filePath, \\\"w+\\\")\\n csvwriter = csv.writer(csvfile) \\n \\n # Recording LED\\n GPIO.setmode(GPIO.BCM)\\n GPIO.setup(RECORDING_LED, GPIO.OUT, initial=GPIO.LOW)\\n GPIO.output(RECORDING_LED,GPIO.HIGH)\\n \\n while total_samples_read < samples_per_channel:\\n read_result = hat.a_in_scan_read(read_request_size, timeout)\\n\\n # Check for an overrun error\\n if read_result.hardware_overrun:\\n print('\\\\n\\\\nHardware overrun\\\\n')\\n break\\n elif read_result.buffer_overrun:\\n print('\\\\n\\\\nBuffer overrun\\\\n')\\n break\\n elif not (read_result.running and completeFlag == 0):\\n completeFlag = 1\\n print('\\\\n (2) Recording Completed - Buffer Draining')\\n\\n samples_read_per_channel = int(len(read_result.data) / num_channels)\\n total_samples_read += samples_read_per_channel\\n \\n totalSamples = len(read_result.data) \\n\\n if samples_read_per_channel > 0:\\n index = samples_read_per_channel * num_channels - num_channels\\n \\n new_index = 0\\n myArray=[] #create an empty array\\n for i in range(0, totalSamples, num_channels):\\n myArray.append([]) #add a row to the array (COLUMN)\\n for j in range(num_channels):\\n\\t\\t\\t\\t\\t#append a num_channels of data to the array (ROW)\\n myArray[new_index].append(read_result.data[i + j]) \\n new_index+=1\\n\\n csvwriter.writerows(myArray) #Write the array to file\\n csvfile.flush\\n\\n # Cleanup\\n csvfile.close() \\n print('\\\\n (3) Buffer Drained - Data Saved to CSV File\\\\n')\\n GPIO.cleanup()\\n GPIO.setmode(GPIO.BCM)\\n \\n # Complete LED\\n GPIO.setup(COMPLETE_LED, GPIO.OUT, initial=GPIO.LOW)\\n GPIO.output(COMPLETE_LED,GPIO.HIGH)\\n time.sleep(5)\\n GPIO.cleanup()\\n hat.a_in_scan_cleanup()\\n global CMD_RECEIVED\\n CMD_RECEIVED = 1\\n \\n # Restarts script to prepare for another recording\\n main()\",\n \"def _response_power_buffer(self, message):\\n if message.logaddr.value == self._last_log_address:\\n self._last_log_collected = True\\n # Collect logged power usage\\n for i in range(1, 5):\\n if getattr(message, \\\"logdate%d\\\" % (i,)).value != None:\\n dt = getattr(message, \\\"logdate%d\\\" % (i,)).value\\n if getattr(message, \\\"pulses%d\\\" % (i,)).value == 0:\\n self.power_history[dt] = 0.0\\n else:\\n self.power_history[dt] = self.pulses_to_kWs(\\n getattr(message, \\\"pulses%d\\\" % (i,)).value, 3600\\n )\\n # Cleanup history for more than 2 day's ago\\n if len(self.power_history.keys()) > 48:\\n for dt in list(self.power_history.keys()):\\n if (dt + self.stick.timezone_delta - timedelta(hours=1)).date() < (\\n datetime.now().today().date() - timedelta(days=1)\\n ):\\n del self.power_history[dt]\\n # Recalculate power use counters\\n last_hour_usage = 0\\n today_power = 0\\n yesterday_power = 0\\n for dt in self.power_history:\\n if (dt + self.stick.timezone_delta) == datetime.now().today().replace(\\n minute=0, second=0, microsecond=0\\n ):\\n last_hour_usage = self.power_history[dt]\\n if (\\n dt + self.stick.timezone_delta - timedelta(hours=1)\\n ).date() == datetime.now().today().date():\\n today_power += self.power_history[dt]\\n if (dt + self.stick.timezone_delta - timedelta(hours=1)).date() == (\\n datetime.now().today().date() - timedelta(days=1)\\n ):\\n yesterday_power += self.power_history[dt]\\n if self.power_consumption_prev_hour != last_hour_usage:\\n self.power_consumption_prev_hour = last_hour_usage\\n self.do_callback(SENSOR_POWER_CONSUMPTION_PREVIOUS_HOUR[\\\"id\\\"])\\n if self.power_consumption_today != today_power:\\n self.power_consumption_today = today_power\\n self.do_callback(SENSOR_POWER_CONSUMPTION_TODAY[\\\"id\\\"])\\n if self.power_consumption_yesterday != yesterday_power:\\n self.power_consumption_yesterday = yesterday_power\\n self.do_callback(SENSOR_POWER_CONSUMPTION_YESTERDAY[\\\"id\\\"])\",\n \"def get_data_from_api():\\n s_date = datetime.now()\\n uid = uuid.uuid1()\\n start_time = time.time()\\n cfl.logging.info(f'new session num {uid} was created at {s_date} ')\\n\\n functions_dict = {'graph' : get_stock_graph_in_range, 'holder': get_stock_holder, 'balance': get_balance,\\n 'cash_flow': get_cash_flow, 'earning': get_earning}\\n\\n answers = inquirer.prompt(questions)\\n symbol = answers.get(\\\"symbol\\\")\\n\\n func = functions_dict[answers.get('user_option')]\\n\\n if answers.get(\\\"user_option\\\") == \\\"graph\\\" :\\n answer_graph = inquirer.prompt(question_graph)\\n start_date = answer_graph.get(\\\"start_date\\\")\\n end_date = answer_graph.get(\\\"end_date\\\")\\n period = answer_graph.get(\\\"period\\\")\\n e_date = datetime.now()\\n end_time = time.time()\\n print(f\\\"{func(symbol, start_date, end_date, period)}\\\\n\\\")\\n cfl.logging.info(f' session {uid} end at : {e_date} ')\\n cfl.logging.info(f'the time it took to get data from api for session {uid} is: {end_time - start_time} ')\\n return\\n\\n else:\\n end_time = time.time()\\n e_date = datetime.now()\\n print(f\\\"{func(symbol)}\\\\n\\\\n\\\")\\n cfl.logging.info(f' session {uid} end at : {e_date} ')\\n cfl.logging.info(f'the time it took to get data from api for session {uid} is: {end_time - start_time} ')\\n return\",\n \"def get_data(self):\\n if self.ser.in_waiting:\\n data_string = self.ser.readline().decode().strip()\\n if not data_string: return self.data\\n self.data = [\\n float(element) for element in data_string.split()\\n ]\\n self.ser.reset_input_buffer()\\n return self.data\",\n \"def _stab_log_data(self, timestamp, data, logconf):\\n\\t\\t#print strftime(\\\"%H:%M:%S \\\", gmtime())\\n\\t\\tstr1=data['mb.distance']\\n\\t\\tnum1=float(str1)\\n\\t\\tnum1=30-num1\\n\\n\\t\\t#self.updateplot(num1)\\n\\t\\t#print \\\"test: \\\",num1\\n\\t\\t#self.databuffer.append(num1)\\n\\t\\t#self.y[:] = self.databuffer\\n\\t\\t#self.curve.setData(x,num1)\\n\\t\\t#self.app.processEvents()\\n\\n\\t\\tresults.append(num1)\\n\\t\\tresultspyqt.append(num1)\\n\\t\\tself.x = list(range(0,len(resultspyqt)))\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\tprint \\\"[%d][%s]: %s\\\" % (timestamp, logconf.name, data)\\n\\t\\t\\n\\t\\t#if not data: break\\n\\t\\tdata=self.serv_listen()\\n\\t\\tif data>0:\\n\\t\\t\\tprint \\\"app: \\\",data\\n\\t\\t\\tif(int(data)<100):#we are in thrust\\n\\t\\t\\t\\tprint \\\"thrust\\\"\\n\\t\\t\\t\\tprint self.roll, self.pitch, self.yawrate, self.thrust \\n\\t\\t\\t\\tself.thrust=int(data)*600\\n\\t\\t\\t\\tself._cf.commander.send_setpoint(self.roll, self.pitch, self.yawrate, self.thrust)\\n\\t\\t\\t\\t#time.sleep(0.1)\\n\\t\\t\\telif((int(data)>100)and(int(data)<200)):#we are in pitch\\n\\t\\t\\t\\tprint roll, pitch, yawrate, thrust \\n\\t\\t\\t\\tpitch=(int(data))/5-30\\n\\t\\t\\t\\tself._cf.commander.send_setpoint(roll, (int(data))/5-30, yawrate, thrust)\\n\\t\\t\\t\\t#time.sleep(0.1)\\n\\t\\t\\telif(int(data)>200):#we are in roll\\n\\t\\t\\t\\tprint \\\"add roll: \\\",150-(int(data))*3/5\\n\\t\\t\\t\\tprint roll, pitch, yawrate, thrust \\n\\t\\t\\t\\troll=50-(int(data))/5\\n\\t\\t\\t\\tself._cf.commander.send_setpoint(50-(int(data))/5, pitch, yawrate, thrust)\\n\\t\\t\\t\\t#time.sleep(0.1) \\n\\t\\tif data == 'Hover':\\n\\t\\t\\tprint \\\"app: \\\",data\",\n \"def result(self):\\n\\n # determine the X and Y sensors to plot from those sensors selected by the user.\\n sensorX = bmsapp.models.Sensor.objects.get(pk=self.request_params['select_sensor_x'])\\n sensorY = bmsapp.models.Sensor.objects.get(pk=self.request_params['select_sensor_y'])\\n\\n # determine the averaging time\\n averaging_hours = float(self.request_params['averaging_time_xy'])\\n\\n # get the building's timezone\\n tz = pytz.timezone(self.timezone)\\n\\n # determine the start and end time for selecting records\\n st_ts, end_ts = self.get_ts_range()\\n\\n # get the dividing date, if there is one\\n div_datestring = self.request_params['div_date']\\n div_dt = tz.localize(parser.parse(div_datestring)) if len(div_datestring) else None\\n\\n\\n # The list that will hold each series\\n series = []\\n\\n # get the X and Y sensor records and perform the requested averaging\\n dfX = self.reading_db.dataframeForOneID(sensorX.sensor_id, st_ts, end_ts, tz)\\n dfY = self.reading_db.dataframeForOneID(sensorY.sensor_id, st_ts, end_ts, tz)\\n\\n if not dfX.empty and not dfY.empty: # both sensors have some data, so proceed to average the data points\\n \\n dfX = bmsapp.data_util.resample_timeseries(dfX,averaging_hours)\\n dfX.rename(columns = {'val':'X'}, inplace = True)\\n\\n dfY = bmsapp.data_util.resample_timeseries(dfY,averaging_hours)\\n dfY.rename(columns = {'val':'Y','ts':'tsY'}, inplace = True)\\n\\n # Join the X and Y values for the overlapping time intervals and make\\n # a list of points.\\n df_all = dfX.join(dfY, how='inner') # inner join does intersection of timestamps\\n\\n # make sure there are matched records before continuing\\n if len(df_all):\\n\\n # add a point name column to be used in the tooltip.\\n df_all['name'] = df_all.index.strftime('%a %m/%d/%y %H:%M')\\n\\n # add a column identifying whether point is in occupied or unoccupied period.\\n resolution = self.occupied_resolution()\\n if (self.schedule is None) or (resolution is None):\\n # no schedule or data doesn't lend itself to classifying\\n # consider all points to be occupied\\n df_all['occupied'] = 1\\n else:\\n df_all['occupied'] = [self.schedule.is_occupied(ts, resolution=resolution) for ts in df_all.ts]\\n\\n # Set up the parameters for the different series of data\\n # Required Info is (starting datetime, ending datetime, occupied status (0 or 1), series name, \\n # series color, series symbol, series radius, series zindex).\\n now_dt = datetime.now()\\n if div_dt:\\n # A dividing date was provided by the user.\\n div_dt = div_dt.replace(tzinfo=None) # needs to be naive\\n ser_params = ( (datetime(1970,1,1), div_dt, 1, 'Prior to %s' % div_datestring, '#2f7ed8', 'circle', 4.5),\\n (datetime(1970,1,1), div_dt, 0, 'Prior to %s, Unoccupied' % div_datestring, '#2f7ed8', 'triangle-up', 3),\\n (div_dt, now_dt, 1, '%s and beyond' % div_datestring, '#FF0000', 'circle', 4.5),\\n (div_dt, now_dt, 0, '%s and beyond, Unoccupied' % div_datestring, '#FF0000', 'triangle-up', 3) )\\n else:\\n # Divide data by how recent it is.\\n ser_params = ( (now_dt - timedelta(days=1), now_dt, 1, 'Last 24 Hours', '#FF0000', 'circle', 4.5),\\n (now_dt - timedelta(days=1), now_dt, 0, 'Last 24 Hours, Unoccupied', '#FF0000', 'triangle-up', 3),\\n (now_dt - timedelta(days=7), now_dt - timedelta(days=1), 1, 'Last 7 Days', '#00CC00', 'circle', 4.5),\\n (now_dt - timedelta(days=7), now_dt - timedelta(days=1), 0, 'Last 7 Days, Unoccupied', '#00CC00', 'triangle-up', 3),\\n (datetime(1970,1,1), now_dt - timedelta(days=7), 1, '7+ Days Old', '#2f7ed8', 'circle', 4.5),\\n (datetime(1970,1,1), now_dt - timedelta(days=7), 0, '7+ Days Old, Unoccupied', '#2f7ed8', 'triangle-up', 3),\\n )\\n\\n for t_start, t_end, occup, ser_name, ser_color, ser_symbol, radius in reversed(ser_params):\\n mask = (df_all.index >= t_start) & (df_all.index < t_end) & (df_all.occupied==occup)\\n if mask.max():\\n series.append( {'x': np.char.mod('%.4g',df_all[mask].X.values).astype(float).tolist(),\\n 'y': np.char.mod('%.4g',df_all[mask].Y.values).astype(float).tolist(),\\n 'text': df_all[mask].name.values.tolist(),\\n 'type': 'scatter',\\n 'mode': 'markers', \\n 'name': ser_name,\\n 'marker': { 'color': ser_color,\\n 'symbol': ser_symbol,\\n 'size': radius * 2\\n }\\n } )\\n\\n # create the X and Y axis labels and the series\\n x_label = '%s, %s' % (sensorX.title, sensorX.unit.label)\\n y_label = '%s, %s' % (sensorY.title, sensorY.unit.label)\\n\\n opt = self.get_chart_options('plotly')\\n opt['data'] = series\\n opt['layout']['title'] = sensorY.title + \\\" vs. \\\" + sensorX.title\\n opt['layout']['xaxis']['title'] = x_label\\n opt['layout']['yaxis']['title'] = y_label\\n opt['layout']['legend']['traceorder'] = 'reversed'\\n\\n html = basechart.chart_config.chart_container_html(opt['layout']['title'])\\n\\n return {'html': html, 'objects': [('plotly', opt)]}\",\n \"def realtimestreaming(self, **kwargs):\\n url_path = 'realtimestreaming'\\n self.logger.debug(f\\\"Get Realtime Streaming report data\\\")\\n body = self._make_body(kwargs)\\n return self._common_post(request_path=url_path, body=body)\",\n \"def _send_data(self):\\n \\n # Do not send more than 100 datasets each time (totally arbitrary)\\n MAX_DATA_SETS_PER_POST = 100\\n data_to_send = self._data_buffer[0:MAX_DATA_SETS_PER_POST]\\n data_to_keep = self._data_buffer[MAX_DATA_SETS_PER_POST:]\\n\\n # Prepare data string with the values in data buffer\\n now = time.time()\\n data_string = '[' \\n for (timestamp, data) in data_to_send:\\n data_string += '['\\n data_string += str(round(timestamp-now,2))\\n for sample in data:\\n data_string += ','\\n data_string += str(sample)\\n data_string += '],'\\n # Remove trailing comma and close bracket\\n data_string = data_string[0:-1]+']'\\n\\n self._log.debug(\\\"Data string: \\\" + data_string)\\n \\n # Prepare URL string of the form\\n # 'http://domain.tld/emoncms/input/bulk.json?apikey=\\n # 12345&data=[[-10,10,1806],[-5,10,1806],[0,10,1806]]'\\n url_string = self._settings['protocol'] + self._settings['domain'] + \\\\\\n self._settings['path'] + \\\"/input/bulk_json?apikey=\\\" + \\\\\\n self._settings['apikey'] + \\\"&data=\\\" + data_string\\n self._log.debug(\\\"URL string: \\\" + url_string)\\n\\n # Send data to server\\n self._log.info(\\\"Sending to \\\" + \\n self._settings['domain'] + self._settings['path'])\\n try:\\n result = urllib2.urlopen(url_string, timeout=60)\\n except urllib2.HTTPError as e:\\n self._log.warning(\\\"Couldn't send to server, HTTPError: \\\" + \\n str(e.code))\\n except urllib2.URLError as e:\\n self._log.warning(\\\"Couldn't send to server, URLError: \\\" + \\n str(e.reason))\\n except httplib.HTTPException:\\n self._log.warning(\\\"Couldn't send to server, HTTPException\\\")\\n except Exception:\\n import traceback\\n self._log.warning(\\\"Couldn't send to server, Exception: \\\" + \\n traceback.format_exc())\\n else:\\n if (result.readline() == 'ok'):\\n self._log.debug(\\\"Send ok\\\")\\n # Send ok -> empty buffer\\n self._data_buffer = data_to_keep\\n return True\\n else:\\n self._log.warning(\\\"Send failure\\\")\",\n \"def giveHistoricalData(stockName):\\n now = datetime.datetime.fromtimestamp(getTime())\\n fiveDaysAgo = datetime.datetime.fromtimestamp(\\n getTime() - daysToSeconds(5)\\n )\\n\\n resp = json.dumps(\\n getHistoricalData(stockName, fiveDaysAgo)\\n )\\n return resp\",\n \"async def last_read(self):\\n try:\\n asyncio.set_event_loop(self.loop)\\n asyncio.get_event_loop().create_task(self.browse())\\n await self.browse()\\n\\n # parse the return reads and extract the most recent one\\n # (i.e. last not None)\\n jsonResponse = json.loads(self.raw_data)\\n lastRead = None\\n for read in jsonResponse['reads']:\\n if read['value'] is None:\\n break\\n lastRead = read\\n _LOGGER.debug(\\\"lastRead = %s\\\", lastRead)\\n\\n self.startTime = lastRead['startTime']\\n self.endTime = lastRead['endTime']\\n self.last_read_val = lastRead['value']\\n self.unit_of_measurement = jsonResponse['unit']\\n\\n _LOGGER.debug(\\\"last read = %s %s %s %s\\\", self.startTime, self.endTime, self.last_read_val, self.unit_of_measurement)\\n\\n return self.startTime, self.endTime, self.last_read_val, self.unit_of_measurement\\n except:\\n raise MeterError(\\\"Error requesting meter data\\\")\",\n \"def GetData(self):\\r\\n if self.Error == False:\\r\\n Extra = {}\\r\\n try:\\r\\n result = {}\\r\\n temp = self.ScrapeMainWebpage()\\r\\n if temp != None:\\r\\n result.update(temp)\\r\\n temp = self.ScrapeParameters1Webpage()\\r\\n if temp != None:\\r\\n result.update(temp)\\r\\n temp = self.ScrapeParameters2Webpage()\\r\\n if temp != None:\\r\\n result.update(temp)\\r\\n temp = self.ScrapeStatusWebpage()\\r\\n if temp != None:\\r\\n result.update(temp)\\r\\n sqlArray = {}\\r\\n sqlArray[self.deviceDescr] = {}\\r\\n sqlArray[self.deviceDescr][self.devNumber] = {}\\r\\n sqlArray[self.deviceDescr][self.devNumber][\\\"General\\\"] = result\\r\\n sqlArray[self.deviceDescr][self.devNumber][\\\"_ExtractInfo\\\"] = {}\\r\\n sqlArray[self.deviceDescr][self.devNumber][\\\"_ExtractInfo\\\"][\\\"ExtractTime\\\"] = time.time()\\r\\n sqlArray[\\\"ReadError\\\"] = False \\r\\n return sqlArray\\r\\n \\r\\n except Exception as e: \\r\\n self.log.printError(\\\"ERROR in Retreiving Seatel VSAT Data,%s Module Error\\\" % sys._getframe().f_code.co_name) \\r\\n self.log.printError( str(e))\\r\\n self.Error = True\\r\\n Extra[\\\"ReadError\\\"] = True\\r\\n return Extra\\r\\n else:\\r\\n self.log.printWarning(\\\"%s skipped due to previous failure\\\" % sys._getframe().f_code.co_name)\\r\\n return None\",\n \"def get_raw_data(self, dataset):\\n\\t\\tprint(\\\"Getting raw data for\\\", dataset)\\n\\t\\tself.raw_documents[dataset] = []\\n\\t\\tself.Y[dataset] = []\\n\\n\\t\\twith open(self.jsons[dataset]) as handle:\\n\\t\\t\\tfor line in handle:\\n\\t\\t\\t\\tjson_obj = json.loads(line)\\n\\t\\t\\t\\tstars = json_obj[\\\"stars\\\"]\\n\\t\\t\\t\\tif stars != 3:\\n\\t\\t\\t\\t\\tself.raw_documents[dataset].append(json_obj[\\\"text\\\"])\\n\\t\\t\\t\\t\\tself.Y[dataset].append(int(stars > 3))\",\n \"def request_realtime_info(self):\\n self.socket_datastream.sendto(b\\\"!r\\\", self.ip_port_arduino_datastream)\\n self.socket_datastream.sendto(b\\\"!s\\\", self.ip_port_arduino_datastream)\",\n \"def update_data():\\n values = temp_serial_placeholder()\\n time = current_time_milli() - __start\\n points = [ [time, values[0]], [time, values[1]] ]\\n __data.append(points)\\n return points\",\n \"def process_data(self, data):\\n parsed = json.loads(data)\\n current = parsed[\\\"current\\\"]\\n future = parsed[\\\"hourly\\\"]\\n current_res = self.get_columns(current)\\n self.database_conn(\\\"current\\\", -1, current_res)\\n for hour, data in enumerate(future):\\n current_res = self.get_columns(data)\\n self.database_conn(\\\"current\\\", hour, current_res)\",\n \"def get_data(stream_url, count, is_graph):\\n data = requests.get(stream_url + '/Data' + '?count=' + str(count) + '&Startindex=1970-01-01T00:00:00Z', headers=headers)\\n Values = []\\n for event in data.json():\\n Values.append(event['Value'])\\n if is_graph:\\n terminalplot.plot(range(len(Values)), Values)\\n else:\\n print(Values)\\n input(\\\"Press any key to continue...\\\")\\n return\",\n \"def _plot_data(self, data):\\r\\n # only send data if xqueue exists\\r\\n if self.capa_system.xqueue is None:\\r\\n return {'success': False, 'message': 'Cannot connect to the queue'}\\r\\n\\r\\n # pull relevant info out of get\\r\\n response = data['submission']\\r\\n\\r\\n # construct xqueue headers\\r\\n qinterface = self.capa_system.xqueue['interface']\\r\\n qtime = datetime.utcnow().strftime(xqueue_interface.dateformat)\\r\\n callback_url = self.capa_system.xqueue['construct_callback']('ungraded_response')\\r\\n anonymous_student_id = self.capa_system.anonymous_student_id\\r\\n # TODO: Why is this using self.capa_system.seed when we have self.seed???\\r\\n queuekey = xqueue_interface.make_hashkey(str(self.capa_system.seed) + qtime +\\r\\n anonymous_student_id +\\r\\n self.input_id)\\r\\n xheader = xqueue_interface.make_xheader(\\r\\n lms_callback_url=callback_url,\\r\\n lms_key=queuekey,\\r\\n queue_name=self.queuename)\\r\\n\\r\\n # construct xqueue body\\r\\n student_info = {\\r\\n 'anonymous_student_id': anonymous_student_id,\\r\\n 'submission_time': qtime\\r\\n }\\r\\n contents = {\\r\\n 'grader_payload': self.plot_payload,\\r\\n 'student_info': json.dumps(student_info),\\r\\n 'student_response': response\\r\\n }\\r\\n\\r\\n (error, msg) = qinterface.send_to_queue(header=xheader,\\r\\n body=json.dumps(contents))\\r\\n # save the input state if successful\\r\\n if error == 0:\\r\\n self.input_state['queuekey'] = queuekey\\r\\n self.input_state['queuestate'] = 'queued'\\r\\n self.input_state['queuetime'] = time.time()\\r\\n\\r\\n return {'success': error == 0, 'message': msg}\",\n \"def test_get_measurement_history(self):\\n device = DeviceFactory(node=Node.objects.first(), external_id='123', type__code=SecureDeviceType.SRT321,\\n device_param__type__code=SecureDeviceParameterType.MEASURED_TEMPERATURE)\\n d_id_1 = device.external_id\\n\\n now_loc = datetime.datetime.now(bst)\\n ts_loc = now_loc - datetime.timedelta(seconds=30)\\n ts_str = ts_loc.strftime('%Y-%m-%dT%H:%M:%S')\\n\\n data = self.create_secure_server_push_data(d_id_1, ts_str)\\n\\n SecureClient.process_push_data(data)\\n time.sleep(.5)\\n\\n # get newer timestamp\\n ts_str = now_loc.strftime('%Y-%m-%dT%H:%M:%S')\\n data = self.create_secure_server_push_data(d_id_1, ts_str, value=\\\"23.5\\\")\\n\\n SecureClient.process_push_data(data)\\n\\n token = Token.objects.get(user__username=email)\\n device_param = device.parameters.first()\\n client = APIClient()\\n client.credentials(HTTP_AUTHORIZATION='Token ' + token.key)\\n url = reverse('api:device_measurements', kwargs={'device_parameter_id': device_param.id})\\n\\n time.sleep(.5)\\n\\n response = client.get(url, format='json')\\n\\n self.assertTrue(response.status_code == 200)\\n self.assertTrue(len(response.data) >= 2)\",\n \"def get_com_data(self):\\n self.form_url_str()\\n if self.__print_url: print self.com_data_full_url\\n self.download_json()\\n self.get_datalist_fr_json()\",\n \"def measurements():\\n print(\\\"server received request for precipitation data...\\\")\\n return jsonify(measurements_data)\",\n \"def read_live_data(wearable_port):\\r\\n IMU1_num = []\\r\\n IMU2_num = []\\r\\n IMU3_num = []\\r\\n\\r\\n try:\\r\\n wearable = serial.Serial(wearable_port, baudrate=115200, timeout=5)\\r\\n #arduino = serial.Serial(arduino_port, timeout=1)\\r\\n # Delay for 2 seconds to wait for serial port to be ready.\\r\\n print(\\\"Waiting 2 seconds for serial to be ready.\\\")\\r\\n time.sleep(2)\\r\\n except Exception as e:\\r\\n print(e)\\r\\n print('Please check the port')\\r\\n return\\r\\n\\r\\n input(\\\"Press Enter to continue...\\\")\\r\\n str(wearable.write(bytes(33)))\\r\\n # Open file to store the data; filename includes date and time; format: data-YYYYMMDDHHmmss.csv\\r\\n filename = \\\"data-\\\" + str(dt.datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")) + \\\".csv\\\"\\r\\n filenamplot = \\\"plot-\\\" + str(dt.datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")) + \\\".png\\\"\\r\\n print(\\\"Opening %s\\\" % filename)\\r\\n f = open(filename, \\\"a+\\\")\\r\\n # f.write(\\\"power,rpm\\\\n\\\")\\r\\n count = 1000\\r\\n # Get data and continuously yield Power and RPM as integers\\r\\n\\r\\n while (count >0):\\r\\n count = count -1\\r\\n #if arduino.in_waiting > 0:\\r\\n wearable.flushInput()\\r\\n\\r\\n '''\\r\\n arduino_output = arduino.readline().decode(\\\"utf_8\\\", \\\"strict\\\")\\r\\n print(\\\"Distance: %s\\\" % arduino_output)\\r\\n f.writelines(\\\"%s\\\" % arduino_output)\\r\\n if arduino_output == \\\"Hard Stop\\\\r\\\\n\\\":\\r\\n break\\r\\n arduino_output = arduino_output.replace(\\\"\\\\r\\\\n\\\", \\\"\\\")\\r\\n Distance.append(int(float(arduino_output)))\\r\\n '''\\r\\n\\r\\n try:\\r\\n data = wearable.readline().decode(\\\"utf_8\\\", \\\"strict\\\")\\r\\n data = data.replace(\\\"\\\\r\\\\n\\\", \\\"\\\\n\\\").split()\\r\\n IMU1= data[2].replace(\\\"\\\\n\\\", \\\"\\\")\\r\\n IMU1_num.append(int(IMU1))\\r\\n IMU2 = data[3].replace(\\\"\\\\n\\\", \\\"\\\")\\r\\n IMU2_num.append(int(IMU2))\\r\\n IMU3 = data[4].replace(\\\"\\\\n\\\", \\\"\\\")\\r\\n IMU3_num.append(int(IMU3))\\r\\n print(\\\"IMU1: %s\\\\t IMU2: %s\\\\t IMU3: %s\\\\t\\\" % (IMU1, IMU2, IMU3))\\r\\n f.writelines(\\\"%s,%s,%s,%s\\\\n\\\" % (IMU1, IMU2, IMU3))\\r\\n yield int(IMU1), int(IMU2), int(IMU3)\\r\\n except Exception as e:\\r\\n print('error')\\r\\n f.writelines(\\\"Error\\\\n\\\")\\r\\n\\r\\n print('Program ended.')\\r\\n t = numpy.linspace(1, len(IMU1_num), len(IMU1_num))\\r\\n fig, (ax1) = plt.subplots(nrows=1, ncols=1, figsize=(16.0, 9.0)) # create figure & 1 axis\\r\\n ax1.plot(t, IMU1_num, t, IMU2_num,t, IMU3_num)\\r\\n ax1.set_title('IMU')\\r\\n ax1.legend(('IMU1', 'IMU2', 'IMU3'))\\r\\n # manager = plt.get_current_fig_manager()\\r\\n # manager.resize(*manager.window.maxsize())\\r\\n fig.savefig(filenamplot)\\r\\n plt.show()\\r\\n\\r\\n f.close()\\r\\n #arduino.close()\\r\\n wearable.close()\",\n \"def loop(self) -> None:\\n while True:\\n # Sleep before running code to ensure that the sensor is\\n # initialized on first run, as per the specifications.\\n sleep(config.SLEEP)\\n\\n self.setup_quiet_hours()\\n\\n if self.quiet_setup:\\n if self.in_quiet_hours():\\n if config.DC_QH:\\n self.sensor.close()\\n self.sleep_quiet_hours()\\n continue\\n\\n # In the case that quiet hours were established during first run\\n # and removed from the endpoint afterwards, the sensor may not\\n # be in the open state. Because serial.Serial.open() may raise\\n # an exception if the sensor is already open, just check prior.\\n if not self.sensor.isOpen():\\n self.sensor.open()\\n\\n config.LOGGER.info('Woke up after sleeping. Running loop()')\\n self.data = []\\n for _ in range(10):\\n datum = self.sensor.read()\\n self.data.append(datum)\\n\\n for pm, start in self._SLICES.items():\\n # Might be necessary to give the endpoint some time\\n # between responses\\n sleep(10)\\n reading = self.read_data_from_bytes(start)\\n aq_dict = air_quality.AQS[pm].get_range(reading)\\n\\n sections = [\\n {\\n 'type': 'text',\\n 'color': aq_dict['color'],\\n 'value': f'Quality: {aq_dict[\\\"label\\\"]}'\\n },\\n {\\n 'type': 'gauge',\\n 'color': [aq_dict['color']],\\n 'range': [aq_dict['lower'], aq_dict['upper']],\\n 'value': reading,\\n },\\n {\\n 'type': 'gauge',\\n 'color': air_quality.COLORS,\\n 'range': air_quality.AQS[pm].get_all_ranges(),\\n 'value': reading,\\n }\\n ]\\n\\n data = {\\n 'module': f'photo-dash-sds011-pm{pm}',\\n 'title': f'Air Quality - PM{pm}',\\n 'sections': sections,\\n }\\n\\n try:\\n r = requests.put(config.ENDPOINT, json=data)\\n except Exception as e: # Catching broad Exceptions for now\\n config.LOGGER.error(e)\\n config.LOGGER.info(r.status_code)\",\n \"def get_data(last):\\n Table = \\\"ServerRoom\\\"\\n filter = \\\"\\\"\\n if last == \\\"lastone\\\":\\n data = request_meteodata(\\\"SELECT * from `ServerRoom` ORDER BY id DESC LIMIT 1 \\\")\\n if len(data) == 0:\\n return [SensorData(datetime.datetime.now(), 0, 0)]\\n res = []\\n for d in data:\\n res.append(SensorData(d[1], d[2], d[3]))\\n return res\\n if last != \\\"All\\\":\\n limit = datetime.datetime.now().astimezone(utz)\\n if last == \\\"24hours\\\":\\n limit -= datetime.timedelta(hours=24)\\n else:\\n limit = limit.replace(hour=0, minute=0, second=0, microsecond=0)\\n if last == \\\"3days\\\":\\n limit -= datetime.timedelta(days=3)\\n elif last == \\\"7days\\\":\\n limit -= datetime.timedelta(days=7)\\n elif last == \\\"month\\\":\\n limit = limit.replace(day=1)\\n elif last == \\\"30days\\\":\\n limit -= datetime.timedelta(days=30)\\n elif last == \\\"year\\\":\\n limit = limit.replace(day=1, month=1)\\n filter = \\\" WHERE `date` > '\\\" + str(limit) + \\\"'\\\"\\n order = \\\" ORDER BY `date` ASC\\\"\\n req = \\\"SELECT * FROM `\\\" + Table + \\\"`\\\" + filter + order\\n data = request_meteodata(req)\\n if len(data) == 0:\\n print(\\\"no data: get all\\\")\\n req = \\\"SELECT * FROM `\\\" + Table + \\\"`\\\" + order\\n data = request_meteodata(req)\\n res = []\\n for d in data:\\n res.append(SensorData(d[1], d[2], d[3]))\\n return res\",\n \"def pull_data(stop_event):\\r\\n logger = logging.getLogger(__name__)\\r\\n\\r\\n # List of current formats supported\\r\\n currency_list = ['https://www.bitstamp.net/api/v2/ticker_hour/btceur', 'https://www.bitstamp.net/api/v2/ticker_hour/btcusd',\\r\\n 'https://www.bitstamp.net/api/v2/ticker_hour/ethusd', 'https://www.bitstamp.net/api/v2/ticker_hour/etheur']\\r\\n\\r\\n # Loop until told otherwise!\\r\\n while not stop_event.is_set():\\r\\n for currency in currency_list:\\r\\n res = requests.get(currency)\\r\\n try:\\r\\n res.raise_for_status()\\r\\n except requests.exceptions.HTTPError as e:\\r\\n # Not 200\\r\\n logger.error(str(e))\\r\\n continue\\r\\n\\r\\n # Get the end characters to dertermine the type e.g. btceur, ethusd, etc...\\r\\n currency_type = (currency.rpartition('/')[-1])\\r\\n logger.info('The Curreny type: ' + currency_type)\\r\\n\\r\\n if currency_type == 'btceur':\\r\\n table = 'btceur'\\r\\n elif currency_type == 'btcusd':\\r\\n table = 'btcusd'\\r\\n elif currency_type == 'ethusd':\\r\\n table = 'ethusd'\\r\\n elif currency_type == 'etheur':\\r\\n table = 'etheur'\\r\\n else:\\r\\n table = None\\r\\n\\r\\n # Extract Data and Fields\\r\\n data = res.json()\\r\\n field_list = data.keys()\\r\\n logger.info(field_list)\\r\\n value_list = data.values()\\r\\n logger.info(value_list)\\r\\n\\r\\n # Write to DB\\r\\n db_commit(table, field_list, value_list)\\r\\n # Cannot make more than 600 requests per 10 minutes or they will ban your IP address.\\r\\n # Will in time get real time using their websocket API.\\r\\n time.sleep(5)\",\n \"def loadData(self):\\r\\n self.samplerate = self.app.samplerate\\r\\n self.sensors = self.app.sensors\\r\\n self.sensorMask = self.app.sensorMask\\r\\n self.measurements = self.app.measurements\\r\\n\\r\\n # Get min and max data points\\r\\n for sens in self.sensor_ids:\\r\\n try:\\r\\n for i in range(1,self.measurements):\\r\\n if float(self.app.data[i][sens].text) < self.sensor_range[0]:\\r\\n self.sensor_range[0] = float(self.app.data[i][sens].text)\\r\\n elif float(self.app.data[i][sens].text) > self.sensor_range[1]:\\r\\n self.sensor_range[1] = float(self.app.data[i][sens].text)\\r\\n except:\\r\\n print(self.app.data)\\r\\n \\r\\n # Set x scale from 0 to end of track\\r\\n self.scalex = [0,self.measurements]\\r\\n## self.scalex = [0,self.w/2]\\r\\n # Set y scale to maximum sensor measurement\\r\\n self.setScaleY(self.sensor_range[0], self.sensor_range[1])\",\n \"def get_data(self):\\n\\n self.set_query_string()\\n self.realtime_data = super().get_data()\\n self.set_coordinate()\\n return self.realtime_data\",\n \"def get_json(self):\\r\\n self.get_recordrange()\\r\\n [\\r\\n self.json_data.setter(n, self.get_data(\\\"json\\\", x))\\r\\n for n, x in enumerate(tqdm(self.iterlist))\\r\\n ]\",\n \"def getDataParsed():\\r\\n serialConsole.flush()\\r\\n rawData = serialConsole.readline().decode(\\\"utf-8\\\").rstrip()\\r\\n parsedJson = json.loads(rawData)\\r\\n return parsedJson\",\n \"def test():\\n temp_data = fetch_temp_data(\\n (\\\"https://opendata-download-metobs.smhi.se/api/version/\\\" +\\n \\\"latest/parameter/1/station/52350/period/latest-day/data.json\\\"))\\n data = temp_series(temp_data)\\n print(data)\",\n \"def plot(accessToken, collection):\\n \\n plt.xlabel('Date/Time')\\n plt.ylabel('Sensor Value')\\n plt.title(\\\"Sensors Monitor\\\")\\n \\n # to save png files\\n i = 0\\n \\n # set interactive mode on\\n plt.ion()\\n \\n # set figure to full screen\\n mng = plt.get_current_fig_manager()\\n mng.full_screen_toggle()\\n\\n while True:\\n jsondata = getJsonData(accessToken)\\n if jsondata:\\n #limit date string\\n jsondata[DATE] = jsondata[DATE][8:13]\\n appendJsonData(jsondata, collection)\\n \\n # clear figure\\n plt.clf()\\n \\n # limit samples to be viewed\\n if (len(collection[DATE]) > SAMPLE_SIZE_LIMIT):\\n plt.xticks(range(SAMPLE_SIZE_LIMIT), collection[DATE][-SAMPLE_SIZE_LIMIT:])\\n plt.plot(collection[SENSOR1][-SAMPLE_SIZE_LIMIT:], 'k', label='sensor 1')\\n plt.plot(collection[SENSOR2][-SAMPLE_SIZE_LIMIT:], 'b', label='sensor 2')\\n plt.plot(collection[SENSOR3][-SAMPLE_SIZE_LIMIT:], 'g', label='sensor 3')\\n plt.plot(collection[SENSOR4][-SAMPLE_SIZE_LIMIT:], 'r', label='sensor 4')\\n else:\\n plt.xticks(range(len(collection[DATE])), collection[DATE])\\n plt.plot(collection[SENSOR1], 'k', label='sensor 1')\\n plt.plot(collection[SENSOR2], 'b', label='sensor 2')\\n plt.plot(collection[SENSOR3], 'g', label='sensor 3')\\n plt.plot(collection[SENSOR4], 'r', label='sensor 4')\\n \\n plt.legend(loc='upper left')\\n plt.show()\\n \\n # Take a screenshot on Gnome desktop\\n if os.environ.get(\\\"XDG_MENU_PREFIX\\\").startswith(\\\"gnome\\\"):\\n os.system(\\\"gnome-screenshot -f screenshot{}.png\\\".format(i))\\n i = i+1\\n \\n #plt.pause(1)\\n plt.pause(60*60) # one hour\\n else:\\n print(str(datetime.datetime.now()) + \\\" Empty json data\\\")\",\n \"def getSamples(self,limit=None):\\n theseReadings = self.readings\\n if limit:\\n theseReadings = theseReadings[:limit]\\n return [x.asJSON() for x in theseReadings]\",\n \"def readData(self, duration_s, toV=True, maxAI=1024, maxV=5.0,\\n updateFunc=None, nPntsUpdate=1, trigger=[]):\\n isDone = False\\n nLines = 0\\n empty = numpy.array([])\\n \\n if self.rate_ms >= 0:\\n nPnts = round(duration_s *1000.0 /self.rate_ms)\\n print(\\\"{0:.3f} s duration = {1} samples\\\".format(duration_s, nPnts))\\n else: \\n nPnts = 100\\n print(\\\"Sample rate invalid, {0} samples will be recorded\\\".format(nPnts))\\n\\n if not(self.isOpen): \\n print(\\\"ERROR: Link not open\\\")\\n return (-1, empty, empty, empty)\\n \\n # Create empty arrays for the data\\n #\\n np_data_0 = numpy.zeros([nPnts], dtype=float)\\n np_data_1 = numpy.zeros([nPnts], dtype=float)\\n np_data_t = numpy.zeros([nPnts], dtype=float)\\n np_dt_ms = numpy.zeros([nPnts], dtype=float)\\n \\n # Attempt to read data\\n #\\n while not(isDone):\\n # Read a line\\n #\\n (errC, parts) = self.__readLine()\\n if not(errC == 0):\\n return (errC, empty, empty, empty)\\n \\n else: \\n np_data_0[nLines] = float(parts[2])\\n np_data_1[nLines] = float(parts[3])\\n np_data_t[nLines] = float(parts[0])/1000.0\\n np_dt_ms[nLines] = float(parts[1]) /1000.0\\n \\\"\\\"\\\"\\n print(\\\"{0:.3f} {1} {2}\\\".format(int(parts[0])/1000.0, \\n int(parts[2]), int(parts[3])))\\n \\\"\\\"\\\"\\n # Update plot of data, if requested\\n #\\n if updateFunc and ((nLines % nPntsUpdate) == 0):\\n updateFunc(nLines, np_data_t[nLines], np_data_0[nLines], \\n np_data_1[nLines])\\n \\n if nLines < (nPnts-1):\\n sys.stdout.write(\\\"\\\\r{0:.0f}% {1:.3f} s: {2:.3f} {3:.3f} ...\\\"\\n .format(nLines/float(nPnts) *100, \\n np_data_t[nLines]/1000.0,\\n np_data_0[nLines], np_data_1[nLines]))\\n else: \\n sys.stdout.write(\\\"\\\\r100% done\\\" +\\\" \\\"*40 +\\\"\\\\n\\\")\\n \\n nLines += 1\\n isDone = (nLines == nPnts)\\n \\n print(\\\"SUCCESS\\\") \\n print(\\\"{0} data points recorded\\\".format(nLines))\\n print(\\\"Rate = {0:.3f} +/- {1:.3f} ms\\\".format(numpy.mean(np_dt_ms), \\n numpy.std(np_dt_ms)))\\n\\n if toV: \\n np_data_0 = np_data_0 /float(maxAI -1) *maxV\\n np_data_1 = np_data_1 /float(maxAI -1) *maxV\\n \\n return (0, np_data_t, np_data_0, np_data_1)\",\n \"def collect_data(self):\\n self.lines = []\\n\\n while True:\\n self._process_serial_data()\",\n \"def update(self):\\r\\n mc = self._motor_controllers[0]\\r\\n lj = self._labjacks[0]\\r\\n r = None\\r\\n\\r\\n lj._finished = False\\r\\n errors = 0\\r\\n missed = 0\\r\\n # Read from Queue until there is no data.\\r\\n try:\\r\\n # get([block[, timeout]])¶\\r\\n # Remove and return an item from the queue. If optional\\r\\n # args block is true and timeout is None (the default),\\r\\n # block if necessary until an item is available. If timeout\\r\\n # is a positive number, it blocks at most timeout seconds\\r\\n # and raises the Empty exception if no item was available\\r\\n # within that time. Otherwise (block is false), return an\\r\\n # item if one is immediately available, else raise the\\r\\n # Empty exception (timeout is ignored in that case).\\r\\n # Pull results out of the Queue in a blocking manner.\\r\\n result = lj.raw_data.get(False) # (True, 0.0001)\\r\\n if result[\\\"errors\\\"] != 0:\\r\\n errors += result[\\\"errors\\\"]\\r\\n missed += result[\\\"missed\\\"]\\r\\n logging.warning(\\r\\n \\\"Total Errors: {}, Total Missed: \\\"\\r\\n \\\"{}\\\".format(errors, missed),\\r\\n extra=self.extra)\\r\\n # Convert the raw bytes (result['result']) to voltage data.\\r\\n r = lj.device.processStreamData(result['result'])\\r\\n lj.raw_data.task_done()\\r\\n lj.raw_data_ready.clear()\\r\\n except lj.raw_data.Empty:\\r\\n if lj._finished:\\r\\n logging.info(\\\"Done reading from the Queue.\\\", extra=self.extra)\\r\\n else:\\r\\n logging.error(\\\"Queue is empty. Stopping...\\\", extra=self.extra)\\r\\n lj._finished = True\\r\\n except Exception as e:\\r\\n logging.error(\\\"{}: {}\\\".format(e), extra=self.extra)\\r\\n lj._finished = True\\r\\n\\r\\n with lj.raw_data.mutex:\\r\\n lj.raw_data.queue.clear()\\r\\n current_time = self._times[-1] + self._dt\\r\\n self._times.append(current_time)\\r\\n self._data[\\\"time (s)\\\"] = self._times\\r\\n\\r\\n for s in lj.sensors():\\r\\n name = '{} {} ({})'.format(s.parent().name,\\r\\n s.name,\\r\\n s.signal.units)\\r\\n if r is not None:\\r\\n # Get the average, make sure the length of the list\\r\\n # is a float for float division.\\r\\n voltage = (\\r\\n (sum(r[AIN.upper() + str(s.channel)]) /\\r\\n float(len(r[AIN.upper() + str(s.channel)])))\\r\\n )\\r\\n # convert to physical quantity\\r\\n v = Q_(np.asarray([voltage]), 'V')\\r\\n if s.name == 'p1':\\r\\n quantity = convert_pressure_px119(\\r\\n v, r_shunt=Q_(470.0, 'ohm'),\\r\\n value_range=Q_(np.array([0, 30]), 'psi'), zero=Q_(1.375, 'kPa')\\r\\n ).magnitude[0]\\r\\n elif s.name == 'p2':\\r\\n quantity = convert_pressure_px119(\\r\\n v, r_shunt=Q_(470.0, 'ohm'),\\r\\n value_range=Q_(np.array([0, 30]), 'psi'), zero=Q_(1.7, 'kPa')\\r\\n ).magnitude[0]\\r\\n elif s.name == 'p3':\\r\\n quantity = convert_pressure_px119(\\r\\n v, r_shunt=Q_(470.0, 'ohm'),\\r\\n value_range=Q_(np.array([0, 30]), 'psi'), zero=Q_(1.85, 'kPa')\\r\\n ).magnitude[0]\\r\\n elif s.name == 'T1':\\r\\n # logging.debug(\\\"T sensor voltage {}\\\".format(v[0]), extra=self.extra)\\r\\n quantity = convert_temperature_rtd(\\r\\n v, v_in=Q_(2.5, 'V'),\\r\\n r1=Q_(100., 'ohm'), filename='pt100.txt', zero=Q_(0.29, 'degC')\\r\\n ).magnitude[0]\\r\\n elif s.name == 'T2':\\r\\n # logging.debug(\\\"T sensor voltage {}\\\".format(v[0]), extra=self.extra)\\r\\n quantity = convert_temperature_rtd(\\r\\n v, v_in=Q_(2.5, 'V'),\\r\\n r1=Q_(100., 'ohm'), filename='pt100.txt', zero=Q_(-0.05, 'degC')\\r\\n ).magnitude[0]\\r\\n elif s.name == 'T3':\\r\\n # logging.debug(\\\"T sensor voltage {}\\\".format(v[0]), extra=self.extra)\\r\\n quantity = convert_temperature_rtd(\\r\\n v, v_in=Q_(2.5, 'V'),\\r\\n r1=Q_(100., 'ohm'), filename='pt100.txt'\\r\\n ).magnitude[0]\\r\\n elif s.name == 'T4':\\r\\n # logging.debug(\\\"T sensor voltage {}\\\".format(v[0]), extra=self.extra)\\r\\n quantity = convert_temperature_rtd(\\r\\n v, v_in=Q_(2.5, 'V'),\\r\\n r1=Q_(100., 'ohm'), filename='pt100.txt'\\r\\n ).magnitude[0]\\r\\n elif s.name == 'frate': # flow rate\\r\\n # logging.debug(\\\"magmeter voltage {}\\\".format(v[0]), extra=self.extra)\\r\\n quantity = convert_flow_rate_magmeter(\\r\\n v, r_shunt=Q_(465.2, 'ohm'),\\r\\n value_range=Q_(np.array([0, 80]), 'l/min')\\r\\n ).magnitude[0]\\r\\n if quantity < 0.0:\\r\\n quantity = 0.0\\r\\n else:\\r\\n quantity = voltage\\r\\n s.signal.field.setText('{:3.1f}'.format(quantity))\\r\\n self._data[name].append(quantity)\\r\\n\\r\\n for i, m in enumerate(mc.children()):\\r\\n if m is not None:\\r\\n mc.r_lock.acquire()\\r\\n for s in m.sensors():\\r\\n value = s.read()\\r\\n name = '{} {} ({})'.format(s.parent().name,\\r\\n s.name,\\r\\n s.signal.units)\\r\\n s.signal.field.setText('{:3.2f}'.format(value))\\r\\n self._data[name].append(value)\\r\\n mc.r_lock.release()\\r\\n d = {}\\r\\n for k, v in self._data.items():\\r\\n d[k] = '{:3.10f}'.format(v[-1])\\r\\n self._csv_writer.writerow(d)\\r\\n self._line_plot.setData(self._times, self._data[self._signal])\",\n \"async def _get_data(self):\\n coros = []\\n results = []\\n for series_ids in self.series_ids:\\n response = self._post(data={\\\"series_id\\\": series_ids})\\n coros.append(response)\\n if len(coros) == 5: # throttle at 5\\n _ = await asyncio.gather(*coros)\\n results.extend(_)\\n coros = [] # Reset accumulator\\n if coros:\\n results.extend(await asyncio.gather(*coros))\\n\\n return filter(None, results)\",\n \"def sensor_history(self, sensor_name, start_time_sec, end_time_sec,\\n include_value_ts=False, timeout_sec=0):\\n\\n if timeout_sec != 0:\\n self._logger.warn(\\n \\\"timeout_sec is no longer supported. Default tornado timeout is used\\\")\\n\\n params = {\\n 'sensor': sensor_name,\\n 'start_time': start_time_sec,\\n 'end_time': end_time_sec,\\n 'limit': MAX_SAMPLES_PER_HISTORY_QUERY,\\n 'include_value_time': include_value_ts\\n }\\n\\n url = url_concat(\\n (yield self.get_sitemap())['historic_sensor_values'] + '/query', params)\\n self._logger.debug(\\\"Sensor history request: %s\\\", url)\\n response = yield self._http_client.fetch(url)\\n data_json = json.loads(response.body)\\n if 'data' not in data_json:\\n raise SensorHistoryRequestError(\\\"Error requesting sensor history: {}\\\"\\n .format(response.body))\\n data = []\\n for item in data_json['data']:\\n if 'value_time' in item:\\n sample = SensorSampleValueTime(item['sample_time'],\\n item['value_time'],\\n item['value'],\\n item['status'])\\n else:\\n sample = SensorSample(item['sample_time'],\\n item['value'],\\n item['status'])\\n data.append(sample)\\n result = sorted(data, key=_sort_by_sample_time)\\n raise tornado.gen.Return(result)\",\n \"def get_data_logic():\\r\\n global input_exchange\\r\\n global input_symbols\\r\\n global all_symbols\\r\\n global input_timeframe\\r\\n\\r\\n # create exchange connection\\r\\n exchange = Exchange(input_exchange)\\r\\n\\r\\n # perform check that exchange can grab price data\\r\\n if exchange.connection.has['fetchOHLCV']:\\r\\n\\r\\n # user ticked 'All Symbols?', so includes all symbols in\\r\\n # exchange_tickers.py for the particular exchange\\r\\n if all_symbols:\\r\\n symbol_list = SymbolList(symbols='auto', exchange=exchange)\\r\\n # user didn't tick 'All Symbols?', so create unpopulated symbol list\\r\\n else:\\r\\n symbol_list = SymbolList(exchange=exchange)\\r\\n # add all symbols user inputted\\r\\n for s in input_symbols:\\r\\n symbol_list.input_symbol(s)\\r\\n\\r\\n # get auto timeframe and check it is valid\\r\\n timeframe = Timeframe(timeframe=input_timeframe, exchange=exchange)\\r\\n while not timeframe.check_timeframe():\\r\\n timeframe.input_timeframe() # default to asking for input\\r\\n\\r\\n print(f\\\"Pulling data on the {timeframe.tf} timeframe for...\\\")\\r\\n print(symbol_list.symbols)\\r\\n\\r\\n # get current time in UTC in milliseconds\\r\\n now = datetime.now().astimezone(pytz.timezone('UTC'))\\r\\n now = int(now.timestamp()*1000)\\r\\n\\r\\n # loop over each symbol and pull new data\\r\\n for sym in symbol_list.symbols:\\r\\n # create csv filename and path\\r\\n file_sym = sym.replace('/', '')\\r\\n file_sym = file_sym.replace('-', '')\\r\\n filename = f\\\"{exchange.name}_{file_sym}_{timeframe.tf}.csv\\\" # generate filename from given information\\r\\n csv_path = f\\\"{exchange.name}/{timeframe.tf}/{filename}\\\"\\r\\n\\r\\n # get most recent price data and append it to existing data\\r\\n # (if it exists)\\r\\n price_data = PriceData(exchange=exchange, tf=timeframe.tf,\\r\\n sym=sym, now=now, path=csv_path)\\r\\n\\r\\n # check if price data csv already exists\\r\\n if price_data.exists():\\r\\n price_data.get_current()\\r\\n # get new data as far back as possible if csv does not exist\\r\\n else:\\r\\n price_data.get_new()\\r\\n\\r\\n # keep updating price_data until current time\\r\\n price_data.update()\\r\\n\\r\\n # write to csv\\r\\n price_data.write()\\r\\n\\r\\n print(\\\"Finished writing files!\\\")\",\n \"def main():\\n data_file = 'shrec_timer.json'\\n\\n if len(sys.argv) == 2:\\n generate_data(data_file, sys.argv[1])\\n\\n plot_data(data_file)\",\n \"def startDataAcq(self):\\r\\n\\t\\tglobal payload, control, output_settings, serials, datfiles\\r\\n\\t\\t# INITIALIZE THE OUTPUT FOLDER STRUCTURE\\r\\n\\t\\tcheck_dir(output_settings['folder'], output_settings['cruise'], payload)\\r\\n\\t\\tconfirm_dir(output_settings['folder'], output_settings['cruise'])\\r\\n\\t\\t# FIND THE START TIME\\r\\n\\t\\toutput_settings['start_time'] = init_time()\\r\\n\\t\\t# PRINT THE START TIME\\r\\n\\t\\tprint_spacer()\\r\\n\\t\\tprint 'Local Time: ', time.ctime(output_settings['start_time'])\\r\\n\\t\\tprint 'UTC: ', time.asctime(time.gmtime(output_settings['start_time']))\\r\\n\\t\\t\\r\\n\\t\\t# LOOP THROUGH THE SCIENTIFIC PAYLOAD\\r\\n\\t\\tfor k in payload.keys():\\r\\n\\t\\t\\ttry:\\r\\n\\t\\t\\t\\tif serials[k].isOpen():\\r\\n\\t\\t\\t\\t\\tclose_serial(serials[k])\\r\\n\\t\\t\\texcept KeyError:\\r\\n\\t\\t\\t\\tprint ' '\\r\\n\\t\\t\\t\\t# print 'Serial port connected to '+k+' was not previously open.'\\r\\n\\t\\t\\t# open the serial port\\r\\n\\t\\t\\tserials[k] = init_serial(payload[k])\\r\\n\\t\\t\\tif serials[k].isOpen():\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t# print the serial info\\r\\n\\t\\t\\t\\tprint 'Receiving data from '+k\\r\\n\\t\\t\\t\\t# initialize the data file\\r\\n\\t\\t\\t\\tdatfiles[k] = init_datafile(output_settings, payload[k])\\r\\n\\t\\t\\t\\t# read one line because the first one after opening a port is usually gibberish\\r\\n\\t\\t\\t\\tline = serials[k].readline()\\r\\n\\t\\t\\telse: \\r\\n\\t\\t\\t\\tprint 'Unable to connect to serial port '+payload[k]['port']+' connected to '+k\\r\\n\\t\\t\\t# pause get everything setup\\r\\n\\t\\t\\ttime.sleep(1)\\r\\n\\t\\t# start the loop \\r\\n\\t\\tcontrol.combine()\",\n \"async def get_api_data(self) -> dict:\\n if not self.bos.is_set():\\n self.lit = False\\n return self.messages\\n try:\\n # get all data and split it up\\n all_data = await self.send_api_cmd(\\\"devs+temps+fans\\\")\\n devs_raw = all_data['devs'][0]\\n temps_raw = all_data['temps'][0]\\n fans_raw = all_data['fans'][0]\\n\\n # parse temperature data\\n temps_data = {}\\n for board in range(len(temps_raw['TEMPS'])):\\n temps_data[f\\\"board_{temps_raw['TEMPS'][board]['ID']}\\\"] = {}\\n temps_data[f\\\"board_{temps_raw['TEMPS'][board]['ID']}\\\"][\\\"Board\\\"] = temps_raw['TEMPS'][board]['Board']\\n temps_data[f\\\"board_{temps_raw['TEMPS'][board]['ID']}\\\"][\\\"Chip\\\"] = temps_raw['TEMPS'][board]['Chip']\\n\\n # parse individual board and chip temperature data\\n for board in temps_data.keys():\\n if \\\"Board\\\" not in temps_data[board].keys():\\n temps_data[board][\\\"Board\\\"] = 0\\n if \\\"Chip\\\" not in temps_data[board].keys():\\n temps_data[board][\\\"Chip\\\"] = 0\\n\\n # parse hashrate data\\n hr_data = {}\\n for board in range(len(devs_raw['DEVS'])):\\n hr_data[f\\\"board_{devs_raw['DEVS'][board]['ID']}\\\"] = {}\\n hr_data[f\\\"board_{devs_raw['DEVS'][board]['ID']}\\\"][\\\"HR\\\"] = round(\\n devs_raw['DEVS'][board]['MHS 5s'] / 1000000,\\n 2)\\n\\n # parse fan data\\n fans_data = {}\\n for fan in range(len(fans_raw['FANS'])):\\n fans_data[f\\\"fan_{fans_raw['FANS'][fan]['ID']}\\\"] = {}\\n fans_data[f\\\"fan_{fans_raw['FANS'][fan]['ID']}\\\"]['RPM'] = fans_raw['FANS'][fan]['RPM']\\n\\n # set the miner data\\n miner_data = {'IP': self.ip, \\\"Light\\\": \\\"show\\\", 'Fans': fans_data, 'HR': hr_data, 'Temps': temps_data}\\n\\n # save stats for later\\n self.stats = miner_data\\n\\n # return stats\\n return miner_data\\n except:\\n # if it fails, return install data\\n # usually fails on getting None from API\\n self.lit = False\\n data = self.messages\\n data['Light'] = \\\"show\\\"\\n return data\",\n \"def run(self):\\n\\n if self.transport == 'any':\\n devs = kromek.discover()\\n else:\\n devs = kromek.discover(self.transport)\\n\\n print('Discovered %s' % devs)\\n\\n if len(devs) <= 0:\\n return\\n\\n filtered = []\\n\\n for dev in devs:\\n if self.device == 'all' or dev[0] in self.device:\\n filtered.append(dev)\\n\\n devs = filtered\\n if len(devs) <= 0:\\n return\\n\\n done_devices = set()\\n try:\\n while self.running:\\n print(\\\"Plot_manager.run: getting data\\\")\\n with kromek.Controller(devs, self.interval) as controller:\\n for reading in controller.read():\\n if self.create_structures:\\n self.total = np.array(reading[4])\\n self.lst = np.array([reading[4]])\\n self.create_structures = False\\n else:\\n self.total += np.array(reading[4])\\n self.lst = np.concatenate(\\n (self.lst, [np.array(reading[4])]))\\n serial = reading[0]\\n dev_count = reading[1]\\n if serial not in done_devices:\\n this_start, this_end = self.get_interval(\\n time.time() - self.interval)\\n\\n self.handle_spectra(\\n this_start, this_end, reading[4])\\n if dev_count >= self.count > 0:\\n done_devices.add(serial)\\n controller.stop_collector(serial)\\n if len(done_devices) >= len(devs):\\n break\\n except KeyboardInterrupt:\\n self.vprint(1, '\\\\nKeyboardInterrupt: stopping Manager run')\\n self.takedown()\\n except SystemExit:\\n self.vprint(1, '\\\\nSystemExit: taking down Manager')\\n self.takedown()\",\n \"def receive_data(self):\\n while True:\\n\\n data = self.recv_end()\\n\\n if len(data) > 0:\\n\\n try:\\n self.current_data = json.loads(data)\\n self.current_3D_points = base64.b64decode(self.current_data['points'])\\n self.is_new_data = True\\n\\n except:\\n # print('cannot load DepthCamera data')\\n pass\",\n \"def get_data(self):\\n logging.info(\\n \\\"[IEXIntervalDataSource] started: fetching every %d seconds\\\",\\n self._interval,\\n )\\n\\n def _get(self):\\n data = self._iex_source(**self._iex_source_kwargs)\\n if data:\\n should_update = True\\n if self._should_hash:\\n hashed = str_to_float(json.dumps(data, sort_keys=True))\\n should_update = hashed != self._last_hash\\n if should_update:\\n self._last_hash = hashed\\n if should_update:\\n if self._data_cleaner:\\n data = self._data_cleaner(data)\\n self.table.update(data)\\n \\n callback = tornado.ioloop.PeriodicCallback(callback=partial(_get, self), callback_time=self._interval)\\n callback.start()\",\n \"def log_data(self):\\n\\n assert self.tello is not None\\n self.tello.subscribe(self.tello.EVENT_LOG_DATA, self.log_handler)\\n self.tello.subscribe(self.tello.EVENT_FLIGHT_DATA, self.log_handler)\\n self.tello.subscribe(self.tello.EVENT_FILE_RECEIVED, self.log_handler)\",\n \"def update_live_data(n, last_time, id1, id2, power):\\n if power:\\n raise PreventUpdate\\n\\n timer_start = perf_counter()\\n # 1 sec delay so server has time to add live data\\n end_time = datetime.now(timezone.utc) - timedelta(seconds=1)\\n\\n # Initialization and lag prevention\\n if last_time is None or end_time - strptime_fix(last_time) > timedelta(seconds=3):\\n logging.warning('Falling behind! Start %s End %s', last_time, end_time)\\n return dash.no_update, dash.no_update, end_time.isoformat(), dash.no_update\\n\\n # Query data from SMIP\\n logging.info(f'start_time {last_time} end_time {end_time}')\\n timer_query_start = perf_counter()\\n r = conn.get_data(last_time, end_time.isoformat(),\\n [id1, id2], timeout=1)\\n timer_query_end = perf_counter()\\n response_json: dict = r.json()\\n logging.debug(response_json.keys())\\n if 'errors' in response_json:\\n logging.error(response_json)\\n raise Exception()\\n data = response_json['data']['getRawHistoryDataWithSampling']\\n logging.info('Got %s responses in %s seconds', len(\\n data), timer_query_end - timer_query_start)\\n\\n # Used for measuring performance\\n start_processing = perf_counter()\\n\\n # Unpack data\\n def unpack(id: int):\\n \\\"\\\"\\\"Unpacks return data into time and value lists\\\"\\\"\\\"\\n id = int(id)\\n time_list = [i['ts'] for i in data if int(i['id']) == id]\\n val_list = [i['floatvalue'] for i in data if int(i['id']) == id]\\n # SMIP always returns one entry before the start time for each ID, we don't need this\\n if len(time_list) < 2 or len(val_list) < 2:\\n return dash.no_update\\n time_list.pop(0)\\n val_list.pop(0)\\n # Measure sampling rate\\n rate = nan\\n if len(time_list) > 1:\\n rate = (strptime_fix(time_list[1])\\n - strptime_fix(time_list[0])).total_seconds()\\n return {'time_list': time_list, 'val_list': val_list, 'rate': rate}\\n\\n # Used for measuring performance\\n data_processed = perf_counter()\\n logging.info('Total %s Query %s Processing %s', data_processed - timer_start, timer_query_end - timer_query_start,\\n data_processed - start_processing)\\n\\n return unpack(id1), unpack(id2), end_time.isoformat(), \\\\\\n [f'Last updated {end_time.astimezone()},',\\n html.Br(),\\n f'received {len(data)} samples in {round(data_processed - timer_start, 3)} seconds']\",\n \"def on_timer(self):\\n self.read_serial_data()\\n # self.update_monitor()\",\n \"def _after_connect(self):\\r\\n _debug('GUISignalGenerator: _after_connect()')\\r\\n # Update the controls\\r\\n self.button_sweep.enable()\\r\\n self.button_send_list.enable()\\r\\n self.button_reset.enable()\\r\\n \\r\\n # Update the RF button.\\r\\n rf_on = self.api.get_output()\\r\\n if rf_on == None: self.button_rf.set_checked(True, block_events=True).enable()\\r\\n else: self.button_rf.set_checked(rf_on, block_events=True).enable()\\r\\n \\r\\n # Update the combo; we block first just in case the value doesn't \\\"change\\\"\\r\\n if self.api == None: self.label_instrument_name.set_text('Simulation')\\r\\n else:\\r\\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\\r\\n else: self.combo_mode.set_value(1, block_events=True).enable()\\r\\n self._combo_mode_changed()\\r\\n \\r\\n # Update the list plot\\r\\n self.query_list()\",\n \"def get_last_data(request):\\n\\n return_list = []\\n if request.POST:\\n try:\\n conn = psycopg2.connect(dbname=DB_NAME,\\n user=DB_USER,\\n password=DB_PASSWORD,\\n host=DB_HOST)\\n cur = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)\\n\\n cur.execute(\\\"SELECT sn, time, icsmain, icsz1, icsz2, icsz3, icsboiler, t1, t2, t3, t4, t5, t6, t7,\\\"\\n \\\"rt1, rt2, rt3, endswitch, weather FROM devicedata \\\"\\n \\\"WHERE sn='BRANDON_SN_US' \\\"\\n \\\"ORDER BY id DESC LIMIT 5\\\")\\n\\n get_device_data = cur.fetchall()\\n\\n cur.close()\\n conn.close()\\n\\n for info in get_device_data:\\n item_dict = {\\\"sn\\\": info[0], \\\"time\\\": str(info[1]), \\\"icsmain\\\": info[2], \\\"icsz1\\\": info[3], \\\"icsz2\\\": info[4],\\n \\\"icsz3\\\": info[5], \\\"icsboiler\\\": info[6], \\\"t1\\\": info[7], \\\"t2\\\": info[8], \\\"t3\\\": info[9],\\n \\\"t4\\\": info[10], \\\"t5\\\": info[11], \\\"t6\\\": info[12], \\\"t7\\\": info[13], \\\"rt1\\\": info[14], \\\"rt2\\\": info[15],\\n \\\"rt3\\\": info[16], \\\"endswitch\\\": info[17]}\\n return_list.append(item_dict)\\n except:\\n pass\\n\\n return JsonResponse(return_list, safe=False)\",\n \"def handle_spectra(self, this_start, this_end, spectra):\\n\\n self.rt_plot.add_data(self.rt_plot.queue, spectra, self.maxspectra)\\n\\n if self.plot:\\n\\n '''\\n Plot the data.\\n '''\\n self.plot_waterfall(1)\\n self.plot_spectrum(2)\\n # self.plot_fitter()\\n\\n '''\\n Uncomment 3 lines below to plot the spectra fitter plots.\\n '''\\n else:\\n self.data_handler.main(\\n self.datalog, self.calibrationlog, spectra, this_start, this_end)\",\n \"def data_received(self, data):\\n self.log.debug('data_received: {!r}'.format(data))\\n self._last_received = datetime.datetime.now()\\n for byte in (bytes([value]) for value in data):\\n\\n try:\\n self.stream.feed_byte(byte)\\n except (ValueError, AssertionError):\\n e_type, e_value, _ = sys.exc_info()\\n map(self.log.warn,\\n traceback.format_exception_only(e_type, e_value))\\n continue\\n\\n if self.stream.is_oob:\\n continue\\n\\n # self.reader.feed_byte()\\n self.shell.feed_byte(byte)\",\n \"def query_list(self):\\r\\n self.plot_list.clear()\\r\\n self.settings.send_to_databox_header(self.plot_list)\\r\\n \\r\\n self.label_list_status.set_text('Getting frequencies and powers.')\\r\\n self.window.process_events()\\r\\n \\r\\n fs = self.api.get_list_frequencies()\\r\\n ps = self.api.get_list_powers()\\r\\n if fs == None or ps == None: return\\r\\n \\r\\n if not len(fs) == len(ps):\\r\\n print(\\\"ERROR query_list(): List lengths do not match. len(fs)=\\\"+str(len(fs))+' len(ps)='+str(len(ps)) )\\r\\n \\r\\n N = len(fs)\\r\\n self.plot_list['n'] = _n.linspace(0, N-1, N)\\r\\n self.plot_list['f_Hz'] = fs\\r\\n self.plot_list['P_dBm'] = ps\\r\\n \\r\\n self.label_list_status.set_text(str(N) + ' points in list memory')\\r\\n self.plot_list.plot()\\r\\n self.button_send_list.disable()\\r\\n self.window.process_events()\",\n \"def get_history():\\n return response_texts_to_entries(make_post_request(HISTORY_API, data={\\\"k\\\": config[\\\"api_key\\\"]}))\",\n \"def start(self):\\n record_list_count = 0\\n item_count = 0\\n output_list = []\\n record_in_range = False\\n\\n if not self.trim:\\n print PROMPT + \\\"Getting Voltage readings that arrived at the server from device \\\" + \\\\\\n self.name,\\n if self.start_time is not None:\\n print(\\\"after around UTC \\\" + date.strftime(self.start_time, \\\"%Y-%m-%d %H:%M\\\")),\\n if self.end_time is not None:\\n print(\\\"and before around UTC \\\" + date.strftime(self.end_time, \\\"%Y-%m-%d %H:%M\\\")),\\n stdout.write('\\\\n')\\n print PROMPT + \\\"V_BAT_OK, V_IN, V_PRIMARY (all in milliVolts)\\\"\\n\\n # Set some default start and end times if they are None\\n if self.start_time is None:\\n self.start_time = datetime.strptime('Jan 1 1970', '%b %d %Y').replace(tzinfo=utc)\\n if self.end_time is None:\\n self.end_time = datetime.strptime('Jan 1 2038', '%b %d %Y').replace(tzinfo=utc)\\n\\n # Create some dummy object IDs from the dates/times to use with PyMongo\\n object_id_start_time = ObjectId.from_datetime(self.start_time)\\n object_id_end_time = ObjectId.from_datetime(self.end_time)\\n\\n # Retrieve all the records that match the given name in the order they were created\\n record_list = self.collection.find({\\\"n\\\": self.name, \\\\\\n \\\"_id\\\": {\\\"$gte\\\": object_id_start_time, \\\\\\n \\\"$lte\\\": object_id_end_time}}). \\\\\\n sort([[\\\"_id\\\", 1]])\\n for record in record_list:\\n record_in_range = record[\\\"_id\\\"].generation_time > self.start_time\\n if record_in_range:\\n record_list_count += 1\\n # Find the index in the record, just to be sure it's a record\\n if \\\"i\\\" in record:\\n # Find the report items in the record\\n if \\\"r\\\" in record:\\n r_list = record[\\\"r\\\"]\\n # Go through the list\\n for r_item in r_list:\\n # See if there's a voltages item in it\\n if \\\"vlt\\\" in r_item:\\n voltages_item = r_item[\\\"vlt\\\"]\\n item_count += 1\\n # Decode the voltages and add them to our list\\n voltages_struct = self.get_voltages_item(voltages_item)\\n output_list.append(voltages_struct)\\n # Having got everything, sort it in time order\\n output_list.sort(key=sort_func)\\n # Now print it\\n for item in output_list:\\n time_string = datetime.utcfromtimestamp(item.timestamp) \\\\\\n .strftime(\\\"%Y-%m-%d_%H:%M:%S\\\")\\n print(\\\"%s %d %d %d\\\" % (time_string, item.v_bat_ok_mv,\\n item.v_in_mv, item.v_primary_mv))\\n if not self.trim:\\n print(PROMPT + \\\"%r record(s) returned containing %r voltage reading(s)\\\"\\n % (record_list_count, item_count))\",\n \"def slot_history_changed(self, _sender, _data):\\r\\n last_candle = self.history.last_candle()\\r\\n if last_candle:\\r\\n self.client.history_last_candle = last_candle.tim\",\n \"def __flight_data_handler(self, event, sender, data):\\n self.battery = data.battery_percentage\\n self.fly_mode = data.fly_mode\\n self.throw_fly_timer = data.throw_fly_timer\\n self.throw_ongoing = data.throw_fly_timer > 0\\n\\n if self.prev_flight_data != str(data):\\n print(data)\\n self.prev_flight_data = str(data)\\n self.flight_data = data\\n\\n if self.is_flying != data.em_sky:\\n self.is_flying = data.em_sky\\n log.debug(f\\\"FLYING : {self.is_flying}\\\")\\n if not self.is_flying:\\n self.reset()\\n else:\\n if self.tracking_after_takeoff:\\n log.info(\\\"Tracking on after takeoff\\\")\\n self.toggle_tracking(True)\\n\\n # if self.write_header_log:\\n # self.write_header_log = False\\n # self.log_file_log.write(f\\\"{data.format_cvs_header()}\\\\n\\\")\\n # self.log_file_log.write(f\\\"{data.format_cvs(0)}\\\\n\\\")\",\n \"def get_data(self):\\n return self.read_sample_win()\",\n \"def listen(self):\\n\\n if not self.key_data:\\n self.key_data = {}\\n for i in range(1024):\\n self.key_data[i] = False\\n\\n if not self.axis_data:\\n self.axis_data = {}\\n for i in range(self.controller.get_numaxes()):\\n self.axis_data[i] = 0.0\\n\\n if not self.button_data:\\n self.button_data = {}\\n for i in range(self.controller.get_numbuttons()):\\n self.button_data[i] = False\\n\\n if not self.hat_data:\\n self.hat_data = {}\\n for i in range(self.controller.get_numhats()):\\n self.hat_data[i] = (0, 0)\\n\\n debug_toggle = True\\n print_state_toggle = True\\n\\n # These parameters define how frequesnt speed setting sent over serial to arduino\\n speed_threshold = 10.0 # sets update threshold\\n speed_step = 1 # sets acceleration\\n speed_delay = 0.01 # delay per 1 step in sec\\n\\n mode_switch = \\\"j\\\" # control mode: k - keyboard, j - joystick\\n\\n # Parameters for keyboard control mode\\n speed = 0.0\\n speed_current = 0\\n direction = \\\"r\\\" # r - release, f - forward, b - backward\\n direction_current = \\\"r\\\"\\n\\n # Parameters for joystick control mode\\n speed_l = 0\\n speed_r = 0\\n prev_speed_l = 0\\n prev_speed_r = 0\\n prev_btn = False\\n\\n while True:\\n prev = self.axis_data\\n for event in pygame.event.get():\\n if event.type == pygame.KEYDOWN:\\n self.key_data[event.key] = True\\n elif event.type == pygame.KEYUP:\\n self.key_data[event.key] = False\\n if event.type == pygame.JOYAXISMOTION:\\n self.axis_data[event.axis] = round(event.value,2)\\n elif event.type == pygame.JOYBUTTONDOWN:\\n self.button_data[event.button] = True\\n elif event.type == pygame.JOYBUTTONUP:\\n self.button_data[event.button] = False\\n elif event.type == pygame.JOYHATMOTION:\\n self.hat_data[event.hat] = event.value\\n\\n # check for exit command\\n if self.button_data[9] or self.key_data[pygame.QUIT] or self.key_data[pygame.K_ESCAPE]:\\n pygame.quit()\\n break\\n\\n # toggle debug\\n if self.key_data[pygame.K_d]:\\n if debug_toggle:\\n print(\\\"Toggle debug\\\")\\n self.ser.write(b'd')\\n debug_toggle = False\\n else:\\n debug_toggle = True\\n\\n # print out motors status\\n if self.key_data[pygame.K_p]:\\n if print_state_toggle:\\n self.ser.write(b'p')\\n if self.ser.in_waiting:\\n print (self.ser.readline())\\n print_state_toggle = False\\n else:\\n print_state_toggle = True\\n\\n if self.key_data[pygame.K_1] and mode_switch != \\\"k\\\":\\n mode_switch = \\\"k\\\"\\n\\n if self.key_data[pygame.K_2] and mode_switch != \\\"j\\\":\\n print(\\\"Joystick mode: ON\\\")\\n mode_switch = \\\"j\\\"\\n\\n if mode_switch == \\\"k\\\": # keyboard control mode\\n # accelearte forward\\n if self.key_data[pygame.K_a] and direction != \\\"r\\\":\\n if speed < 255.0:\\n speed = speed + speed_step\\n sleep(speed_delay)\\n # accelerate backward\\n if self.key_data[pygame.K_z] and direction != \\\"r\\\":\\n if speed > 0.0:\\n speed = speed - speed_step\\n sleep(speed_delay)\\n\\n if self.key_data[pygame.K_UP] and direction != \\\"f\\\":\\n direction = \\\"f\\\"\\n if self.key_data[pygame.K_DOWN] and direction != \\\"b\\\":\\n direction = \\\"b\\\"\\n if self.key_data[pygame.K_UP] == False and direction == \\\"f\\\":\\n direction = \\\"r\\\"\\n if self.key_data[pygame.K_DOWN] == False and direction == \\\"b\\\":\\n direction = \\\"r\\\"\\n\\n if math.fabs(speed - speed_current) > speed_threshold or direction != direction_current:\\n # print(\\\"{0}, {1}, {2}, {3}\\\".format(speed, speed_current, direction, direction_current))\\n direction_current = direction\\n if direction == \\\"r\\\":\\n speed = 0.0\\n speed_current = int(speed)\\n str_r = \\\"sr\\\" + direction_current + str(speed_current) + \\\"e\\\"\\n str_l = \\\"sl\\\" + direction_current + str(speed_current) + \\\"e\\\"\\n print(str_l)\\n print(str_r)\\n self.ser.write(str_r.encode())\\n self.ser.write(str_l.encode())\\n\\n if(self.key_data[pygame.K_LEFT]):\\n str_rf = \\\"srf\\\" + str(speed_current) + \\\"e\\\"\\n self.ser.write(str_rf.encode())\\n str_lf = \\\"slf\\\" + str(int(speed_current*0.9)) + \\\"e\\\"\\n self.ser.write(str_lf.encode())\\n elif(self.key_data[pygame.K_RIGHT]):\\n str_rb = \\\"srf\\\" + str(int(speed_current*0.9)) + \\\"e\\\"\\n self.ser.write(str_rb.encode())\\n str_lb = \\\"slf\\\" + str(speed_current) + \\\"e\\\"\\n self.ser.write(str_lb.encode())\\n\\n if (self.key_data[pygame.K_UP] == False and self.key_data[pygame.K_DOWN] == False) and (self.key_data[pygame.K_a] == False and self.key_data[pygame.K_z] == False):\\n speed = 0\\n speed_current = speed\\n direction = \\\"r\\\"\\n direction_current = direction\\n self.ser.write(b'srze')\\n self.ser.write(b'slze')\\n\\n if mode_switch == \\\"j\\\": # joystick control mode\\n if self.ser.in_waiting:\\n data = str(self.ser.readline().strip())\\n data = data[2 :len(data)-1]\\n print(data)\\n #self.aio.send('Team Hacky Slackers', data)\\n\\n prev_speed_l = speed_l\\n prev_speed_r = speed_r\\n speed_threshold = 1\\n\\n #simplified linear mapping for controller\\n speed_l = int((self.axis_data[0]*(-50)) + 90)\\n speed_r = int(math.fabs(self.axis_data[3]*255))\\n #print(self.axis_data)\\n #print(\\\"curr_l: {0}, perv_l: {1}, curr_r:{2}, perv_r:{3}\\\".format(speed_l, prev_speed_l, speed_r,prev_speed_r))\\n\\n if self.axis_data[0] < -0.05 and math.fabs(speed_l - prev_speed_l) > speed_threshold:\\n str_lf = \\\"slf\\\" + str(speed_l) + \\\"e\\\"\\n self.ser.write(str_lf.encode())\\n elif self.axis_data[0] > 0.05 and math.fabs(speed_l - prev_speed_l) > speed_threshold:\\n str_lb = \\\"slb\\\" + str(speed_l) + \\\"e\\\"\\n self.ser.write(str_lb.encode())\\n\\n\\n if self.axis_data[3] < -0.03 and math.fabs(speed_r - prev_speed_r) > speed_threshold:\\n str_rf = \\\"srf\\\" + str(speed_r) + \\\"e\\\"\\n self.ser.write(str_rf.encode())\\n elif self.axis_data[3] > 0.03 and math.fabs(speed_r - prev_speed_r) > speed_threshold:\\n str_rb = \\\"srb\\\" + str(speed_r) + \\\"e\\\"\\n self.ser.write(str_rb.encode())\\n\\n if ( self.axis_data[0] >= -0.05 and self.axis_data[0] <= 0.05 ) and ( self.axis_data[3] >= -0.05 and self.axis_data[3] <= 0.05 ):\\n speed_l = 90\\n speed_r = 0\\n self.ser.write(b'srze')\\n self.ser.write(b'slze')\\n\\n #Logic to call RFID scan only once per click of R1 button\\n # if(prev_btn != self.button_data[5]):\\n # prev_btn = self.button_data[5]\\n # if self.button_data[5] :\\n # print(\\\"Scanning for RFID Card\\\")\\n # self.ser.write(\\\"i\\\".encode())\\n\\n # clear()\\n # pprint.pprint(self.button_data)\\n # pprint.pprint(self.axis_data)\\n # pprint.pprint(self.hat_data)\",\n \"def receive_data():\\n\\n while True:\\n try:\\n bytes_to_read = ser.readline()\\n print(bytes_to_read)\\n data = json.loads(bytes_to_read.decode('utf-8'))\\n distance = data['distance']\\n print(f'distance: {distance}')\\n except Exception as e:\\n print(f'Error in reading bytes from the \\\\'duino: {e}')\",\n \"def sendPreviousDataPoints(self):\\n if self.ioLoopInst is not None:\\n cmd = {'cmd': 'setDataPoints', 'value': self.dataPoints}\\n self._sendMessageToWeb(cmd)\\n else:\\n print(\\\"sendPreviousDataPoints: \\\" + self.dataPoints)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6700092","0.6360538","0.6166242","0.60464233","0.6038091","0.6023963","0.60063523","0.5908595","0.58683914","0.5861097","0.58507204","0.5833523","0.5832018","0.57664955","0.57027274","0.5638211","0.5628629","0.5615999","0.56110036","0.56060934","0.5573338","0.55372125","0.55178803","0.5506934","0.5479551","0.54564303","0.54483074","0.5427582","0.54211545","0.5408876","0.5407351","0.5375614","0.53665334","0.5360664","0.5356425","0.53510857","0.5341443","0.5334029","0.5332098","0.5315797","0.531547","0.5304051","0.53018165","0.5300674","0.52904433","0.5290254","0.52779025","0.5276737","0.5276123","0.52648497","0.5262615","0.5249989","0.5248876","0.52415985","0.523876","0.5231435","0.52294254","0.52247196","0.5218119","0.5216528","0.5214594","0.52132654","0.52109796","0.52079827","0.5203675","0.520273","0.5189451","0.51790315","0.517195","0.51679075","0.516474","0.51528597","0.5150831","0.51491565","0.5148176","0.5146634","0.5140949","0.5130911","0.51291615","0.5126091","0.5125773","0.5115986","0.5114233","0.5110002","0.5108117","0.51050806","0.5104406","0.5102758","0.5102146","0.51020974","0.50982267","0.50956583","0.50918645","0.50890255","0.5088444","0.5086157","0.50858295","0.50841296","0.50827307","0.5082223"],"string":"[\n \"0.6700092\",\n \"0.6360538\",\n \"0.6166242\",\n \"0.60464233\",\n \"0.6038091\",\n \"0.6023963\",\n \"0.60063523\",\n \"0.5908595\",\n \"0.58683914\",\n \"0.5861097\",\n \"0.58507204\",\n \"0.5833523\",\n \"0.5832018\",\n \"0.57664955\",\n \"0.57027274\",\n \"0.5638211\",\n \"0.5628629\",\n \"0.5615999\",\n \"0.56110036\",\n \"0.56060934\",\n \"0.5573338\",\n \"0.55372125\",\n \"0.55178803\",\n \"0.5506934\",\n \"0.5479551\",\n \"0.54564303\",\n \"0.54483074\",\n \"0.5427582\",\n \"0.54211545\",\n \"0.5408876\",\n \"0.5407351\",\n \"0.5375614\",\n \"0.53665334\",\n \"0.5360664\",\n \"0.5356425\",\n \"0.53510857\",\n \"0.5341443\",\n \"0.5334029\",\n \"0.5332098\",\n \"0.5315797\",\n \"0.531547\",\n \"0.5304051\",\n \"0.53018165\",\n \"0.5300674\",\n \"0.52904433\",\n \"0.5290254\",\n \"0.52779025\",\n \"0.5276737\",\n \"0.5276123\",\n \"0.52648497\",\n \"0.5262615\",\n \"0.5249989\",\n \"0.5248876\",\n \"0.52415985\",\n \"0.523876\",\n \"0.5231435\",\n \"0.52294254\",\n \"0.52247196\",\n \"0.5218119\",\n \"0.5216528\",\n \"0.5214594\",\n \"0.52132654\",\n \"0.52109796\",\n \"0.52079827\",\n \"0.5203675\",\n \"0.520273\",\n \"0.5189451\",\n \"0.51790315\",\n \"0.517195\",\n \"0.51679075\",\n \"0.516474\",\n \"0.51528597\",\n \"0.5150831\",\n \"0.51491565\",\n \"0.5148176\",\n \"0.5146634\",\n \"0.5140949\",\n \"0.5130911\",\n \"0.51291615\",\n \"0.5126091\",\n \"0.5125773\",\n \"0.5115986\",\n \"0.5114233\",\n \"0.5110002\",\n \"0.5108117\",\n \"0.51050806\",\n \"0.5104406\",\n \"0.5102758\",\n \"0.5102146\",\n \"0.51020974\",\n \"0.50982267\",\n \"0.50956583\",\n \"0.50918645\",\n \"0.50890255\",\n \"0.5088444\",\n \"0.5086157\",\n \"0.50858295\",\n \"0.50841296\",\n \"0.50827307\",\n \"0.5082223\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6273694"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":1398,"cells":{"query":{"kind":"string","value":"Determines if a given datetime.datetime is aware."},"document":{"kind":"string","value":"def is_aware(value):\n return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def is_aware(value: datetime) -> bool:\n\n return value.utcoffset() is not None","def test_make_datetime_aware(settings):\n # Set the TIME_ZONE in the settings.\n settings.TIME_ZONE = \"America/New_York\"\n\n # Calling make_datetime_aware() returns a timezone-aware datetime referring\n # to the moment from the naive_datetime_obj, in the appropriate time zone.\n naive_datetime_str = \"2018-01-01T20:00:00\"\n expected_datetime_obj = make_aware(\n datetime(year=2018, month=1, day=1, hour=20, minute=0, second=0),\n timezone=pytz.timezone(\"America/New_York\"),\n )\n assert make_datetime_aware(naive_datetime_str) == expected_datetime_obj\n\n # Calling make_datetime_aware() for non-datetime strings returns None.\n dt_str = \"\"\n aware_dt = make_datetime_aware(dt_str)\n assert aware_dt == None\n dt_str = None\n aware_dt = make_datetime_aware(dt_str)\n assert aware_dt == None","def _is_timezone_aware(value):\n return value.utcoffset() is not None","def valid_datetime(dt):\n if isinstance(dt.tzinfo, tzinfo) and not datetime_ambiguous(dt):\n return True\n return False","def is_datetime(self) -> bool:\n return False","def is_datetime(self):\n answer = self._call('is_datetime')\n return answer.yes","def test_freeze_with_timezone_aware_datetime_in_non_utc():\n utc_now = datetime.datetime.utcnow()\n assert utc_now.tzinfo is None\n assert utc_now == datetime.datetime(1970, 1, 1, 4)","def check_dt_consistency(date_dt):\n\n # https://en.wikipedia.org/wiki/Tz_database\n # https://www.iana.org/time-zones\n \n if date_dt.tzinfo is None:\n return True\n else:\n \n # This check is quite heavy but there is apparently no other way to do it.\n if date_dt.utcoffset() != dt_from_s(s_from_dt(date_dt), tz=date_dt.tzinfo).utcoffset():\n return False\n else:\n return True","def make_aware(value: datetime, timezone=None, is_dst=None) -> datetime:\n\n if timezone is None:\n timezone = get_current_timezone()\n\n if hasattr(timezone, \"localize\"):\n # This method is available for pytz time zones.\n return timezone.localize(value, is_dst=is_dst)\n else:\n # Check that we won't overwrite the timezone of an aware datetime.\n if is_aware(value):\n raise ValueError(\"make_aware expects a naive datetime, got %s\" % value)\n # This may be wrong around DST changes!\n return value.replace(tzinfo=timezone)","def correct_datetime(record_datetime):\n assert record_datetime.date() == datetime.now(timezone.utc).date()","def _uses_datetimeblock(dtype: Union[np.dtype, ExtensionDtype]) -> bool:\n vtype = dtype.type\n return issubclass(vtype, np.datetime64)","def test_freeze_with_timezone_aware_datetime_in_utc():\n utc_now = datetime.datetime.utcnow()\n assert utc_now.tzinfo is None","def is_after(self, dt: datetime) -> bool:\n return self.target_time >= make_tz_aware(dt)","def in_between_datetime(now, start, end):\n return start <= now <= end","def isNaive(self, date):\n return not self.isAware(date)","def has_datetime_type(obj: _std_typing.Any) -> bool:\n return obj.dtype == sc.DType.datetime64","def is_date(dt):\n return isinstance(dt, datetime.date) and not isinstance(dt, datetime.datetime)","def is_naive(value: datetime) -> bool:\n\n return value.utcoffset() is None","def datetime_has_tz(dt):\n\n if type(dt) != datetime.datetime:\n raise TypeError(f\"dt must be type datetime.datetime, not {type(dt)}\")\n\n return dt.tzinfo is not None and dt.tzinfo.utcoffset(dt) is not None","def in_datetime_interval(when, *, start=None, end=None):\n when = as_ref_datetime(when) # This is not allowed to be None, but could be str and we need datetimes to compare.\n start = start and as_ref_datetime(start)\n end = end and as_ref_datetime(end)\n return (not start or start <= when) and (not end or end >= when)","async def datetime(self, aware=False) -> dt.datetime:\n if aware is True:\n now = await self.AD.sched.get_now()\n return now.astimezone(self.AD.tz)\n else:\n return await self.AD.sched.get_now_naive()","def check_date(created_at, start, end):\n x = get_date(created_at)\n return x <= end and x >= start","def test_enlighten_dtime(self):\n\n est = pytz.timezone(\"EST\")\n aware_dtime = datetime.datetime(\n year=1985, month=11, day=15,\n hour=6, minute=0,\n tzinfo=est)\n\n enlightened_dtime = enlighten_dtime(aware_dtime)\n # The tzinfo should be untouched.\n self.assertIs(aware_dtime.tzinfo, enlightened_dtime.tzinfo)\n\n # This is a naive object, but has UTC values for hour.\n utcnow = datetime.datetime.now()\n # No tzinfo was present, so that is replaced. hour should be the same.\n enlightened_utcnow = enlighten_dtime(utcnow)\n self.assertEqual(enlightened_utcnow.hour, utcnow.hour)\n self.assertIs(enlightened_utcnow.tzinfo, UTC_TZINFO)","def office_is_open_on_datetime(iso_datetime):\n is_open = False\n d_time = datetime.fromisoformat(iso_datetime)\n d_date = date(d_time.year, d_time.month, d_time.day)\n schedule = AppointmentService.APPOINTMENT_SCHEDULE.get(d_date.weekday(), {})\n if schedule:\n begin_time = datetime.combine(d_date, schedule['begin'])\n end_time = datetime.combine(d_date, schedule['end'])\n if begin_time <= d_time <= end_time:\n is_open = True\n\n return is_open","def ensure_datetime(ob: AnyDatetime) -> datetime.datetime:\n if isinstance(ob, datetime.datetime):\n return ob\n date = cast(datetime.date, ob)\n time = cast(datetime.time, ob)\n if isinstance(ob, datetime.date):\n time = datetime.time()\n if isinstance(ob, datetime.time):\n date = datetime.date(1900, 1, 1)\n return datetime.datetime.combine(date, time)","def make_tz_aware(local_dt):\n aware_dt = timezone('US/Eastern').localize(local_dt)\n return aware_dt","def _is_date_in_range(self, date):\n date_obj = datetime.strptime(date.split('T')[0], '%Y-%m-%d')\n \"\"\"When running under delta feed mode, we need to consider only those vulns which were\n updated between the given offset date and today's date.\"\"\"\n return self.today > date_obj >= self.start_day","def omniscient_datetime(*args):\n d = original_datetime(*args)\n if settings.USE_TZ:\n d = timezone.make_aware(d, timezone.utc)\n return d","def validDateTime( dateTime ):\n try:\n datetime.strptime( dateTime, \"%Y-%m-%dT%H:%M:%S.%fZ\" )\n return True\n except ValueError:\n return False","def adjust_icms_v1_datetime(dt_val: dt.datetime) -> dt.datetime:\n\n if timezone.is_aware(dt_val):\n raise ValueError(f\"Unable to adjust an aware datetime value: {dt_val}\")\n\n # ICMS V1 datetime values are created using this:\n # https://docs.oracle.com/database/121/SQLRF/functions207.htm#SQLRF06124\n # Therefore replace the naive datetime with the correct timezone\n aware_dt = dt_val.replace(tzinfo=UK_TZ)\n\n # Return a datetime that has been offset to UTC\n utc_dt = aware_dt.astimezone(dt.timezone.utc)\n\n return utc_dt","def timestamp_aware(dt):\n if dt.tzinfo is None:\n dt = dt.replace(tzinfo=tz.tzlocal()) # new object\n return dt","def get_timezone_aware_datetime(datetime):\n if not datetime:\n return None\n local = timezone.get_current_timezone()\n return (local.localize(parse(datetime), is_dst=None)).astimezone(timezone.utc)","def aired(self):\n # TODO: timezone\n airdatetime = self.airdatetime\n if airdatetime:\n return datetime.now() >= airdatetime + timedelta(minutes=self.series.runtime)\n else:\n return False","def is_in_advent() -> bool:\n # Run the code from the 1st to the 24th\n return datetime.now(EST).day in range(1, 25) and datetime.now(EST).month == 12","def enforce_timezone(self, value):\n try:\n tz = timezone._active.value\n if (self.default_timezone is not None) and not timezone.is_aware(value):\n return timezone.make_aware(value, tz)\n return value\n except AttributeError:\n return super().enforce_timezone(value)","def almost_same_datetime(dt1, dt2, allowed_delta=timedelta(minutes=1)):\r\n return abs(dt1 - dt2) < allowed_delta","def test_datetime(self):\n diff = self.machine_date - self.actual_date < datetime.timedelta(0, 20, 0)","def is_datetime(s: Union[str, int, float]):\n if is_number(s):\n return False\n\n try:\n parse_datetime(s)\n return True\n except Exception:\n return False","def date_make_timezone_aware(datetime_object, timezone_string=None):\n if timezone_string:\n # make the date timezone aware using the given timezone_string\n timezone_object = pytz_timezone_object(timezone_string)\n timezone_aware_datetime_object = timezone_object.localize(datetime_object)\n else:\n # make the date timezone aware using the timezone of the current system\n timezone_aware_datetime_object = datetime_object.astimezone()\n\n return timezone_aware_datetime_object","def is_interpretable(self):\n return bool(self.as_date() or self.as_time())","def test_paid_at(self):\n\n self.assertIsInstance(self.obj.paid_at, datetime)","def check_date(date):\n import datetime\n correctDate = None\n date = str(date)\n \n if (len(date)!=8):\n return False\n year = int(date[0:4])\n month = int(date[4:6])\n day = int(date[6:8])\n try:\n datetime.datetime(year,month,day)\n correctDate = True\n except ValueError:\n correctDate = False\n return correctDate","def could_be_datetime(val, fmt):\n\n if val == None or fmt == None:\n return False\n\n if isinstance(val, datetime):\n return True\n\n if isinstance(val, (str, unicode)):\n if Record.is_empty_str(val) or Record.is_empty_str(fmt):\n return False\n\n try:\n d = datetime.strptime(val, fmt)\n if not isinstance(d, datetime):\n raise ValueError\n else:\n return True\n except Exception as e:\n logging.error(e)\n return False\n\n #otherwise\n return False","def has_time(self):\n return isinstance(self._start, datetime.datetime)","def is_in_the_future(dt):\n if dt > datetime.now(pytz.utc):\n return True\n return False","def is_available_at(self, datetime):\n for booking in self.booking_set.all():\n if booking.schedule_start <= datetime < booking.schedule_end and not booking.is_cancelled():\n return False\n return True","def test_update_at(self):\n self.assertIsInstance(self.obj.update_at, datetime)","def test_update_at(self):\n self.assertIsInstance(self.obj.update_at, datetime)","def test_update_at(self):\n self.assertIsInstance(self.obj.update_at, datetime)","def tz_aware(value: datetime) -> datetime:\n if settings.USE_TZ:\n value = value.replace(tzinfo=timezone.utc)\n\n return value","def test_missing_report_datetime(self):\n self.assertEqual(datetime.datetime.min, self.__uft.datetime('raise'))","def is_starttrimester(today):\n if isinstance(today, datetime):\n if today.day == 1 and today.month == 1:\n return True\n elif today.day == 1 and today.month == 4:\n return True\n elif today.day == 1 and today.month == 7:\n return True\n elif today.day == 1 and today.month == 10:\n return True\n return False\n else:\n raise Exception(\"{} is not a datetime instance\".format(today))","def datetime_checkinput(year, month, day):\n try:\n datetime.datetime(year, month, day)\n except:\n raise Invaliddatetimeinput\n return 0","def tz_aware(dt: datetime, default: tzinfo = tzutc()) -> datetime:\n if dt.tzinfo is None:\n dt = dt.replace(tzinfo=default)\n return dt","def test_14_digit_datetime_detection(self):\n obj = awstats_reader.awstats_datetime('20091130165230')\n self.assertTrue(isinstance(obj, awstats_reader.AwstatsDateTime))","def is_valid_date_offset(user_date, offset):\n return","def skip_or_run_datetime_test(func):\n\n return skip_or_run_test_pcall_require(func, 'datetime',\n 'does not support datetime type')","def is_auto_assigned_date_column(column):\n return (\n (\n isinstance(column.type, sa.DateTime) or\n isinstance(column.type, sa.Date)\n )\n and\n (\n column.default or\n column.server_default or\n column.onupdate or\n column.server_onupdate\n )\n )","def simulatedate_checkinput(start, end):\n start_year, start_month, start_day = parse_string_datetime(start)\n end_year, end_month, end_day = parse_string_datetime(end)\n if datetime_checkinput(start_year, start_month, start_day) == 0 and datetime_checkinput(end_year, end_month, end_day) == 0:\n start_time = datetime.datetime(start_year, start_month, start_day)\n end_time = datetime.datetime(end_year, end_month, end_day)\n if start_time < end_time:\n return 0\n else:\n raise Invaliddatetimeinput","def test_format_builtin(self):\n with self.settings(TIME_ZONE='UTC'):\n datetime = aware_datetime(2015, 1, 1, 5, 7)\n assert_equal(format_datetime(datetime, 'time'), '05:07 UTC')","def is_soon(dt, window):\r\n soon = (utcnow() + datetime.timedelta(seconds=window))\r\n return normalize_time(dt) <= soon","def is_soon(dt, window):\n soon = (utcnow() + datetime.timedelta(seconds=window))\n return normalize_time(dt) <= soon","def _test_df_datetime(self, df):\n date_raw = df['DateListed'].iloc[0] # e.g. '2016-01-07 00:00:00'\n first_date_time = datetime.strptime(date_raw, \"%Y-%m-%d %H:%M:%S\")\n assert first_date_time >= datetime(2016, 1, 1, 0, 0) and \\\n first_date_time < datetime(2017, 1, 1, 0, 0)","def is_available(iso_datetime):\n d_time = datetime.fromisoformat(AppointmentService.closest_half(iso_datetime))\n av_slots = AppointmentService.get_available_slots(iso_datetime)\n is_available = (d_time in av_slots)\n\n return is_available","def acceptable(self):\n now = datetime.datetime.now()\n origin = datetime.datetime.combine(self.date, datetime.time.min)\n start = origin + datetime.timedelta(hours=6)\n end = origin + datetime.timedelta(days=1)\n morning = end + datetime.timedelta(hours=6)\n if now < origin or now > morning:\n return 0\n if now >= end or now <= start:\n return 1\n return 3","def validate_date(start_date_str, end_date_str):\n # NOTE: datetime.fromisoformat() New in version Python 3.7\n\n try:\n start_date_iso = datetime.fromisoformat(start_date_str)\n end_date_iso = datetime.fromisoformat(end_date_str)\n return True\n except ValueError as date_error:\n print(f\"Incorrect data format, datetime should be in ISO format, {date_error}\")\n return False\n if start_date_iso > end_date_iso:\n return False\n\n return True","def test_datetime_with_naive_duedate_only_fails(self):\n # setup\n specify_wd = self.project.activity('Specify wheel diameter')\n\n # save old values\n old_start, old_due = datetime.strptime(specify_wd._json_data.get('start_date'), ISOFORMAT), \\\n datetime.strptime(specify_wd._json_data.get('due_date'), ISOFORMAT)\n naive_duedate = datetime(2017, 6, 5, 5, 0, 0)\n with warnings.catch_warnings(record=False) as w:\n warnings.simplefilter(\"ignore\")\n specify_wd.edit(due_date=naive_duedate)\n\n # teardown\n with warnings.catch_warnings(record=False) as w:\n warnings.simplefilter(\"ignore\")\n specify_wd.edit(due_date=old_due)","def compare_datetime(self_datetime, other_datetime):\n # pylint: disable=superfluous-parens\n if (isinstance(self_datetime and other_datetime, (datetime, type(None)))):\n return (\n (self_datetime == other_datetime\n if all(str(_.time()) != \"00:00:00\"\n for _ in [self_datetime, other_datetime])\n else self_datetime.date() == other_datetime.date())\n if self_datetime and other_datetime\n else self_datetime == other_datetime)\n else:\n Representation.attrs_values_types_error(\n self_attr=self_datetime, other_attr=other_datetime,\n expected_types=(datetime.__name__, type(None).__name__))","def are_all_datetimes(values: List[Union[str, int, float]]):\n for value in values:\n if not is_datetime(value):\n return False\n return True","def isdt(self):\n return self.Units.isreftime and self._subarray.dtype == _dtype_object","def test_date_change_fails_on_naive_datetime(self):\n event = Event(\n Guild(12345),\n 'Some title',\n datetime(2020, 10, 10, 10, 10, tzinfo=utc),\n 'Some description')\n with self.assertRaises(ValueError):\n event.date = datetime(2020, 10, 10, 12, 10)","async def test_has_group_address_localtime(self):\n xknx = XKNX()\n self.datetime = DateTime(\n xknx,\n \"TestDateTime\",\n group_address=\"1/2/3\",\n group_address_state=\"1/2/4\",\n localtime=True,\n )\n assert self.datetime.has_group_address(GroupAddress(\"1/2/3\"))\n # group_address_state ignored when using localtime\n assert not self.datetime.has_group_address(GroupAddress(\"1/2/4\"))","def _is_ready(self, as_of):\n if self.is_one_off():\n return self.initial_billing_cycle.date_range.lower <= as_of\n else:\n return True","def date_temporal_paradox_free(self):\n valid_date = True\n new_val = self.date_edit.text()\n datetime_object = datetime.strptime(new_val, \"%Y-%m-%d\")\n\n if datetime_object > datetime.now():\n valid_date = False\n return valid_date","def is_outdated(self):\n today = datetime.datetime.today()\n day = datetime.datetime.combine(self.date, self.start_time)\n return day <= today","def test_8_digit_date_detection(self):\n obj = awstats_reader.awstats_datetime('20091130')\n self.assertTrue(isinstance(obj, awstats_reader.AwstatsDate))","def test_created_at(self):\n self.assertIsInstance(self.obj.created_at, datetime)","def test_created_at(self):\n self.assertIsInstance(self.obj.created_at, datetime)","def test_created_at(self):\n self.assertIsInstance(self.obj.created_at, datetime)","def test_datetime_from(self):\n dt = sync.datetime_from('2012-09-09T00:00:00') # EDT\n self.assertEqual(2012, dt.year)\n self.assertEqual(9, dt.month)\n self.assertEqual(10, dt.day)\n self.assertEqual(3, dt.hour)\n self.assertEqual(59, dt.minute)\n self.assertEqual(59, dt.second)\n self.assertEqual(dt.tzname(), 'UTC')\n\n dt = sync.datetime_from('2012-12-09T00:00:00') # EST\n self.assertEqual(2012, dt.year)\n self.assertEqual(12, dt.month)\n self.assertEqual(10, dt.day)\n self.assertEqual(4, dt.hour)\n self.assertEqual(59, dt.minute)\n self.assertEqual(59, dt.second)\n self.assertEqual(dt.tzname(), 'UTC')","def is_primary_time(time_string):\n return ':00' in time_string or ':30' in time_string","def is_dst ():\n\n x = datetime(datetime.now().year, 1, 1, 0, 0, 0, tzinfo=pytz.timezone(timezonename)) # Jan 1 of this year\n y = datetime.now(pytz.timezone(timezonename))\n\n # if DST is in effect, their offsets will be different\n return not (y.utcoffset() == x.utcoffset())","def test_validate(self):\n # Instances of datetime.datetime simply pass through as-is.\n self.assertEquals(self.dt_when,\n self.TDTT.validate_when(self.dt_when))\n\n # Date/time in string form should be in ISO-8601 format.\n self.assertEquals(self.dt_when,\n self.TDTT.validate_when(self.txt_when))\n\n self.assertEquals(None,\n self.TDTT.validate_when(self.NOT_DATE_AND_TIME))\n\n encoded = {'when': self.txt_when, 'unused': 'ignored'}\n decoded_props = {'when': self.dt_when}\n self.check_validate(encoded, decoded_props, self.TDTT.validate)","def CheckTransactionDate(trans_dt):\n return ConvertTransactionDateToEpochGM(trans_dt) > 0","def check_dates(dates):\n for date in dates:\n if type(date) != datetime.datetime:\n raise TypeError('Input date, %s, not datetime object' % date)","def is_date_dtype(df, col_name):\n dtype = df.dtypes[col_name]\n return np.issubdtype(dtype, np.datetime64) or np.issubdtype(dtype, np.timedelta64)","def test_datetime_with_tzinfo_provides_correct_offset(self):\n # setup\n specify_wd = self.project.activity('Specify wheel diameter')\n # save old values\n old_start, old_due = datetime.strptime(specify_wd._json_data.get('start_date'), ISOFORMAT), \\\n datetime.strptime(specify_wd._json_data.get('due_date'), ISOFORMAT)\n\n tz = pytz.timezone('Europe/Amsterdam')\n tzaware_due = tz.localize(datetime(2017, 7, 1))\n tzaware_start = tz.localize(datetime(2017, 6, 30, 0, 0, 0))\n\n specify_wd.edit(start_date=tzaware_start)\n self.assertTrue(specify_wd._json_data['start_date'], tzaware_start.isoformat(sep='T'))\n self.assertRegexpMatches(specify_wd._json_data['start_date'], r'^.*(\\+02:00|\\+01:00)$')\n\n specify_wd.edit(due_date=tzaware_due)\n self.assertTrue(specify_wd._json_data['due_date'], tzaware_due.isoformat(sep='T'))\n self.assertRegexpMatches(specify_wd._json_data['due_date'], r'^.*(\\+02:00|\\+01:00)$')\n\n # teardown\n with warnings.catch_warnings(record=False) as w:\n warnings.simplefilter(\"ignore\")\n specify_wd.edit(start_date=old_start, due_date=old_due)","def insure_localisation(dt, timezone=str(get_localzone())):\n\n if isinstance(dt, datetime):\n tz = pytz.timezone(timezone)\n if dt.tzinfo is None:\n dt = tz.localize(dt)\n return dt\n elif isinstance(dt, date):\n return dt\n else:\n raise TypeError('\"date\" or \"datetime\" object expected, not {!r}.'.format(dt.__class__.__name__))","def to_aware_datetime(ts: Timestamp):\n return utc.localize(ts.ToDatetime())","def opened_at(self, datetime: datetime) -> None:","def in_window(window, date):\n win = datetime.timedelta(window)\n if date == None:\n return False\n date = date.replace(tzinfo=None)\n delta = UTCNOW - date\n return delta <= win","def test_interpret_datetime():\n timestamps = [\n \"2019-01-01 01:01:01\",\n \"2019-01-01 01:01:01.000001\",\n \"2019-01-01T01:01:01Z\",\n \"2019-01-01T01:01:01.000001Z\",\n \"2019-01-01_01:01:01.000001\",\n \"2019-01-01_01-01-01-000000\",\n ]\n\n for timestamp in timestamps:\n dt = interpret_datetime(timestamp)\n assert isinstance(dt, datetime)\n if \".\" in timestamp:\n assert dt == datetime(2019, 1, 1, 1, 1, 1, 1)\n else:\n assert dt == datetime(2019, 1, 1, 1, 1, 1)","def validate_datetime(self, current_date):\n valid_minute = None\n valid_hour = None\n MIN_HOUR = 0\n MAX_HOUR = 23\n MIN_MINUTE = 0\n MAX_MINUTE = 59\n TIME_SEPARATOR = u':'\n\n hour, minute = current_date.split(TIME_SEPARATOR)\n\n try:\n if ((MIN_HOUR <= int(hour) <= MAX_HOUR) and\n (MIN_MINUTE <= int(minute) <= MAX_MINUTE)):\n valid_minute = int(minute)\n valid_hour = int(hour)\n except ValueError as e:\n logging.error(u'Given current time is invalid %s', e)\n\n valid_datetime = {u'hour': valid_hour, u'minute': valid_minute}\n\n return valid_datetime","def contact_now(date: str) -> bool:\n\n time_date = string_to_datetime(date)\n return date_is_today(time_date) or date_is_in_past(time_date)","def _valid_day(self, date_find):\n try:\n datetime.strptime(date_find, settings.TIME_FORMAT)\n valid = True\n except ValueError:\n valid = False\n return valid","def make_tz_aware(time_string):\n naive_dt = datetime.datetime.strptime(time_string.strip(), '%m/%d/%Y')\n aware_dt = pytz.timezone('Asia/Manila').localize(naive_dt)\n return aware_dt.astimezone(pytz.UTC)","def is_opening(self):\n now = timezone.now()\n return self.start_date.date() >= now.date()","def __eq__(self, t):\n if not isinstance(t, DateTime):\n return False\n return (self._micros, self._tz) == (t._micros, t._tz)","def valid_until(self) -> datetime:\n return self._valid_until","def match(self, dt):\n raise NotImplemented"],"string":"[\n \"def is_aware(value: datetime) -> bool:\\n\\n return value.utcoffset() is not None\",\n \"def test_make_datetime_aware(settings):\\n # Set the TIME_ZONE in the settings.\\n settings.TIME_ZONE = \\\"America/New_York\\\"\\n\\n # Calling make_datetime_aware() returns a timezone-aware datetime referring\\n # to the moment from the naive_datetime_obj, in the appropriate time zone.\\n naive_datetime_str = \\\"2018-01-01T20:00:00\\\"\\n expected_datetime_obj = make_aware(\\n datetime(year=2018, month=1, day=1, hour=20, minute=0, second=0),\\n timezone=pytz.timezone(\\\"America/New_York\\\"),\\n )\\n assert make_datetime_aware(naive_datetime_str) == expected_datetime_obj\\n\\n # Calling make_datetime_aware() for non-datetime strings returns None.\\n dt_str = \\\"\\\"\\n aware_dt = make_datetime_aware(dt_str)\\n assert aware_dt == None\\n dt_str = None\\n aware_dt = make_datetime_aware(dt_str)\\n assert aware_dt == None\",\n \"def _is_timezone_aware(value):\\n return value.utcoffset() is not None\",\n \"def valid_datetime(dt):\\n if isinstance(dt.tzinfo, tzinfo) and not datetime_ambiguous(dt):\\n return True\\n return False\",\n \"def is_datetime(self) -> bool:\\n return False\",\n \"def is_datetime(self):\\n answer = self._call('is_datetime')\\n return answer.yes\",\n \"def test_freeze_with_timezone_aware_datetime_in_non_utc():\\n utc_now = datetime.datetime.utcnow()\\n assert utc_now.tzinfo is None\\n assert utc_now == datetime.datetime(1970, 1, 1, 4)\",\n \"def check_dt_consistency(date_dt):\\n\\n # https://en.wikipedia.org/wiki/Tz_database\\n # https://www.iana.org/time-zones\\n \\n if date_dt.tzinfo is None:\\n return True\\n else:\\n \\n # This check is quite heavy but there is apparently no other way to do it.\\n if date_dt.utcoffset() != dt_from_s(s_from_dt(date_dt), tz=date_dt.tzinfo).utcoffset():\\n return False\\n else:\\n return True\",\n \"def make_aware(value: datetime, timezone=None, is_dst=None) -> datetime:\\n\\n if timezone is None:\\n timezone = get_current_timezone()\\n\\n if hasattr(timezone, \\\"localize\\\"):\\n # This method is available for pytz time zones.\\n return timezone.localize(value, is_dst=is_dst)\\n else:\\n # Check that we won't overwrite the timezone of an aware datetime.\\n if is_aware(value):\\n raise ValueError(\\\"make_aware expects a naive datetime, got %s\\\" % value)\\n # This may be wrong around DST changes!\\n return value.replace(tzinfo=timezone)\",\n \"def correct_datetime(record_datetime):\\n assert record_datetime.date() == datetime.now(timezone.utc).date()\",\n \"def _uses_datetimeblock(dtype: Union[np.dtype, ExtensionDtype]) -> bool:\\n vtype = dtype.type\\n return issubclass(vtype, np.datetime64)\",\n \"def test_freeze_with_timezone_aware_datetime_in_utc():\\n utc_now = datetime.datetime.utcnow()\\n assert utc_now.tzinfo is None\",\n \"def is_after(self, dt: datetime) -> bool:\\n return self.target_time >= make_tz_aware(dt)\",\n \"def in_between_datetime(now, start, end):\\n return start <= now <= end\",\n \"def isNaive(self, date):\\n return not self.isAware(date)\",\n \"def has_datetime_type(obj: _std_typing.Any) -> bool:\\n return obj.dtype == sc.DType.datetime64\",\n \"def is_date(dt):\\n return isinstance(dt, datetime.date) and not isinstance(dt, datetime.datetime)\",\n \"def is_naive(value: datetime) -> bool:\\n\\n return value.utcoffset() is None\",\n \"def datetime_has_tz(dt):\\n\\n if type(dt) != datetime.datetime:\\n raise TypeError(f\\\"dt must be type datetime.datetime, not {type(dt)}\\\")\\n\\n return dt.tzinfo is not None and dt.tzinfo.utcoffset(dt) is not None\",\n \"def in_datetime_interval(when, *, start=None, end=None):\\n when = as_ref_datetime(when) # This is not allowed to be None, but could be str and we need datetimes to compare.\\n start = start and as_ref_datetime(start)\\n end = end and as_ref_datetime(end)\\n return (not start or start <= when) and (not end or end >= when)\",\n \"async def datetime(self, aware=False) -> dt.datetime:\\n if aware is True:\\n now = await self.AD.sched.get_now()\\n return now.astimezone(self.AD.tz)\\n else:\\n return await self.AD.sched.get_now_naive()\",\n \"def check_date(created_at, start, end):\\n x = get_date(created_at)\\n return x <= end and x >= start\",\n \"def test_enlighten_dtime(self):\\n\\n est = pytz.timezone(\\\"EST\\\")\\n aware_dtime = datetime.datetime(\\n year=1985, month=11, day=15,\\n hour=6, minute=0,\\n tzinfo=est)\\n\\n enlightened_dtime = enlighten_dtime(aware_dtime)\\n # The tzinfo should be untouched.\\n self.assertIs(aware_dtime.tzinfo, enlightened_dtime.tzinfo)\\n\\n # This is a naive object, but has UTC values for hour.\\n utcnow = datetime.datetime.now()\\n # No tzinfo was present, so that is replaced. hour should be the same.\\n enlightened_utcnow = enlighten_dtime(utcnow)\\n self.assertEqual(enlightened_utcnow.hour, utcnow.hour)\\n self.assertIs(enlightened_utcnow.tzinfo, UTC_TZINFO)\",\n \"def office_is_open_on_datetime(iso_datetime):\\n is_open = False\\n d_time = datetime.fromisoformat(iso_datetime)\\n d_date = date(d_time.year, d_time.month, d_time.day)\\n schedule = AppointmentService.APPOINTMENT_SCHEDULE.get(d_date.weekday(), {})\\n if schedule:\\n begin_time = datetime.combine(d_date, schedule['begin'])\\n end_time = datetime.combine(d_date, schedule['end'])\\n if begin_time <= d_time <= end_time:\\n is_open = True\\n\\n return is_open\",\n \"def ensure_datetime(ob: AnyDatetime) -> datetime.datetime:\\n if isinstance(ob, datetime.datetime):\\n return ob\\n date = cast(datetime.date, ob)\\n time = cast(datetime.time, ob)\\n if isinstance(ob, datetime.date):\\n time = datetime.time()\\n if isinstance(ob, datetime.time):\\n date = datetime.date(1900, 1, 1)\\n return datetime.datetime.combine(date, time)\",\n \"def make_tz_aware(local_dt):\\n aware_dt = timezone('US/Eastern').localize(local_dt)\\n return aware_dt\",\n \"def _is_date_in_range(self, date):\\n date_obj = datetime.strptime(date.split('T')[0], '%Y-%m-%d')\\n \\\"\\\"\\\"When running under delta feed mode, we need to consider only those vulns which were\\n updated between the given offset date and today's date.\\\"\\\"\\\"\\n return self.today > date_obj >= self.start_day\",\n \"def omniscient_datetime(*args):\\n d = original_datetime(*args)\\n if settings.USE_TZ:\\n d = timezone.make_aware(d, timezone.utc)\\n return d\",\n \"def validDateTime( dateTime ):\\n try:\\n datetime.strptime( dateTime, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\" )\\n return True\\n except ValueError:\\n return False\",\n \"def adjust_icms_v1_datetime(dt_val: dt.datetime) -> dt.datetime:\\n\\n if timezone.is_aware(dt_val):\\n raise ValueError(f\\\"Unable to adjust an aware datetime value: {dt_val}\\\")\\n\\n # ICMS V1 datetime values are created using this:\\n # https://docs.oracle.com/database/121/SQLRF/functions207.htm#SQLRF06124\\n # Therefore replace the naive datetime with the correct timezone\\n aware_dt = dt_val.replace(tzinfo=UK_TZ)\\n\\n # Return a datetime that has been offset to UTC\\n utc_dt = aware_dt.astimezone(dt.timezone.utc)\\n\\n return utc_dt\",\n \"def timestamp_aware(dt):\\n if dt.tzinfo is None:\\n dt = dt.replace(tzinfo=tz.tzlocal()) # new object\\n return dt\",\n \"def get_timezone_aware_datetime(datetime):\\n if not datetime:\\n return None\\n local = timezone.get_current_timezone()\\n return (local.localize(parse(datetime), is_dst=None)).astimezone(timezone.utc)\",\n \"def aired(self):\\n # TODO: timezone\\n airdatetime = self.airdatetime\\n if airdatetime:\\n return datetime.now() >= airdatetime + timedelta(minutes=self.series.runtime)\\n else:\\n return False\",\n \"def is_in_advent() -> bool:\\n # Run the code from the 1st to the 24th\\n return datetime.now(EST).day in range(1, 25) and datetime.now(EST).month == 12\",\n \"def enforce_timezone(self, value):\\n try:\\n tz = timezone._active.value\\n if (self.default_timezone is not None) and not timezone.is_aware(value):\\n return timezone.make_aware(value, tz)\\n return value\\n except AttributeError:\\n return super().enforce_timezone(value)\",\n \"def almost_same_datetime(dt1, dt2, allowed_delta=timedelta(minutes=1)):\\r\\n return abs(dt1 - dt2) < allowed_delta\",\n \"def test_datetime(self):\\n diff = self.machine_date - self.actual_date < datetime.timedelta(0, 20, 0)\",\n \"def is_datetime(s: Union[str, int, float]):\\n if is_number(s):\\n return False\\n\\n try:\\n parse_datetime(s)\\n return True\\n except Exception:\\n return False\",\n \"def date_make_timezone_aware(datetime_object, timezone_string=None):\\n if timezone_string:\\n # make the date timezone aware using the given timezone_string\\n timezone_object = pytz_timezone_object(timezone_string)\\n timezone_aware_datetime_object = timezone_object.localize(datetime_object)\\n else:\\n # make the date timezone aware using the timezone of the current system\\n timezone_aware_datetime_object = datetime_object.astimezone()\\n\\n return timezone_aware_datetime_object\",\n \"def is_interpretable(self):\\n return bool(self.as_date() or self.as_time())\",\n \"def test_paid_at(self):\\n\\n self.assertIsInstance(self.obj.paid_at, datetime)\",\n \"def check_date(date):\\n import datetime\\n correctDate = None\\n date = str(date)\\n \\n if (len(date)!=8):\\n return False\\n year = int(date[0:4])\\n month = int(date[4:6])\\n day = int(date[6:8])\\n try:\\n datetime.datetime(year,month,day)\\n correctDate = True\\n except ValueError:\\n correctDate = False\\n return correctDate\",\n \"def could_be_datetime(val, fmt):\\n\\n if val == None or fmt == None:\\n return False\\n\\n if isinstance(val, datetime):\\n return True\\n\\n if isinstance(val, (str, unicode)):\\n if Record.is_empty_str(val) or Record.is_empty_str(fmt):\\n return False\\n\\n try:\\n d = datetime.strptime(val, fmt)\\n if not isinstance(d, datetime):\\n raise ValueError\\n else:\\n return True\\n except Exception as e:\\n logging.error(e)\\n return False\\n\\n #otherwise\\n return False\",\n \"def has_time(self):\\n return isinstance(self._start, datetime.datetime)\",\n \"def is_in_the_future(dt):\\n if dt > datetime.now(pytz.utc):\\n return True\\n return False\",\n \"def is_available_at(self, datetime):\\n for booking in self.booking_set.all():\\n if booking.schedule_start <= datetime < booking.schedule_end and not booking.is_cancelled():\\n return False\\n return True\",\n \"def test_update_at(self):\\n self.assertIsInstance(self.obj.update_at, datetime)\",\n \"def test_update_at(self):\\n self.assertIsInstance(self.obj.update_at, datetime)\",\n \"def test_update_at(self):\\n self.assertIsInstance(self.obj.update_at, datetime)\",\n \"def tz_aware(value: datetime) -> datetime:\\n if settings.USE_TZ:\\n value = value.replace(tzinfo=timezone.utc)\\n\\n return value\",\n \"def test_missing_report_datetime(self):\\n self.assertEqual(datetime.datetime.min, self.__uft.datetime('raise'))\",\n \"def is_starttrimester(today):\\n if isinstance(today, datetime):\\n if today.day == 1 and today.month == 1:\\n return True\\n elif today.day == 1 and today.month == 4:\\n return True\\n elif today.day == 1 and today.month == 7:\\n return True\\n elif today.day == 1 and today.month == 10:\\n return True\\n return False\\n else:\\n raise Exception(\\\"{} is not a datetime instance\\\".format(today))\",\n \"def datetime_checkinput(year, month, day):\\n try:\\n datetime.datetime(year, month, day)\\n except:\\n raise Invaliddatetimeinput\\n return 0\",\n \"def tz_aware(dt: datetime, default: tzinfo = tzutc()) -> datetime:\\n if dt.tzinfo is None:\\n dt = dt.replace(tzinfo=default)\\n return dt\",\n \"def test_14_digit_datetime_detection(self):\\n obj = awstats_reader.awstats_datetime('20091130165230')\\n self.assertTrue(isinstance(obj, awstats_reader.AwstatsDateTime))\",\n \"def is_valid_date_offset(user_date, offset):\\n return\",\n \"def skip_or_run_datetime_test(func):\\n\\n return skip_or_run_test_pcall_require(func, 'datetime',\\n 'does not support datetime type')\",\n \"def is_auto_assigned_date_column(column):\\n return (\\n (\\n isinstance(column.type, sa.DateTime) or\\n isinstance(column.type, sa.Date)\\n )\\n and\\n (\\n column.default or\\n column.server_default or\\n column.onupdate or\\n column.server_onupdate\\n )\\n )\",\n \"def simulatedate_checkinput(start, end):\\n start_year, start_month, start_day = parse_string_datetime(start)\\n end_year, end_month, end_day = parse_string_datetime(end)\\n if datetime_checkinput(start_year, start_month, start_day) == 0 and datetime_checkinput(end_year, end_month, end_day) == 0:\\n start_time = datetime.datetime(start_year, start_month, start_day)\\n end_time = datetime.datetime(end_year, end_month, end_day)\\n if start_time < end_time:\\n return 0\\n else:\\n raise Invaliddatetimeinput\",\n \"def test_format_builtin(self):\\n with self.settings(TIME_ZONE='UTC'):\\n datetime = aware_datetime(2015, 1, 1, 5, 7)\\n assert_equal(format_datetime(datetime, 'time'), '05:07 UTC')\",\n \"def is_soon(dt, window):\\r\\n soon = (utcnow() + datetime.timedelta(seconds=window))\\r\\n return normalize_time(dt) <= soon\",\n \"def is_soon(dt, window):\\n soon = (utcnow() + datetime.timedelta(seconds=window))\\n return normalize_time(dt) <= soon\",\n \"def _test_df_datetime(self, df):\\n date_raw = df['DateListed'].iloc[0] # e.g. '2016-01-07 00:00:00'\\n first_date_time = datetime.strptime(date_raw, \\\"%Y-%m-%d %H:%M:%S\\\")\\n assert first_date_time >= datetime(2016, 1, 1, 0, 0) and \\\\\\n first_date_time < datetime(2017, 1, 1, 0, 0)\",\n \"def is_available(iso_datetime):\\n d_time = datetime.fromisoformat(AppointmentService.closest_half(iso_datetime))\\n av_slots = AppointmentService.get_available_slots(iso_datetime)\\n is_available = (d_time in av_slots)\\n\\n return is_available\",\n \"def acceptable(self):\\n now = datetime.datetime.now()\\n origin = datetime.datetime.combine(self.date, datetime.time.min)\\n start = origin + datetime.timedelta(hours=6)\\n end = origin + datetime.timedelta(days=1)\\n morning = end + datetime.timedelta(hours=6)\\n if now < origin or now > morning:\\n return 0\\n if now >= end or now <= start:\\n return 1\\n return 3\",\n \"def validate_date(start_date_str, end_date_str):\\n # NOTE: datetime.fromisoformat() New in version Python 3.7\\n\\n try:\\n start_date_iso = datetime.fromisoformat(start_date_str)\\n end_date_iso = datetime.fromisoformat(end_date_str)\\n return True\\n except ValueError as date_error:\\n print(f\\\"Incorrect data format, datetime should be in ISO format, {date_error}\\\")\\n return False\\n if start_date_iso > end_date_iso:\\n return False\\n\\n return True\",\n \"def test_datetime_with_naive_duedate_only_fails(self):\\n # setup\\n specify_wd = self.project.activity('Specify wheel diameter')\\n\\n # save old values\\n old_start, old_due = datetime.strptime(specify_wd._json_data.get('start_date'), ISOFORMAT), \\\\\\n datetime.strptime(specify_wd._json_data.get('due_date'), ISOFORMAT)\\n naive_duedate = datetime(2017, 6, 5, 5, 0, 0)\\n with warnings.catch_warnings(record=False) as w:\\n warnings.simplefilter(\\\"ignore\\\")\\n specify_wd.edit(due_date=naive_duedate)\\n\\n # teardown\\n with warnings.catch_warnings(record=False) as w:\\n warnings.simplefilter(\\\"ignore\\\")\\n specify_wd.edit(due_date=old_due)\",\n \"def compare_datetime(self_datetime, other_datetime):\\n # pylint: disable=superfluous-parens\\n if (isinstance(self_datetime and other_datetime, (datetime, type(None)))):\\n return (\\n (self_datetime == other_datetime\\n if all(str(_.time()) != \\\"00:00:00\\\"\\n for _ in [self_datetime, other_datetime])\\n else self_datetime.date() == other_datetime.date())\\n if self_datetime and other_datetime\\n else self_datetime == other_datetime)\\n else:\\n Representation.attrs_values_types_error(\\n self_attr=self_datetime, other_attr=other_datetime,\\n expected_types=(datetime.__name__, type(None).__name__))\",\n \"def are_all_datetimes(values: List[Union[str, int, float]]):\\n for value in values:\\n if not is_datetime(value):\\n return False\\n return True\",\n \"def isdt(self):\\n return self.Units.isreftime and self._subarray.dtype == _dtype_object\",\n \"def test_date_change_fails_on_naive_datetime(self):\\n event = Event(\\n Guild(12345),\\n 'Some title',\\n datetime(2020, 10, 10, 10, 10, tzinfo=utc),\\n 'Some description')\\n with self.assertRaises(ValueError):\\n event.date = datetime(2020, 10, 10, 12, 10)\",\n \"async def test_has_group_address_localtime(self):\\n xknx = XKNX()\\n self.datetime = DateTime(\\n xknx,\\n \\\"TestDateTime\\\",\\n group_address=\\\"1/2/3\\\",\\n group_address_state=\\\"1/2/4\\\",\\n localtime=True,\\n )\\n assert self.datetime.has_group_address(GroupAddress(\\\"1/2/3\\\"))\\n # group_address_state ignored when using localtime\\n assert not self.datetime.has_group_address(GroupAddress(\\\"1/2/4\\\"))\",\n \"def _is_ready(self, as_of):\\n if self.is_one_off():\\n return self.initial_billing_cycle.date_range.lower <= as_of\\n else:\\n return True\",\n \"def date_temporal_paradox_free(self):\\n valid_date = True\\n new_val = self.date_edit.text()\\n datetime_object = datetime.strptime(new_val, \\\"%Y-%m-%d\\\")\\n\\n if datetime_object > datetime.now():\\n valid_date = False\\n return valid_date\",\n \"def is_outdated(self):\\n today = datetime.datetime.today()\\n day = datetime.datetime.combine(self.date, self.start_time)\\n return day <= today\",\n \"def test_8_digit_date_detection(self):\\n obj = awstats_reader.awstats_datetime('20091130')\\n self.assertTrue(isinstance(obj, awstats_reader.AwstatsDate))\",\n \"def test_created_at(self):\\n self.assertIsInstance(self.obj.created_at, datetime)\",\n \"def test_created_at(self):\\n self.assertIsInstance(self.obj.created_at, datetime)\",\n \"def test_created_at(self):\\n self.assertIsInstance(self.obj.created_at, datetime)\",\n \"def test_datetime_from(self):\\n dt = sync.datetime_from('2012-09-09T00:00:00') # EDT\\n self.assertEqual(2012, dt.year)\\n self.assertEqual(9, dt.month)\\n self.assertEqual(10, dt.day)\\n self.assertEqual(3, dt.hour)\\n self.assertEqual(59, dt.minute)\\n self.assertEqual(59, dt.second)\\n self.assertEqual(dt.tzname(), 'UTC')\\n\\n dt = sync.datetime_from('2012-12-09T00:00:00') # EST\\n self.assertEqual(2012, dt.year)\\n self.assertEqual(12, dt.month)\\n self.assertEqual(10, dt.day)\\n self.assertEqual(4, dt.hour)\\n self.assertEqual(59, dt.minute)\\n self.assertEqual(59, dt.second)\\n self.assertEqual(dt.tzname(), 'UTC')\",\n \"def is_primary_time(time_string):\\n return ':00' in time_string or ':30' in time_string\",\n \"def is_dst ():\\n\\n x = datetime(datetime.now().year, 1, 1, 0, 0, 0, tzinfo=pytz.timezone(timezonename)) # Jan 1 of this year\\n y = datetime.now(pytz.timezone(timezonename))\\n\\n # if DST is in effect, their offsets will be different\\n return not (y.utcoffset() == x.utcoffset())\",\n \"def test_validate(self):\\n # Instances of datetime.datetime simply pass through as-is.\\n self.assertEquals(self.dt_when,\\n self.TDTT.validate_when(self.dt_when))\\n\\n # Date/time in string form should be in ISO-8601 format.\\n self.assertEquals(self.dt_when,\\n self.TDTT.validate_when(self.txt_when))\\n\\n self.assertEquals(None,\\n self.TDTT.validate_when(self.NOT_DATE_AND_TIME))\\n\\n encoded = {'when': self.txt_when, 'unused': 'ignored'}\\n decoded_props = {'when': self.dt_when}\\n self.check_validate(encoded, decoded_props, self.TDTT.validate)\",\n \"def CheckTransactionDate(trans_dt):\\n return ConvertTransactionDateToEpochGM(trans_dt) > 0\",\n \"def check_dates(dates):\\n for date in dates:\\n if type(date) != datetime.datetime:\\n raise TypeError('Input date, %s, not datetime object' % date)\",\n \"def is_date_dtype(df, col_name):\\n dtype = df.dtypes[col_name]\\n return np.issubdtype(dtype, np.datetime64) or np.issubdtype(dtype, np.timedelta64)\",\n \"def test_datetime_with_tzinfo_provides_correct_offset(self):\\n # setup\\n specify_wd = self.project.activity('Specify wheel diameter')\\n # save old values\\n old_start, old_due = datetime.strptime(specify_wd._json_data.get('start_date'), ISOFORMAT), \\\\\\n datetime.strptime(specify_wd._json_data.get('due_date'), ISOFORMAT)\\n\\n tz = pytz.timezone('Europe/Amsterdam')\\n tzaware_due = tz.localize(datetime(2017, 7, 1))\\n tzaware_start = tz.localize(datetime(2017, 6, 30, 0, 0, 0))\\n\\n specify_wd.edit(start_date=tzaware_start)\\n self.assertTrue(specify_wd._json_data['start_date'], tzaware_start.isoformat(sep='T'))\\n self.assertRegexpMatches(specify_wd._json_data['start_date'], r'^.*(\\\\+02:00|\\\\+01:00)$')\\n\\n specify_wd.edit(due_date=tzaware_due)\\n self.assertTrue(specify_wd._json_data['due_date'], tzaware_due.isoformat(sep='T'))\\n self.assertRegexpMatches(specify_wd._json_data['due_date'], r'^.*(\\\\+02:00|\\\\+01:00)$')\\n\\n # teardown\\n with warnings.catch_warnings(record=False) as w:\\n warnings.simplefilter(\\\"ignore\\\")\\n specify_wd.edit(start_date=old_start, due_date=old_due)\",\n \"def insure_localisation(dt, timezone=str(get_localzone())):\\n\\n if isinstance(dt, datetime):\\n tz = pytz.timezone(timezone)\\n if dt.tzinfo is None:\\n dt = tz.localize(dt)\\n return dt\\n elif isinstance(dt, date):\\n return dt\\n else:\\n raise TypeError('\\\"date\\\" or \\\"datetime\\\" object expected, not {!r}.'.format(dt.__class__.__name__))\",\n \"def to_aware_datetime(ts: Timestamp):\\n return utc.localize(ts.ToDatetime())\",\n \"def opened_at(self, datetime: datetime) -> None:\",\n \"def in_window(window, date):\\n win = datetime.timedelta(window)\\n if date == None:\\n return False\\n date = date.replace(tzinfo=None)\\n delta = UTCNOW - date\\n return delta <= win\",\n \"def test_interpret_datetime():\\n timestamps = [\\n \\\"2019-01-01 01:01:01\\\",\\n \\\"2019-01-01 01:01:01.000001\\\",\\n \\\"2019-01-01T01:01:01Z\\\",\\n \\\"2019-01-01T01:01:01.000001Z\\\",\\n \\\"2019-01-01_01:01:01.000001\\\",\\n \\\"2019-01-01_01-01-01-000000\\\",\\n ]\\n\\n for timestamp in timestamps:\\n dt = interpret_datetime(timestamp)\\n assert isinstance(dt, datetime)\\n if \\\".\\\" in timestamp:\\n assert dt == datetime(2019, 1, 1, 1, 1, 1, 1)\\n else:\\n assert dt == datetime(2019, 1, 1, 1, 1, 1)\",\n \"def validate_datetime(self, current_date):\\n valid_minute = None\\n valid_hour = None\\n MIN_HOUR = 0\\n MAX_HOUR = 23\\n MIN_MINUTE = 0\\n MAX_MINUTE = 59\\n TIME_SEPARATOR = u':'\\n\\n hour, minute = current_date.split(TIME_SEPARATOR)\\n\\n try:\\n if ((MIN_HOUR <= int(hour) <= MAX_HOUR) and\\n (MIN_MINUTE <= int(minute) <= MAX_MINUTE)):\\n valid_minute = int(minute)\\n valid_hour = int(hour)\\n except ValueError as e:\\n logging.error(u'Given current time is invalid %s', e)\\n\\n valid_datetime = {u'hour': valid_hour, u'minute': valid_minute}\\n\\n return valid_datetime\",\n \"def contact_now(date: str) -> bool:\\n\\n time_date = string_to_datetime(date)\\n return date_is_today(time_date) or date_is_in_past(time_date)\",\n \"def _valid_day(self, date_find):\\n try:\\n datetime.strptime(date_find, settings.TIME_FORMAT)\\n valid = True\\n except ValueError:\\n valid = False\\n return valid\",\n \"def make_tz_aware(time_string):\\n naive_dt = datetime.datetime.strptime(time_string.strip(), '%m/%d/%Y')\\n aware_dt = pytz.timezone('Asia/Manila').localize(naive_dt)\\n return aware_dt.astimezone(pytz.UTC)\",\n \"def is_opening(self):\\n now = timezone.now()\\n return self.start_date.date() >= now.date()\",\n \"def __eq__(self, t):\\n if not isinstance(t, DateTime):\\n return False\\n return (self._micros, self._tz) == (t._micros, t._tz)\",\n \"def valid_until(self) -> datetime:\\n return self._valid_until\",\n \"def match(self, dt):\\n raise NotImplemented\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7423152","0.6706246","0.656491","0.65267324","0.6137775","0.60896856","0.6019291","0.59568536","0.57755363","0.57708514","0.5679119","0.5660917","0.56022364","0.55941117","0.5527686","0.55162454","0.54947275","0.5432787","0.5420078","0.5379313","0.5340649","0.5322148","0.5298153","0.5293154","0.52929807","0.52778995","0.52714974","0.5259795","0.5222237","0.5187491","0.5122782","0.5093069","0.50930434","0.50884366","0.50757617","0.5070136","0.50533664","0.50315714","0.50046873","0.4992302","0.49912512","0.49733782","0.49728695","0.4943792","0.49412808","0.49187753","0.49183458","0.49183458","0.49183458","0.4893785","0.48789874","0.48788083","0.4866971","0.48667616","0.4854196","0.4842199","0.48249328","0.48244613","0.4812351","0.48117363","0.48114142","0.48085472","0.48025632","0.47908926","0.47836158","0.47832185","0.47677326","0.4736424","0.4735857","0.47207585","0.4705436","0.47045606","0.4693998","0.46798086","0.4678321","0.4671177","0.4665842","0.4665842","0.4665842","0.46651402","0.46594054","0.46457368","0.46456045","0.4627478","0.46231112","0.46202415","0.46185857","0.461694","0.46167815","0.46130997","0.46123692","0.46101803","0.46082205","0.46035638","0.4602636","0.45974898","0.45961443","0.45913842","0.45883387","0.45868957"],"string":"[\n \"0.7423152\",\n \"0.6706246\",\n \"0.656491\",\n \"0.65267324\",\n \"0.6137775\",\n \"0.60896856\",\n \"0.6019291\",\n \"0.59568536\",\n \"0.57755363\",\n \"0.57708514\",\n \"0.5679119\",\n \"0.5660917\",\n \"0.56022364\",\n \"0.55941117\",\n \"0.5527686\",\n \"0.55162454\",\n \"0.54947275\",\n \"0.5432787\",\n \"0.5420078\",\n \"0.5379313\",\n \"0.5340649\",\n \"0.5322148\",\n \"0.5298153\",\n \"0.5293154\",\n \"0.52929807\",\n \"0.52778995\",\n \"0.52714974\",\n \"0.5259795\",\n \"0.5222237\",\n \"0.5187491\",\n \"0.5122782\",\n \"0.5093069\",\n \"0.50930434\",\n \"0.50884366\",\n \"0.50757617\",\n \"0.5070136\",\n \"0.50533664\",\n \"0.50315714\",\n \"0.50046873\",\n \"0.4992302\",\n \"0.49912512\",\n \"0.49733782\",\n \"0.49728695\",\n \"0.4943792\",\n \"0.49412808\",\n \"0.49187753\",\n \"0.49183458\",\n \"0.49183458\",\n \"0.49183458\",\n \"0.4893785\",\n \"0.48789874\",\n \"0.48788083\",\n \"0.4866971\",\n \"0.48667616\",\n \"0.4854196\",\n \"0.4842199\",\n \"0.48249328\",\n \"0.48244613\",\n \"0.4812351\",\n \"0.48117363\",\n \"0.48114142\",\n \"0.48085472\",\n \"0.48025632\",\n \"0.47908926\",\n \"0.47836158\",\n \"0.47832185\",\n \"0.47677326\",\n \"0.4736424\",\n \"0.4735857\",\n \"0.47207585\",\n \"0.4705436\",\n \"0.47045606\",\n \"0.4693998\",\n \"0.46798086\",\n \"0.4678321\",\n \"0.4671177\",\n \"0.4665842\",\n \"0.4665842\",\n \"0.4665842\",\n \"0.46651402\",\n \"0.46594054\",\n \"0.46457368\",\n \"0.46456045\",\n \"0.4627478\",\n \"0.46231112\",\n \"0.46202415\",\n \"0.46185857\",\n \"0.461694\",\n \"0.46167815\",\n \"0.46130997\",\n \"0.46123692\",\n \"0.46101803\",\n \"0.46082205\",\n \"0.46035638\",\n \"0.4602636\",\n \"0.45974898\",\n \"0.45961443\",\n \"0.45913842\",\n \"0.45883387\",\n \"0.45868957\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6891435"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":1399,"cells":{"query":{"kind":"string","value":"For date and time values shows how many seconds, minutes or hours ago compared to current timestamp returns representing string."},"document":{"kind":"string","value":"def naturaltime(value):\n if not isinstance(value, date): # datetime is a subclass of date\n return value\n\n now = datetime.now(utc if is_aware(value) else None)\n if value < now:\n delta = now - value\n if delta.days != 0:\n return 'hace %(delta)s' % {'delta': defaultfilters.timesince(value)}\n elif delta.seconds == 0:\n return 'ahora'\n elif delta.seconds < 60:\n return u'hace %(count)s segundos' % {'count': delta.seconds}\n elif delta.seconds // 60 < 60:\n count = delta.seconds // 60\n return u'hace %(count)s minutos' % {'count': count}\n else:\n count = delta.seconds // 60 // 60\n return u'hace %(count)s horas' % {'count': count}"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def humanize_ts(timestamp=False):\n now = datetime.now()\n diff = now - datetime.fromtimestamp(timestamp)\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return ''\n\n if day_diff == 0:\n if second_diff < 10:\n return \"just now\"\n if second_diff < 60:\n return str(int(second_diff)) + \" seconds ago\"\n if second_diff < 120:\n return \"a minute ago\"\n if second_diff < 3600:\n return str(int(second_diff / 60)) + \" minutes ago\"\n if second_diff < 7200:\n return \"an hour ago\"\n if second_diff < 86400:\n return str(int(second_diff / 3600)) + \" hours ago\"\n if day_diff == 1:\n return \"Yesterday\"\n if day_diff < 7:\n return str(day_diff) + \" days ago\"\n if day_diff < 31:\n return str(int(day_diff / 7)) + \" weeks ago\"\n if day_diff < 365:\n return str(int(day_diff / 30)) + \" months ago\"\n return str(int(day_diff / 365)) + \" years ago\"","def pretty_date(time=False):\n now = datetime.now()\n if type(time) is int:\n diff = now - datetime.fromtimestamp(time)\n elif isinstance(time, datetime):\n diff = now - time\n elif not time:\n diff = now - now\n else:\n diff = now - now\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return ''\n\n if day_diff == 0:\n if second_diff < 10:\n return \"just now\"\n if second_diff < 60:\n return str(int(round(second_diff, 0))) + \" seconds ago\"\n if second_diff < 120:\n return \"a minute ago\"\n if second_diff < 3600:\n return str(int(round(second_diff / 60, 0))) + \" minutes ago\"\n if second_diff < 7200:\n return \"an hour ago\"\n if second_diff < 86400:\n return str(int(round(second_diff / 3600, 0))) + \" hours ago\"\n if day_diff == 1:\n return \"Yesterday\"\n if day_diff < 7:\n return str(int(round(day_diff, 0))) + \" days ago\"\n if day_diff < 31:\n return str(int(round(day_diff / 7, 0))) + \" weeks ago\"\n if day_diff < 365:\n return str(int(round(day_diff / 30, 0))) + \" months ago\"\n return str(int(round(day_diff / 365, 0))) + \" years ago\"","def ago(self):\n return human(self.timestamp/1000.0, precision=1, abbreviate=True)","def time_since(timestamp=None):\n rstr = \"\"\n if not timestamp or not isinstance(timestamp, datetime.datetime):\n return rstr\n\n now = timezone.now()\n timediff = now - timestamp\n days = timediff.days\n weeks = days//7\n months = days//30\n minutes = timediff.seconds % 3600 // 60\n seconds = timediff.seconds % 3600 % 60\n hours = minutes // 60\n\n if days > 365:\n return \"> a year\"\n if months > 0:\n if months == 1:\n tstr = \"month\"\n else:\n tstr = \"months\"\n rstr = rstr + \"%s %s\" % (months, tstr)\n return rstr\n if weeks > 0:\n if weeks == 1:\n tstr = \"week\"\n else:\n tstr = \"weeks\"\n rstr = rstr + \"%s %s\" % (weeks, tstr)\n return rstr\n if days > 0:\n if days == 1:\n tstr = \"day\"\n else:\n tstr = \"days\"\n rstr = rstr + \"%s %s\" % (days, tstr)\n return rstr\n elif hours > 0:\n if hours == 1:\n tstr = \"hour\"\n else:\n tstr = \"hours\"\n rstr = rstr + \"%s %s\" % (hours, tstr)\n return rstr\n elif minutes > 0:\n if minutes == 1:\n tstr = \"min\"\n else:\n tstr = \"mins\"\n rstr = rstr + \"%s %s\" % (minutes, tstr)\n return rstr\n elif seconds > 0:\n if seconds == 1:\n tstr = \"sec\"\n else:\n tstr = \"secs\"\n rstr = rstr + \"%s %s\" % (seconds, tstr)\n return rstr\n else:\n return \"Now\"","def relativeTime(date):\n diff = datetime.utcnow() - date\n\n if diff.days > 7 or diff.days < 0:\n return date.ctime()\n elif diff.days == 1:\n return '1 day ago'\n elif diff.days > 1:\n return '%d days ago' % diff.days\n elif diff.seconds <= 1:\n return 'just now'\n elif diff.seconds < 60:\n return '%d seconds ago' % diff.seconds\n elif diff.seconds < (60 * 2):\n return '1 minute ago'\n elif diff.seconds < (60 * 60):\n return '%d minutes ago' % (diff.seconds / 60)\n elif diff.seconds < (60 * 60 * 2):\n return '1 hour ago'\n else:\n return '%d hours ago' % (diff.seconds / (60 * 60))","def time_since_as_text(time=False):\n now = datetime.now(timezone.utc)\n if type(time) is int:\n diff = now - datetime.fromtimestamp(time)\n elif isinstance(time,datetime):\n diff = now - time\n elif not time:\n diff = now - now\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return ''\n\n if day_diff == 0:\n if second_diff < 10:\n return \"nyss\"\n if second_diff < 60:\n return str(second_diff) + \" sekunder sedan\"\n if second_diff < 120:\n return \"a minute ago\"\n if second_diff < 3600:\n return str(floor(second_diff / 60)) + \" minuter sedan\"\n if second_diff < 7200:\n return \"en timme sedan\"\n if second_diff < 86400:\n return str(floor(second_diff / 3600)) + \" timmar sedan\"\n if day_diff == 1:\n return \"Igår\"\n if day_diff < 7:\n return str(day_diff) + \" dagar sedan\"\n if day_diff < 31:\n return str(floor(day_diff / 7)) + \" veckor sedan\"\n if day_diff < 365:\n return str(floor(day_diff / 30)) + \" månder sedan\"\n return str(day_diff / 365) + \" år sedan\"","def pretty_date(time=False):\n from datetime import datetime\n now = datetime.now()\n if type(time) is int:\n diff = now - datetime.fromtimestamp(time)\n elif isinstance(time,datetime):\n diff = now - time \n elif not time:\n diff = now - now\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return ''\n\n if day_diff == 0:\n if second_diff < 10:\n return \"just now\"\n if second_diff < 60:\n return str(second_diff) + \" seconds ago\"\n if second_diff < 120:\n return \"a minute ago\"\n if second_diff < 3600:\n return str( second_diff / 60 ) + \" minutes ago\"\n if second_diff < 7200:\n return \"an hour ago\"\n if second_diff < 86400:\n return str( second_diff / 3600 ) + \" hours ago\"\n if day_diff == 1:\n return \"Yesterday\"\n if day_diff < 7:\n return str(day_diff) + \" days ago\"\n if day_diff < 31:\n return str(day_diff/7) + \" weeks ago\"\n if day_diff < 365:\n return str(day_diff/30) + \" months ago\"\n return str(day_diff/365) + \" years ago\"","def pretty_date(time=False):\n from datetime import datetime\n\n now = datetime.now()\n if type(time) is int:\n diff = now - datetime.fromtimestamp(time)\n elif isinstance(time, datetime):\n diff = now - time\n elif not time:\n diff = now - now\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return \"\"\n\n if day_diff == 0:\n if second_diff < 10:\n return \"just now\"\n if second_diff < 60:\n return str(second_diff) + \" seconds ago\"\n if second_diff < 120:\n return \"a minute ago\"\n if second_diff < 3600:\n return str(second_diff / 60) + \" minutes ago\"\n if second_diff < 7200:\n return \"an hour ago\"\n if second_diff < 86400:\n return str(second_diff / 3600) + \" hours ago\"\n if day_diff == 1:\n return \"Yesterday\"\n if day_diff < 7:\n return str(day_diff) + \" days ago\"\n if day_diff < 31:\n return str(day_diff / 7) + \" weeks ago\"\n if day_diff < 365:\n return str(day_diff / 30) + \" months ago\"\n return str(day_diff / 365) + \" years ago\"","def pretty_date(time=False):\r\n from datetime import datetime\r\n import dateutil.parser\r\n now = datetime.now()\r\n if type(time) is str or type(time) is unicode:\r\n time = dateutil.parser.parse(time)\r\n if type(time) is int:\r\n diff = now - datetime.fromtimestamp(time)\r\n elif isinstance(time, datetime):\r\n diff = now - time\r\n elif not time:\r\n diff = now - now\r\n second_diff = diff.seconds\r\n day_diff = diff.days\r\n\r\n if day_diff < 0:\r\n return ''\r\n\r\n if day_diff == 0:\r\n if second_diff < 10:\r\n return \"just now\"\r\n if second_diff < 60:\r\n return str(second_diff) + \" seconds ago\"\r\n if second_diff < 120:\r\n return \"a minute ago\"\r\n if second_diff < 3600:\r\n return ' '.join([str(second_diff / 60), \"minutes ago\"])\r\n if second_diff < 7200:\r\n return \"an hour ago\"\r\n if second_diff < 86400:\r\n return ' '.join([str(second_diff / 3600), \"hours ago\"])\r\n if day_diff == 1:\r\n return \"Yesterday\"\r\n if day_diff < 7:\r\n return ' '.join([str(day_diff), \"days ago\"])\r\n if day_diff < 31:\r\n return ' '.join([str(day_diff / 7), \"weeks ago\"])\r\n if day_diff < 60:\r\n return ' '.join([str(day_diff / 30), \"month ago\"])\r\n if day_diff < 365:\r\n return ' '.join([str(day_diff / 30), \"months ago\"])\r\n if day_diff < (365 * 2):\r\n return ' '.join([str(day_diff / 365), \"year ago\"])\r\n return ' '.join([str(day_diff / 365), \"years ago\"])","def timeago(time=False):\n\n return arrow.get(time).humanize()","def relative_datetime(self):\n now = datetime.now(timezone.utc)\n created_at = self.created_at.astimezone(timezone.utc)\n\n delta = humanize.naturaldelta(abs(created_at - now))\n tense = \"from now\" if now < created_at else \"ago\"\n\n return f\"{delta} {tense}\"","def naturaltime(value):\n try:\n value = datetime.datetime(value.year, value.month, value.day, value.hour, value.minute, value.second)\n except AttributeError:\n return value\n except ValueError:\n return value\n\n if getattr(value, 'tzinfo', None):\n now = datetime.datetime.now(LocalTimezone(value))\n else:\n now = datetime.datetime.now()\n now = now - timedelta(0, 0, now.microsecond)\n if value < now:\n delta = now - value\n if delta.days != 0:\n return pgettext(\n 'naturaltime', '%(delta)s ago'\n ) % {'delta': defaultfilters.timesince(value)}\n elif delta.seconds == 0:\n return _(u'now')\n elif delta.seconds < 60:\n return ungettext(\n u'a second ago', u'%(count)s seconds ago', delta.seconds\n ) % {'count': delta.seconds}\n elif delta.seconds // 60 < 60:\n count = delta.seconds // 60\n return ungettext(\n u'a minute ago', u'%(count)s minutes ago', count\n ) % {'count': count}\n else:\n count = delta.seconds // 60 // 60\n return ungettext(\n u'an hour ago', u'%(count)s hours ago', count\n ) % {'count': count}\n else:\n delta = value - now\n if delta.days != 0:\n return pgettext(\n 'naturaltime', '%(delta)s from now'\n ) % {'delta': defaultfilters.timeuntil(value)}\n elif delta.seconds == 0:\n return _(u'now')\n elif delta.seconds < 60:\n return ungettext(\n u'a second from now', u'%(count)s seconds from now', delta.seconds\n ) % {'count': delta.seconds}\n elif delta.seconds // 60 < 60:\n count = delta.seconds // 60\n return ungettext(\n u'a minute from now', u'%(count)s minutes from now', count\n ) % {'count': count}\n else:\n count = delta.seconds // 60 // 60\n return ungettext(\n u'an hour from now', u'%(count)s hours from now', count\n ) % {'count': count}","def howLongAgo(time=False):\n now = timezone.now()\n if type(time) is int:\n diff = now - datetime.fromtimestamp(time)\n elif isinstance(time,datetime):\n diff = now - time\n elif not time:\n diff = now - now\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return ''\n\n if day_diff == 0:\n if second_diff < 10:\n return \"genau jetzt\"\n if second_diff < 60:\n return \"vor \" + str(second_diff) + \" Sek.\"\n if second_diff < 120:\n return \"vor einer Min.\"\n if second_diff < 3600:\n return \"vor \" + str( second_diff / 60 ) + \" Min.\"\n if second_diff < 7200:\n return \"vor einer St.\"\n if second_diff < 86400:\n return \"vor \" + str( second_diff / 3600 ) + \" St.\"\n if day_diff == 1:\n return \"Gestern\"\n if day_diff < 7:\n return \"vor \" + str(day_diff) + \" Tagen\"\n if day_diff < 31:\n return \"vor \" + str(day_diff/7) + \" Wochen\"\n if day_diff < 365:\n return \"vor \" + str(day_diff/30) + \" Monaten\"\n return \"vor \" + str(day_diff/365) + \" Jahren\"","def get_formatted_time() -> datetime.strftime:\n\t\n\tnow = datetime.now() # time now\n\thalf_hour = (now - timedelta(minutes = 30)) # time 30 min ago\n\t# returns half hour ago to accommodate for failed checks\n\t# (bc twint behaves as if none found if check failed)\n\tcurrent_time = half_hour.strftime(\"%Y-%m-%d %H:%M:%S\")\n\treturn current_time","def time_now() -> str:\n return datetime_to_str(datetime_now())","def pretty_date(date: datetime):\n if not isinstance(date, datetime) or date > NOW:\n raise ValueError('pretty_date() only accepts datetime objects in the past')\n diff = NOW - date\n seconds = int(diff.total_seconds())\n minutes = seconds // 60\n hours = minutes // 60\n # This doesn't _feel_ very pythonic…\n if seconds < 10:\n return 'just now'\n if seconds < 60:\n return f'{seconds} seconds ago'\n if minutes < 2:\n return 'a minute ago'\n if minutes < 60:\n return f'{minutes} minutes ago'\n if hours < 2:\n return 'an hour ago'\n if hours < 24:\n return f'{hours} hours ago'\n if hours < 48:\n return 'yesterday'\n return date.strftime('%m/%d/%y')","def pretty_date(time=False):\n now = datetime.datetime.utcnow()\n if type(time) is int:\n diff = now - datetime.datetime.fromtimestamp(time)\n elif isinstance(time, datetime.datetime):\n diff = now - time\n elif not time:\n diff = now - now\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n day_diff *= -1\n second_diff *= -1\n if day_diff < 1:\n if second_diff < 10:\n return ugettext('imminently')\n if second_diff < 60:\n return ungettext('{n} second from now', '{n} seconds from now', second_diff).format(n=second_diff)\n if second_diff < 120:\n return ugettext('in a minute')\n if second_diff < 3600:\n return ungettext('{n} minute from now', '{n} minutes from now', second_diff / 60).format(n=second_diff / 60)\n if second_diff < 7200:\n return ugettext('in an hour')\n if second_diff < 86400:\n return ungettext('{n} hour from now', '{n} hours from now', second_diff / 3600).format(n=second_diff / 3600)\n if day_diff == 1:\n return ugettext('tomorrow')\n if day_diff < 7:\n return ungettext('{n} day from now', '{n} days from now', day_diff).format(n=day_diff)\n if day_diff < 31:\n return ungettext('{n} week from now', '{n} weeks from now', day_diff / 7).format(n=day_diff / 7)\n if day_diff < 365:\n return ungettext('{n} month from now', '{n} months from now', day_diff / 30).format(n=day_diff / 30)\n return ungettext('{n} year from now', '{n} years from now', day_diff / 365).format(n=day_diff / 365)\n\n if day_diff == 0:\n if second_diff < 10:\n return ugettext('just now')\n if second_diff < 60:\n return ungettext('{n} second ago', '{n} seconds ago', second_diff).format(n=second_diff)\n if second_diff < 120:\n return ugettext('a minute ago')\n if second_diff < 3600:\n return ungettext('{n} minute ago', '{n} minutes ago', second_diff / 60).format(n=second_diff / 60)\n if second_diff < 7200:\n return ugettext('an hour ago')\n if second_diff < 86400:\n return ungettext('{n} hour ago', '{n} hours ago', second_diff / 3600).format(n=second_diff / 3600)\n if day_diff == 1:\n return ugettext('yesterday')\n if day_diff < 7:\n return ungettext('{n} day ago', '{n} days ago', day_diff).format(n=day_diff)\n if day_diff < 31:\n return ungettext('{n} week ago', '{n} weeks ago', day_diff / 7).format(n=day_diff / 7)\n if day_diff < 365:\n return ungettext('{n} month ago', '{n} months ago', day_diff / 30).format(n=day_diff / 30)\n return ungettext('{n} year ago', '{n} years ago', day_diff / 365).format(n=day_diff / 365)","def get_time(self):\n return ''","async def humanize_time(self, value):\n if value is None:\n return \"None\"\n return str(datetime.timedelta(seconds=value))","def shorttimesince(value, arg=None):\r\n from django.utils.timesince import timesince\r\n if not value:\r\n return u''\r\n if arg:\r\n return calculate_shorttimesince(arg, value)\r\n return calculate_shorttimesince(value)","def get_date():\n return (datetime.now() - TIMEDELTA).isoformat()","def formatted_time() -> datetime.datetime:\r\n return datetime.datetime.now()","def get_current_timestamp_str(self):\n return str(time.mktime(datetime.datetime.now().timetuple()))","def nowStr(time=None):\n if time is None:\n time = datetime.now().time()\n if time.minute < 10:\n return time.strftime(\"%H ноль %m\")\n else:\n return time.strftime(\"%H %M\")","def human_date(self, date):\n return timeago.format(date)","def str_current_time():\n return strftime(\"%Y_%m_%d_%H_%M_%S_%Z\", gmtime())","def get_now_time():\r\n return '[' + datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f') + ']: '","def get_elapsed_timestamp(self) -> str:\n t = self.elapsed_time\n minutes = int(t / 60)\n seconds = int(t - (60 * minutes))\n millis = int(100 * (t - int(t)))\n return '{:>02d}:{:>02d}.{:<02d}'.format(minutes, seconds, millis)","def time_created(self) -> str:\n return pulumi.get(self, \"time_created\")","def time_created(self) -> str:\n return pulumi.get(self, \"time_created\")","def time_created(self) -> str:\n return pulumi.get(self, \"time_created\")","def time( self, mess, args):\n return str(datetime.datetime.now())","def time( self, mess, args):\n return str(datetime.datetime.now())","def now_short(_format=\"%Y%m%d-%H%M%S\"):\n timeString = time.strftime(_format, time.localtime()) + \"\\t\"\n return timeString","def since(self):\n return str(datetime.datetime.now() - self._refreshed_at)","def get_answer_time(self):\n sec = (self.updated_at - self.created_at).total_seconds()\n return f'{int((sec / 60) % 60):02d}:{int(sec):02d}'","def get_time():\n ct = time.time()\n lt = time.gmtime(ct)\n msec = int((ct - int(ct)) * 1000)\n return f'{time.strftime(DATE_FMT, lt)}.{msec:0>3}'","def now(time):\n a = datetime.fromtimestamp(time).strftime('%Y-%m-%d %H:%M:%S')\n return a","def now(time):\n a = datetime.fromtimestamp(time).strftime('%Y-%m-%d %H:%M:%S')\n return a","def create_human_readable_timestamp(self, now):\n hrdatetime = now.strftime('%c')\n return hrdatetime","def timestr():\n return dt.strftime(dt.now(),'%H:%M:%S')","def adjustedCompareValue(self, value):\n if value.startswith('now'):\n return repr(GenTime())\n return value","def age(self) -> str:\n tdelta = dt.now() - self.created_timestamp\n if tdelta.days >= 548: # enough to round it up to 2 years\n return f'about {tdelta.days/365:.0f} years'\n elif tdelta.days >= 345: # enough to round it up to 1 year (so it doesn't report '12 months')\n return f'about a year'\n elif tdelta.days > 45: # beyond 1 month (after rounding)\n return f'about {tdelta.days/30:.0f} months'\n elif tdelta.days > 24: # enough to round it up to 1 month (so it doesn't report '4 weeks')\n return f'about a month'\n elif tdelta.days > 7:\n # round to nearest half, dropping '.0' when whole\n return f'{round((tdelta.days/7)*2)/2:g} weeks'\n elif tdelta.days == 7:\n return 'a week'\n elif tdelta.days > 1:\n return f'{tdelta.days} days'\n elif tdelta.days == 1:\n return f'a day'\n # break it down into parts of a day\n hours = tdelta.seconds // 3600\n if hours > 1:\n return f'{hours:.0f} hours'\n elif hours == 1:\n return f'an hour'\n minutes = tdelta.seconds % 3600 / 60\n if minutes > 1:\n return f'{minutes:.0f} minutes'\n elif minutes == 1:\n return f'a minute'\n return 'moments'","def time_since(dt, default=\"just now\"):\n\t\n\tnow = datetime.utcnow()\n\tdiff = now - dt\n\t\n\tperiods = (\n\t\t(diff.days / 365, \"year\", \"years\"),\n\t\t(diff.days / 30, \"month\", \"months\"),\n\t\t(diff.days / 7, \"week\", \"weeks\"),\n\t\t(diff.days, \"day\", \"days\"),\n\t\t(diff.seconds / 3600, \"hour\", \"hours\"),\n\t\t(diff.seconds / 60, \"minute\", \"minutes\"),\n\t\t(diff.seconds, \"second\", \"seconds\"),\n\t)\n\n\tfor period, singular, plural in periods:\n\t\tif period:\n\t\t\treturn \"%d %s ago\" % (period, singular if period == 1 else plural)\n\n\treturn default","def get_formatted_duration(self, prev_time):\n duration = time() - prev_time\n if duration < 60:\n unit = 's'\n elif duration < 3600:\n duration /= 60\n unit = 'm'\n else:\n duration /= 3600\n unit = 'h'\n return self.format_num(duration) + unit","def now(self):\n return time.strftime(r'[%d/%b/%Y:%H:%M:%S]')","def _time_delta_from_info(info):\n now = datetime.datetime.now()\n then = info.start_time\n return str(now.replace(microsecond=0) - then.replace(microsecond=0))","def __str__(self):\n return \"({0}:{1}:{2})\".format(self.hours, self.minutes, self.seconds)","def now_short(_format=\"%Y%m%d-%H%M%S\"):\n return time.strftime(_format, time.localtime()) + \"\\t\"","def _time_str(self):\n try:\n if not self._time:\n raise ValueError\n format_ = '%a, %d %b %Y %H:%M:%S'\n return datetime.fromtimestamp(float(self._time)).strftime(format_)\n except ValueError:\n return plastic_date()","def _getUpTime(self):\n diff = (datetime.datetime.now() - self._startTime).__str__()\n return diff[:diff.find('.')]","def get_time_string(self):\n return f\"{self.year} {self.month:02} \" \\\n f\"{self.start_day:02} {self.start_hour:02} 00 {self.get_duration():6}\"","def get_timestamp():\n now, s=get_date()\n return (now, \"%s%s%s%s\" % (s, str(now.hour).zfill(2), str(now.minute).zfill(2), str(now.second).zfill(2)))","def pretty_date(time=None):\n now = datetime.now()\n if type(time) is int:\n diff = now - datetime.fromtimestamp(time)\n elif isinstance(time, datetime):\n diff = now - time\n elif not time:\n diff = now - now\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return ''\n\n if day_diff == 0:\n if second_diff < 10:\n return \"刚刚\"\n if second_diff < 60:\n return str(second_diff) + \" 秒前\"\n if second_diff < 120:\n return \"1一分钟前\"\n if second_diff < 3600:\n return str(second_diff / 60) + \" 分钟前\"\n if second_diff < 7200:\n return \"1小时前\"\n if second_diff < 86400:\n return str(second_diff / 3600) + \" 小时前\"\n if day_diff == 1:\n return \"昨天\"\n if day_diff < 7:\n return str(day_diff) + \" 天前\"\n if day_diff < 31:\n return str(day_diff / 7) + \" 周前\"\n if day_diff < 365:\n return str(day_diff / 30) + \" 个月前\"\n return str(day_diff / 365) + \" 年前\"","def time_elapsed(sec):\n if sec < 60:\n return str(sec) + \" sec\"\n elif sec < (60 * 60):\n return str(sec / 60) + \" min\"\n else:\n return str(sec / (60 * 60)) + \" hr\"","def __get_timestamp() -> str:\n return str(datetime.now().astimezone())","def __get_timestamp() -> str:\n return str(datetime.now().astimezone())","def timesince(dt, default=\"just now\"):\n\n now = datetime.datetime.now()\n diff = now - dt\n \n periods = (\n (diff.days / 365, \"year\", \"years\"),\n (diff.days / 30, \"month\", \"months\"),\n (diff.days / 7, \"week\", \"weeks\"),\n (diff.days, \"day\", \"days\"),\n (diff.seconds / 3600, \"hour\", \"hours\"),\n (diff.seconds / 60, \"minute\", \"minutes\"),\n (diff.seconds, \"second\", \"seconds\"),\n )\n\n for period, singular, plural in periods:\n \n if period:\n return \"%d %s ago\" % (period, singular if period == 1 else plural)\n\n return default","def ts(self, which='now'):\n if which == 'now':\n return '%d%02d%02dT%02d%02d%02d' % self.date['now'][0:6]\n else:\n return '%05dT%02d%02d%02d' % (self.date['cc'][0], self.date['cc'][1], self.date['cc'][2], self.date['cc'][3])","def getFormattedText(self):\r\n h = \"00\"\r\n m = \"00\"\r\n s = \"00\"\r\n if(self.seconds < 10):\r\n s = \"0\" + str(self.seconds)\r\n else:\r\n s = str(self.seconds)\r\n\r\n if(self.minutes < 10):\r\n m = \"0\" + str(self.minutes)\r\n else:\r\n m = str(self.minutes)\r\n\r\n if(self.hours < 10):\r\n h = \"0\" + str(self.hours)\r\n else:\r\n h = str(self.hours)\r\n\r\n return h + \":\" + m + \":\" + s","def time_now():\n cur_time = str(datetime.now().strftime(\"%d-%m-%Y %H:%M:%S\"))\n return cur_time","def time():\n return datetime.datetime.now().strftime(\"%Y%m%dT%H%M%SZ\")","def __str__(self):\n return str(self.elapsed) + ' sec'","def get_time(self):\n return \"%02u:%02u:%02u (%d)\" % self.rtc.datetime()[4:8]","def time_str(num):\n if num > 3600:\n return \"%0.2f hrs\" % (num / 3600)\n elif num > 60:\n return \"%0.2f mins\" % (num / 60)\n else:\n return \"%d seconds\" % num","def now():\n now = datetime.datetime.now()\n return \"%04d-%02d-%02d %02d:%02d:%02d.%03d\" % ( now.year, now.month,now.day,\n now.hour,now.minute,now.second,int(now.microsecond/1e3))","def _get_time_since_tell_send(tell):\n tell_time_sent = int(tell[3])\n\n current_time = int(time.time())\n\n dt1 = datetime.fromtimestamp(tell_time_sent)\n dt2 = datetime.fromtimestamp(current_time)\n rd = dateutil.relativedelta.relativedelta(dt2, dt1)\n\n out = ''\n\n if rd.days == 1:\n out += f'{rd.days} day, '\n elif rd.days != 0:\n out += f'{rd.days} days, '\n\n if rd.hours == 1:\n out += f'{rd.hours} hour, '\n elif rd.hours != 0:\n out += f'{rd.hours} hours, '\n\n if rd.minutes == 1:\n out += f'{rd.minutes} minute and '\n elif rd.minutes != 0:\n out += f'{rd.minutes} minutes and '\n\n if rd.seconds == 1:\n out += f'{rd.seconds} second ago'\n elif rd.seconds != 0:\n out += f'{rd.seconds} seconds ago'\n elif current_time - tell_time_sent == 0:\n out = 'just now'\n\n return out","def timestamp_now():\n return datetime.now().strftime(\"%A, %B %d, %Y, %I:%M %p\")","def time_str(self):\n return datetime.now().strftime('%c')","def current_time(cls) -> float:","def get_timestamp():\n return datetime.datetime.now().strftime(\"%Y-%m-%d %H:%M\")","def _get_inner_time(self):\n timestamp = self.last_two_timestamps[0]\n if not timestamp:\n return '0000-00-00 00:00:00'\n return str(timestamp)","def current_time():\n now = datetime.datetime.now()\n time = now.strftime(\"%Y-%m-%d %H:%M:%S:%f\")\n return time","def timestamp():\n my_date_object = datetime.utcnow()\n my_date_string = my_date_object.strftime('%d-%m-%Y %H:%M:%S')\n return my_date_string","def time_stamper() :\n\treturn datetime.now().strftime(\"%Y-%m-%d-%H-%M-%S\")","def _get_timestamp():\n return str(int(time.time()))","def get_now():\r\n now = dt.datetime.now()\r\n now_str = now.strftime(\"%d/%m %H:%M\")\r\n return now_str","def get_time():\n\n time_format = \"%Y-%m-%d %H:%M:%S\"\n now = str(datetime.datetime.now().strftime(time_format))\n\n return now","def getTimeString():\n\tfrom time import strftime\n\treturn strftime(\"%d-%m-%Y__%H-%M-%S\")","def get_now():\n right_now = datetime.datetime.now()\n return (\"%04d%02d%02d-%02d:%02d:%02d\"\n % (right_now.year, right_now.month, right_now.day,\n right_now.hour, right_now.minute, right_now.second))","def get_time_stamp_str() -> str:\n return datetime.datetime.now().strftime(DateFormat)","def format_time(self, created):\n return time.strftime(\n '%Y-%m-%d %H:%M:%S',\n time.localtime(created)\n )","def datetime_timeplotxml(self):\n if self.time:\n return self.date.strftime(\"%b %d %Y\") + \" \" + self.time.strftime(\"%H:%M:%S\") + \" GMT\"\n else:\n return self.date.strftime(\"%b %d %Y\") + \" \" + \"00:00:00\" + \" GMT\"","def get_time_string(time):\r\n mins = time // 60\r\n secs = time % 60\r\n time_string = ''\r\n\r\n if mins < 10:\r\n time_string += ' '\r\n elif mins < 100:\r\n time_string += ' '\r\n\r\n time_string += '%dm ' % mins\r\n\r\n if secs < 10:\r\n time_string += ' '\r\n\r\n time_string += '%ds' % secs\r\n\r\n return time_string","def timeStamp():\n import time\n return str(time.strftime(\"%a %d %b %Y %I:%M:%S %p\"))","def time_hack(self):\n now = datetime.datetime.now()\n monthnames = ['jan', 'feb', 'mar', 'apr', 'may', 'jun',\n 'jul', 'aug', 'sep', 'oct', 'nov', 'dec']\n month = monthnames[now.month - 1].capitalize()\n return ('[%02d/%s/%04d:%02d:%02d:%02d.%06d]' %\n (now.day, month, now.year, now.hour, now.minute, now.second, now.microsecond))","def get_now():\n\treturn datetime.datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")","def adjustedCompareValue(self, value):\n if value.startswith('now'):\n return repr(GenDate())\n return value","def get_current_datetime_string ( ) :\n return get_current_datetime( ).strftime( \"%Y%m%d-%H%M%S\" )","def get_time(self):\n return time.strftime(\"%d/%m/%y %M:%H:%S\", self.time)","def timestamp():\n return datetime.now().strftime(\"%Y%m%dT%H%M%S\")","def timestamp():\n return datetime.now().strftime('%H:%M:%S %m-%d')","def get_timestamp():\n return time.strftime('%Y-%m-%d %H:%M:%S')","def pending_time_descriptive(self):\n return get_time_descriptive(self.pending_time.seconds)","def timestamp():\n tmptz = time.timezone\n sign_str = '+'\n if tmptz > 0:\n sign_str = '-'\n tmptz_hours = int(tmptz / 3600)\n\n return str(\"%s%s%02d:%02d\" % (time.strftime(\"%Y-%m-%dT%H:%M:%S\", time.localtime()), sign_str, abs(tmptz_hours),\n int(tmptz / 60 - tmptz_hours * 60)))","def currentTime():\n return strftime(\"%H:%M:%S\", time.localtime())","def render_date_time_with_relative_into(into, date_time, add_ago):\n into.append(format(date_time, DATETIME_FORMAT_CODE))\n \n into.append(' [*')\n into.append(elapsed_time(date_time))\n if add_ago:\n into.append(' ago')\n into.append('*]')\n \n return into","def human_datetime(date_time):\n current_datetime = datetime.datetime.now()\n delta = str(current_datetime - date_time)\n if delta.find(',') > 0:\n days, hours = delta.split(',')\n days = int(days.split()[0].strip())\n hours, minutes = hours.split(':')[0:2]\n else:\n hours, minutes = delta.split(':')[0:2]\n days = 0\n days, hours, minutes = int(days), int(hours), int(minutes)\n datelets = []\n years, months, xdays = None, None, None\n plural = lambda x: 's' if x != 1 else ''\n if days >= 365:\n years = int(days / 365)\n datelets.append('%d year%s' % (years, plural(years)))\n days = days % 365\n if days >= 30 and days < 365:\n months = int(days / 30)\n datelets.append('%d month%s' % (months, plural(months)))\n days = days % 30\n if not years and days > 0 and days < 30:\n xdays = days\n datelets.append('%d day%s' % (xdays, plural(xdays)))\n if not (months or years) and hours != 0:\n datelets.append('%d hour%s' % (hours, plural(hours)))\n if not (xdays or months or years):\n datelets.append('%d minute%s' % (minutes, plural(minutes)))\n return ', '.join(datelets) + ' ago.'","def timesince_limited(d):\n today = datetime.datetime.now()\n delta = datetime.timedelta\n interval = today - d\n if today.strftime('%Y-%m-%d') == d.strftime('%Y-%m-%d'):\n if interval < delta(days=0, hours=1):\n return timesince(d) + ' ago '\n else:\n return d.strftime('%H:%M')\n else:\n return d","def SAgeDdt(ddt):\n if ddt.days < 0:\n return \"in the future?\"\n months = int(ddt.days*12/365)\n years = int(ddt.days/365)\n if years >= 1:\n return \"%d year%s ago\" % (years, SPlural(years))\n if months >= 3:\n return \"%d months ago\" % months \n if ddt.days == 1:\n return \"yesterday\"\n if ddt.days > 1:\n return \"%d days ago\" % ddt.days\n hrs = int(ddt.seconds/60/60)\n if hrs >= 1:\n return \"%d hour%s ago\" % (hrs, SPlural(hrs))\n minutes = round(ddt.seconds/60)\n if minutes < 1:\n return \"seconds ago\"\n return \"%d minute%s ago\" % (minutes, SPlural(minutes))"],"string":"[\n \"def humanize_ts(timestamp=False):\\n now = datetime.now()\\n diff = now - datetime.fromtimestamp(timestamp)\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n return ''\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return \\\"just now\\\"\\n if second_diff < 60:\\n return str(int(second_diff)) + \\\" seconds ago\\\"\\n if second_diff < 120:\\n return \\\"a minute ago\\\"\\n if second_diff < 3600:\\n return str(int(second_diff / 60)) + \\\" minutes ago\\\"\\n if second_diff < 7200:\\n return \\\"an hour ago\\\"\\n if second_diff < 86400:\\n return str(int(second_diff / 3600)) + \\\" hours ago\\\"\\n if day_diff == 1:\\n return \\\"Yesterday\\\"\\n if day_diff < 7:\\n return str(day_diff) + \\\" days ago\\\"\\n if day_diff < 31:\\n return str(int(day_diff / 7)) + \\\" weeks ago\\\"\\n if day_diff < 365:\\n return str(int(day_diff / 30)) + \\\" months ago\\\"\\n return str(int(day_diff / 365)) + \\\" years ago\\\"\",\n \"def pretty_date(time=False):\\n now = datetime.now()\\n if type(time) is int:\\n diff = now - datetime.fromtimestamp(time)\\n elif isinstance(time, datetime):\\n diff = now - time\\n elif not time:\\n diff = now - now\\n else:\\n diff = now - now\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n return ''\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return \\\"just now\\\"\\n if second_diff < 60:\\n return str(int(round(second_diff, 0))) + \\\" seconds ago\\\"\\n if second_diff < 120:\\n return \\\"a minute ago\\\"\\n if second_diff < 3600:\\n return str(int(round(second_diff / 60, 0))) + \\\" minutes ago\\\"\\n if second_diff < 7200:\\n return \\\"an hour ago\\\"\\n if second_diff < 86400:\\n return str(int(round(second_diff / 3600, 0))) + \\\" hours ago\\\"\\n if day_diff == 1:\\n return \\\"Yesterday\\\"\\n if day_diff < 7:\\n return str(int(round(day_diff, 0))) + \\\" days ago\\\"\\n if day_diff < 31:\\n return str(int(round(day_diff / 7, 0))) + \\\" weeks ago\\\"\\n if day_diff < 365:\\n return str(int(round(day_diff / 30, 0))) + \\\" months ago\\\"\\n return str(int(round(day_diff / 365, 0))) + \\\" years ago\\\"\",\n \"def ago(self):\\n return human(self.timestamp/1000.0, precision=1, abbreviate=True)\",\n \"def time_since(timestamp=None):\\n rstr = \\\"\\\"\\n if not timestamp or not isinstance(timestamp, datetime.datetime):\\n return rstr\\n\\n now = timezone.now()\\n timediff = now - timestamp\\n days = timediff.days\\n weeks = days//7\\n months = days//30\\n minutes = timediff.seconds % 3600 // 60\\n seconds = timediff.seconds % 3600 % 60\\n hours = minutes // 60\\n\\n if days > 365:\\n return \\\"> a year\\\"\\n if months > 0:\\n if months == 1:\\n tstr = \\\"month\\\"\\n else:\\n tstr = \\\"months\\\"\\n rstr = rstr + \\\"%s %s\\\" % (months, tstr)\\n return rstr\\n if weeks > 0:\\n if weeks == 1:\\n tstr = \\\"week\\\"\\n else:\\n tstr = \\\"weeks\\\"\\n rstr = rstr + \\\"%s %s\\\" % (weeks, tstr)\\n return rstr\\n if days > 0:\\n if days == 1:\\n tstr = \\\"day\\\"\\n else:\\n tstr = \\\"days\\\"\\n rstr = rstr + \\\"%s %s\\\" % (days, tstr)\\n return rstr\\n elif hours > 0:\\n if hours == 1:\\n tstr = \\\"hour\\\"\\n else:\\n tstr = \\\"hours\\\"\\n rstr = rstr + \\\"%s %s\\\" % (hours, tstr)\\n return rstr\\n elif minutes > 0:\\n if minutes == 1:\\n tstr = \\\"min\\\"\\n else:\\n tstr = \\\"mins\\\"\\n rstr = rstr + \\\"%s %s\\\" % (minutes, tstr)\\n return rstr\\n elif seconds > 0:\\n if seconds == 1:\\n tstr = \\\"sec\\\"\\n else:\\n tstr = \\\"secs\\\"\\n rstr = rstr + \\\"%s %s\\\" % (seconds, tstr)\\n return rstr\\n else:\\n return \\\"Now\\\"\",\n \"def relativeTime(date):\\n diff = datetime.utcnow() - date\\n\\n if diff.days > 7 or diff.days < 0:\\n return date.ctime()\\n elif diff.days == 1:\\n return '1 day ago'\\n elif diff.days > 1:\\n return '%d days ago' % diff.days\\n elif diff.seconds <= 1:\\n return 'just now'\\n elif diff.seconds < 60:\\n return '%d seconds ago' % diff.seconds\\n elif diff.seconds < (60 * 2):\\n return '1 minute ago'\\n elif diff.seconds < (60 * 60):\\n return '%d minutes ago' % (diff.seconds / 60)\\n elif diff.seconds < (60 * 60 * 2):\\n return '1 hour ago'\\n else:\\n return '%d hours ago' % (diff.seconds / (60 * 60))\",\n \"def time_since_as_text(time=False):\\n now = datetime.now(timezone.utc)\\n if type(time) is int:\\n diff = now - datetime.fromtimestamp(time)\\n elif isinstance(time,datetime):\\n diff = now - time\\n elif not time:\\n diff = now - now\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n return ''\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return \\\"nyss\\\"\\n if second_diff < 60:\\n return str(second_diff) + \\\" sekunder sedan\\\"\\n if second_diff < 120:\\n return \\\"a minute ago\\\"\\n if second_diff < 3600:\\n return str(floor(second_diff / 60)) + \\\" minuter sedan\\\"\\n if second_diff < 7200:\\n return \\\"en timme sedan\\\"\\n if second_diff < 86400:\\n return str(floor(second_diff / 3600)) + \\\" timmar sedan\\\"\\n if day_diff == 1:\\n return \\\"Igår\\\"\\n if day_diff < 7:\\n return str(day_diff) + \\\" dagar sedan\\\"\\n if day_diff < 31:\\n return str(floor(day_diff / 7)) + \\\" veckor sedan\\\"\\n if day_diff < 365:\\n return str(floor(day_diff / 30)) + \\\" månder sedan\\\"\\n return str(day_diff / 365) + \\\" år sedan\\\"\",\n \"def pretty_date(time=False):\\n from datetime import datetime\\n now = datetime.now()\\n if type(time) is int:\\n diff = now - datetime.fromtimestamp(time)\\n elif isinstance(time,datetime):\\n diff = now - time \\n elif not time:\\n diff = now - now\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n return ''\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return \\\"just now\\\"\\n if second_diff < 60:\\n return str(second_diff) + \\\" seconds ago\\\"\\n if second_diff < 120:\\n return \\\"a minute ago\\\"\\n if second_diff < 3600:\\n return str( second_diff / 60 ) + \\\" minutes ago\\\"\\n if second_diff < 7200:\\n return \\\"an hour ago\\\"\\n if second_diff < 86400:\\n return str( second_diff / 3600 ) + \\\" hours ago\\\"\\n if day_diff == 1:\\n return \\\"Yesterday\\\"\\n if day_diff < 7:\\n return str(day_diff) + \\\" days ago\\\"\\n if day_diff < 31:\\n return str(day_diff/7) + \\\" weeks ago\\\"\\n if day_diff < 365:\\n return str(day_diff/30) + \\\" months ago\\\"\\n return str(day_diff/365) + \\\" years ago\\\"\",\n \"def pretty_date(time=False):\\n from datetime import datetime\\n\\n now = datetime.now()\\n if type(time) is int:\\n diff = now - datetime.fromtimestamp(time)\\n elif isinstance(time, datetime):\\n diff = now - time\\n elif not time:\\n diff = now - now\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n return \\\"\\\"\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return \\\"just now\\\"\\n if second_diff < 60:\\n return str(second_diff) + \\\" seconds ago\\\"\\n if second_diff < 120:\\n return \\\"a minute ago\\\"\\n if second_diff < 3600:\\n return str(second_diff / 60) + \\\" minutes ago\\\"\\n if second_diff < 7200:\\n return \\\"an hour ago\\\"\\n if second_diff < 86400:\\n return str(second_diff / 3600) + \\\" hours ago\\\"\\n if day_diff == 1:\\n return \\\"Yesterday\\\"\\n if day_diff < 7:\\n return str(day_diff) + \\\" days ago\\\"\\n if day_diff < 31:\\n return str(day_diff / 7) + \\\" weeks ago\\\"\\n if day_diff < 365:\\n return str(day_diff / 30) + \\\" months ago\\\"\\n return str(day_diff / 365) + \\\" years ago\\\"\",\n \"def pretty_date(time=False):\\r\\n from datetime import datetime\\r\\n import dateutil.parser\\r\\n now = datetime.now()\\r\\n if type(time) is str or type(time) is unicode:\\r\\n time = dateutil.parser.parse(time)\\r\\n if type(time) is int:\\r\\n diff = now - datetime.fromtimestamp(time)\\r\\n elif isinstance(time, datetime):\\r\\n diff = now - time\\r\\n elif not time:\\r\\n diff = now - now\\r\\n second_diff = diff.seconds\\r\\n day_diff = diff.days\\r\\n\\r\\n if day_diff < 0:\\r\\n return ''\\r\\n\\r\\n if day_diff == 0:\\r\\n if second_diff < 10:\\r\\n return \\\"just now\\\"\\r\\n if second_diff < 60:\\r\\n return str(second_diff) + \\\" seconds ago\\\"\\r\\n if second_diff < 120:\\r\\n return \\\"a minute ago\\\"\\r\\n if second_diff < 3600:\\r\\n return ' '.join([str(second_diff / 60), \\\"minutes ago\\\"])\\r\\n if second_diff < 7200:\\r\\n return \\\"an hour ago\\\"\\r\\n if second_diff < 86400:\\r\\n return ' '.join([str(second_diff / 3600), \\\"hours ago\\\"])\\r\\n if day_diff == 1:\\r\\n return \\\"Yesterday\\\"\\r\\n if day_diff < 7:\\r\\n return ' '.join([str(day_diff), \\\"days ago\\\"])\\r\\n if day_diff < 31:\\r\\n return ' '.join([str(day_diff / 7), \\\"weeks ago\\\"])\\r\\n if day_diff < 60:\\r\\n return ' '.join([str(day_diff / 30), \\\"month ago\\\"])\\r\\n if day_diff < 365:\\r\\n return ' '.join([str(day_diff / 30), \\\"months ago\\\"])\\r\\n if day_diff < (365 * 2):\\r\\n return ' '.join([str(day_diff / 365), \\\"year ago\\\"])\\r\\n return ' '.join([str(day_diff / 365), \\\"years ago\\\"])\",\n \"def timeago(time=False):\\n\\n return arrow.get(time).humanize()\",\n \"def relative_datetime(self):\\n now = datetime.now(timezone.utc)\\n created_at = self.created_at.astimezone(timezone.utc)\\n\\n delta = humanize.naturaldelta(abs(created_at - now))\\n tense = \\\"from now\\\" if now < created_at else \\\"ago\\\"\\n\\n return f\\\"{delta} {tense}\\\"\",\n \"def naturaltime(value):\\n try:\\n value = datetime.datetime(value.year, value.month, value.day, value.hour, value.minute, value.second)\\n except AttributeError:\\n return value\\n except ValueError:\\n return value\\n\\n if getattr(value, 'tzinfo', None):\\n now = datetime.datetime.now(LocalTimezone(value))\\n else:\\n now = datetime.datetime.now()\\n now = now - timedelta(0, 0, now.microsecond)\\n if value < now:\\n delta = now - value\\n if delta.days != 0:\\n return pgettext(\\n 'naturaltime', '%(delta)s ago'\\n ) % {'delta': defaultfilters.timesince(value)}\\n elif delta.seconds == 0:\\n return _(u'now')\\n elif delta.seconds < 60:\\n return ungettext(\\n u'a second ago', u'%(count)s seconds ago', delta.seconds\\n ) % {'count': delta.seconds}\\n elif delta.seconds // 60 < 60:\\n count = delta.seconds // 60\\n return ungettext(\\n u'a minute ago', u'%(count)s minutes ago', count\\n ) % {'count': count}\\n else:\\n count = delta.seconds // 60 // 60\\n return ungettext(\\n u'an hour ago', u'%(count)s hours ago', count\\n ) % {'count': count}\\n else:\\n delta = value - now\\n if delta.days != 0:\\n return pgettext(\\n 'naturaltime', '%(delta)s from now'\\n ) % {'delta': defaultfilters.timeuntil(value)}\\n elif delta.seconds == 0:\\n return _(u'now')\\n elif delta.seconds < 60:\\n return ungettext(\\n u'a second from now', u'%(count)s seconds from now', delta.seconds\\n ) % {'count': delta.seconds}\\n elif delta.seconds // 60 < 60:\\n count = delta.seconds // 60\\n return ungettext(\\n u'a minute from now', u'%(count)s minutes from now', count\\n ) % {'count': count}\\n else:\\n count = delta.seconds // 60 // 60\\n return ungettext(\\n u'an hour from now', u'%(count)s hours from now', count\\n ) % {'count': count}\",\n \"def howLongAgo(time=False):\\n now = timezone.now()\\n if type(time) is int:\\n diff = now - datetime.fromtimestamp(time)\\n elif isinstance(time,datetime):\\n diff = now - time\\n elif not time:\\n diff = now - now\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n return ''\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return \\\"genau jetzt\\\"\\n if second_diff < 60:\\n return \\\"vor \\\" + str(second_diff) + \\\" Sek.\\\"\\n if second_diff < 120:\\n return \\\"vor einer Min.\\\"\\n if second_diff < 3600:\\n return \\\"vor \\\" + str( second_diff / 60 ) + \\\" Min.\\\"\\n if second_diff < 7200:\\n return \\\"vor einer St.\\\"\\n if second_diff < 86400:\\n return \\\"vor \\\" + str( second_diff / 3600 ) + \\\" St.\\\"\\n if day_diff == 1:\\n return \\\"Gestern\\\"\\n if day_diff < 7:\\n return \\\"vor \\\" + str(day_diff) + \\\" Tagen\\\"\\n if day_diff < 31:\\n return \\\"vor \\\" + str(day_diff/7) + \\\" Wochen\\\"\\n if day_diff < 365:\\n return \\\"vor \\\" + str(day_diff/30) + \\\" Monaten\\\"\\n return \\\"vor \\\" + str(day_diff/365) + \\\" Jahren\\\"\",\n \"def get_formatted_time() -> datetime.strftime:\\n\\t\\n\\tnow = datetime.now() # time now\\n\\thalf_hour = (now - timedelta(minutes = 30)) # time 30 min ago\\n\\t# returns half hour ago to accommodate for failed checks\\n\\t# (bc twint behaves as if none found if check failed)\\n\\tcurrent_time = half_hour.strftime(\\\"%Y-%m-%d %H:%M:%S\\\")\\n\\treturn current_time\",\n \"def time_now() -> str:\\n return datetime_to_str(datetime_now())\",\n \"def pretty_date(date: datetime):\\n if not isinstance(date, datetime) or date > NOW:\\n raise ValueError('pretty_date() only accepts datetime objects in the past')\\n diff = NOW - date\\n seconds = int(diff.total_seconds())\\n minutes = seconds // 60\\n hours = minutes // 60\\n # This doesn't _feel_ very pythonic…\\n if seconds < 10:\\n return 'just now'\\n if seconds < 60:\\n return f'{seconds} seconds ago'\\n if minutes < 2:\\n return 'a minute ago'\\n if minutes < 60:\\n return f'{minutes} minutes ago'\\n if hours < 2:\\n return 'an hour ago'\\n if hours < 24:\\n return f'{hours} hours ago'\\n if hours < 48:\\n return 'yesterday'\\n return date.strftime('%m/%d/%y')\",\n \"def pretty_date(time=False):\\n now = datetime.datetime.utcnow()\\n if type(time) is int:\\n diff = now - datetime.datetime.fromtimestamp(time)\\n elif isinstance(time, datetime.datetime):\\n diff = now - time\\n elif not time:\\n diff = now - now\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n day_diff *= -1\\n second_diff *= -1\\n if day_diff < 1:\\n if second_diff < 10:\\n return ugettext('imminently')\\n if second_diff < 60:\\n return ungettext('{n} second from now', '{n} seconds from now', second_diff).format(n=second_diff)\\n if second_diff < 120:\\n return ugettext('in a minute')\\n if second_diff < 3600:\\n return ungettext('{n} minute from now', '{n} minutes from now', second_diff / 60).format(n=second_diff / 60)\\n if second_diff < 7200:\\n return ugettext('in an hour')\\n if second_diff < 86400:\\n return ungettext('{n} hour from now', '{n} hours from now', second_diff / 3600).format(n=second_diff / 3600)\\n if day_diff == 1:\\n return ugettext('tomorrow')\\n if day_diff < 7:\\n return ungettext('{n} day from now', '{n} days from now', day_diff).format(n=day_diff)\\n if day_diff < 31:\\n return ungettext('{n} week from now', '{n} weeks from now', day_diff / 7).format(n=day_diff / 7)\\n if day_diff < 365:\\n return ungettext('{n} month from now', '{n} months from now', day_diff / 30).format(n=day_diff / 30)\\n return ungettext('{n} year from now', '{n} years from now', day_diff / 365).format(n=day_diff / 365)\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return ugettext('just now')\\n if second_diff < 60:\\n return ungettext('{n} second ago', '{n} seconds ago', second_diff).format(n=second_diff)\\n if second_diff < 120:\\n return ugettext('a minute ago')\\n if second_diff < 3600:\\n return ungettext('{n} minute ago', '{n} minutes ago', second_diff / 60).format(n=second_diff / 60)\\n if second_diff < 7200:\\n return ugettext('an hour ago')\\n if second_diff < 86400:\\n return ungettext('{n} hour ago', '{n} hours ago', second_diff / 3600).format(n=second_diff / 3600)\\n if day_diff == 1:\\n return ugettext('yesterday')\\n if day_diff < 7:\\n return ungettext('{n} day ago', '{n} days ago', day_diff).format(n=day_diff)\\n if day_diff < 31:\\n return ungettext('{n} week ago', '{n} weeks ago', day_diff / 7).format(n=day_diff / 7)\\n if day_diff < 365:\\n return ungettext('{n} month ago', '{n} months ago', day_diff / 30).format(n=day_diff / 30)\\n return ungettext('{n} year ago', '{n} years ago', day_diff / 365).format(n=day_diff / 365)\",\n \"def get_time(self):\\n return ''\",\n \"async def humanize_time(self, value):\\n if value is None:\\n return \\\"None\\\"\\n return str(datetime.timedelta(seconds=value))\",\n \"def shorttimesince(value, arg=None):\\r\\n from django.utils.timesince import timesince\\r\\n if not value:\\r\\n return u''\\r\\n if arg:\\r\\n return calculate_shorttimesince(arg, value)\\r\\n return calculate_shorttimesince(value)\",\n \"def get_date():\\n return (datetime.now() - TIMEDELTA).isoformat()\",\n \"def formatted_time() -> datetime.datetime:\\r\\n return datetime.datetime.now()\",\n \"def get_current_timestamp_str(self):\\n return str(time.mktime(datetime.datetime.now().timetuple()))\",\n \"def nowStr(time=None):\\n if time is None:\\n time = datetime.now().time()\\n if time.minute < 10:\\n return time.strftime(\\\"%H ноль %m\\\")\\n else:\\n return time.strftime(\\\"%H %M\\\")\",\n \"def human_date(self, date):\\n return timeago.format(date)\",\n \"def str_current_time():\\n return strftime(\\\"%Y_%m_%d_%H_%M_%S_%Z\\\", gmtime())\",\n \"def get_now_time():\\r\\n return '[' + datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f') + ']: '\",\n \"def get_elapsed_timestamp(self) -> str:\\n t = self.elapsed_time\\n minutes = int(t / 60)\\n seconds = int(t - (60 * minutes))\\n millis = int(100 * (t - int(t)))\\n return '{:>02d}:{:>02d}.{:<02d}'.format(minutes, seconds, millis)\",\n \"def time_created(self) -> str:\\n return pulumi.get(self, \\\"time_created\\\")\",\n \"def time_created(self) -> str:\\n return pulumi.get(self, \\\"time_created\\\")\",\n \"def time_created(self) -> str:\\n return pulumi.get(self, \\\"time_created\\\")\",\n \"def time( self, mess, args):\\n return str(datetime.datetime.now())\",\n \"def time( self, mess, args):\\n return str(datetime.datetime.now())\",\n \"def now_short(_format=\\\"%Y%m%d-%H%M%S\\\"):\\n timeString = time.strftime(_format, time.localtime()) + \\\"\\\\t\\\"\\n return timeString\",\n \"def since(self):\\n return str(datetime.datetime.now() - self._refreshed_at)\",\n \"def get_answer_time(self):\\n sec = (self.updated_at - self.created_at).total_seconds()\\n return f'{int((sec / 60) % 60):02d}:{int(sec):02d}'\",\n \"def get_time():\\n ct = time.time()\\n lt = time.gmtime(ct)\\n msec = int((ct - int(ct)) * 1000)\\n return f'{time.strftime(DATE_FMT, lt)}.{msec:0>3}'\",\n \"def now(time):\\n a = datetime.fromtimestamp(time).strftime('%Y-%m-%d %H:%M:%S')\\n return a\",\n \"def now(time):\\n a = datetime.fromtimestamp(time).strftime('%Y-%m-%d %H:%M:%S')\\n return a\",\n \"def create_human_readable_timestamp(self, now):\\n hrdatetime = now.strftime('%c')\\n return hrdatetime\",\n \"def timestr():\\n return dt.strftime(dt.now(),'%H:%M:%S')\",\n \"def adjustedCompareValue(self, value):\\n if value.startswith('now'):\\n return repr(GenTime())\\n return value\",\n \"def age(self) -> str:\\n tdelta = dt.now() - self.created_timestamp\\n if tdelta.days >= 548: # enough to round it up to 2 years\\n return f'about {tdelta.days/365:.0f} years'\\n elif tdelta.days >= 345: # enough to round it up to 1 year (so it doesn't report '12 months')\\n return f'about a year'\\n elif tdelta.days > 45: # beyond 1 month (after rounding)\\n return f'about {tdelta.days/30:.0f} months'\\n elif tdelta.days > 24: # enough to round it up to 1 month (so it doesn't report '4 weeks')\\n return f'about a month'\\n elif tdelta.days > 7:\\n # round to nearest half, dropping '.0' when whole\\n return f'{round((tdelta.days/7)*2)/2:g} weeks'\\n elif tdelta.days == 7:\\n return 'a week'\\n elif tdelta.days > 1:\\n return f'{tdelta.days} days'\\n elif tdelta.days == 1:\\n return f'a day'\\n # break it down into parts of a day\\n hours = tdelta.seconds // 3600\\n if hours > 1:\\n return f'{hours:.0f} hours'\\n elif hours == 1:\\n return f'an hour'\\n minutes = tdelta.seconds % 3600 / 60\\n if minutes > 1:\\n return f'{minutes:.0f} minutes'\\n elif minutes == 1:\\n return f'a minute'\\n return 'moments'\",\n \"def time_since(dt, default=\\\"just now\\\"):\\n\\t\\n\\tnow = datetime.utcnow()\\n\\tdiff = now - dt\\n\\t\\n\\tperiods = (\\n\\t\\t(diff.days / 365, \\\"year\\\", \\\"years\\\"),\\n\\t\\t(diff.days / 30, \\\"month\\\", \\\"months\\\"),\\n\\t\\t(diff.days / 7, \\\"week\\\", \\\"weeks\\\"),\\n\\t\\t(diff.days, \\\"day\\\", \\\"days\\\"),\\n\\t\\t(diff.seconds / 3600, \\\"hour\\\", \\\"hours\\\"),\\n\\t\\t(diff.seconds / 60, \\\"minute\\\", \\\"minutes\\\"),\\n\\t\\t(diff.seconds, \\\"second\\\", \\\"seconds\\\"),\\n\\t)\\n\\n\\tfor period, singular, plural in periods:\\n\\t\\tif period:\\n\\t\\t\\treturn \\\"%d %s ago\\\" % (period, singular if period == 1 else plural)\\n\\n\\treturn default\",\n \"def get_formatted_duration(self, prev_time):\\n duration = time() - prev_time\\n if duration < 60:\\n unit = 's'\\n elif duration < 3600:\\n duration /= 60\\n unit = 'm'\\n else:\\n duration /= 3600\\n unit = 'h'\\n return self.format_num(duration) + unit\",\n \"def now(self):\\n return time.strftime(r'[%d/%b/%Y:%H:%M:%S]')\",\n \"def _time_delta_from_info(info):\\n now = datetime.datetime.now()\\n then = info.start_time\\n return str(now.replace(microsecond=0) - then.replace(microsecond=0))\",\n \"def __str__(self):\\n return \\\"({0}:{1}:{2})\\\".format(self.hours, self.minutes, self.seconds)\",\n \"def now_short(_format=\\\"%Y%m%d-%H%M%S\\\"):\\n return time.strftime(_format, time.localtime()) + \\\"\\\\t\\\"\",\n \"def _time_str(self):\\n try:\\n if not self._time:\\n raise ValueError\\n format_ = '%a, %d %b %Y %H:%M:%S'\\n return datetime.fromtimestamp(float(self._time)).strftime(format_)\\n except ValueError:\\n return plastic_date()\",\n \"def _getUpTime(self):\\n diff = (datetime.datetime.now() - self._startTime).__str__()\\n return diff[:diff.find('.')]\",\n \"def get_time_string(self):\\n return f\\\"{self.year} {self.month:02} \\\" \\\\\\n f\\\"{self.start_day:02} {self.start_hour:02} 00 {self.get_duration():6}\\\"\",\n \"def get_timestamp():\\n now, s=get_date()\\n return (now, \\\"%s%s%s%s\\\" % (s, str(now.hour).zfill(2), str(now.minute).zfill(2), str(now.second).zfill(2)))\",\n \"def pretty_date(time=None):\\n now = datetime.now()\\n if type(time) is int:\\n diff = now - datetime.fromtimestamp(time)\\n elif isinstance(time, datetime):\\n diff = now - time\\n elif not time:\\n diff = now - now\\n second_diff = diff.seconds\\n day_diff = diff.days\\n\\n if day_diff < 0:\\n return ''\\n\\n if day_diff == 0:\\n if second_diff < 10:\\n return \\\"刚刚\\\"\\n if second_diff < 60:\\n return str(second_diff) + \\\" 秒前\\\"\\n if second_diff < 120:\\n return \\\"1一分钟前\\\"\\n if second_diff < 3600:\\n return str(second_diff / 60) + \\\" 分钟前\\\"\\n if second_diff < 7200:\\n return \\\"1小时前\\\"\\n if second_diff < 86400:\\n return str(second_diff / 3600) + \\\" 小时前\\\"\\n if day_diff == 1:\\n return \\\"昨天\\\"\\n if day_diff < 7:\\n return str(day_diff) + \\\" 天前\\\"\\n if day_diff < 31:\\n return str(day_diff / 7) + \\\" 周前\\\"\\n if day_diff < 365:\\n return str(day_diff / 30) + \\\" 个月前\\\"\\n return str(day_diff / 365) + \\\" 年前\\\"\",\n \"def time_elapsed(sec):\\n if sec < 60:\\n return str(sec) + \\\" sec\\\"\\n elif sec < (60 * 60):\\n return str(sec / 60) + \\\" min\\\"\\n else:\\n return str(sec / (60 * 60)) + \\\" hr\\\"\",\n \"def __get_timestamp() -> str:\\n return str(datetime.now().astimezone())\",\n \"def __get_timestamp() -> str:\\n return str(datetime.now().astimezone())\",\n \"def timesince(dt, default=\\\"just now\\\"):\\n\\n now = datetime.datetime.now()\\n diff = now - dt\\n \\n periods = (\\n (diff.days / 365, \\\"year\\\", \\\"years\\\"),\\n (diff.days / 30, \\\"month\\\", \\\"months\\\"),\\n (diff.days / 7, \\\"week\\\", \\\"weeks\\\"),\\n (diff.days, \\\"day\\\", \\\"days\\\"),\\n (diff.seconds / 3600, \\\"hour\\\", \\\"hours\\\"),\\n (diff.seconds / 60, \\\"minute\\\", \\\"minutes\\\"),\\n (diff.seconds, \\\"second\\\", \\\"seconds\\\"),\\n )\\n\\n for period, singular, plural in periods:\\n \\n if period:\\n return \\\"%d %s ago\\\" % (period, singular if period == 1 else plural)\\n\\n return default\",\n \"def ts(self, which='now'):\\n if which == 'now':\\n return '%d%02d%02dT%02d%02d%02d' % self.date['now'][0:6]\\n else:\\n return '%05dT%02d%02d%02d' % (self.date['cc'][0], self.date['cc'][1], self.date['cc'][2], self.date['cc'][3])\",\n \"def getFormattedText(self):\\r\\n h = \\\"00\\\"\\r\\n m = \\\"00\\\"\\r\\n s = \\\"00\\\"\\r\\n if(self.seconds < 10):\\r\\n s = \\\"0\\\" + str(self.seconds)\\r\\n else:\\r\\n s = str(self.seconds)\\r\\n\\r\\n if(self.minutes < 10):\\r\\n m = \\\"0\\\" + str(self.minutes)\\r\\n else:\\r\\n m = str(self.minutes)\\r\\n\\r\\n if(self.hours < 10):\\r\\n h = \\\"0\\\" + str(self.hours)\\r\\n else:\\r\\n h = str(self.hours)\\r\\n\\r\\n return h + \\\":\\\" + m + \\\":\\\" + s\",\n \"def time_now():\\n cur_time = str(datetime.now().strftime(\\\"%d-%m-%Y %H:%M:%S\\\"))\\n return cur_time\",\n \"def time():\\n return datetime.datetime.now().strftime(\\\"%Y%m%dT%H%M%SZ\\\")\",\n \"def __str__(self):\\n return str(self.elapsed) + ' sec'\",\n \"def get_time(self):\\n return \\\"%02u:%02u:%02u (%d)\\\" % self.rtc.datetime()[4:8]\",\n \"def time_str(num):\\n if num > 3600:\\n return \\\"%0.2f hrs\\\" % (num / 3600)\\n elif num > 60:\\n return \\\"%0.2f mins\\\" % (num / 60)\\n else:\\n return \\\"%d seconds\\\" % num\",\n \"def now():\\n now = datetime.datetime.now()\\n return \\\"%04d-%02d-%02d %02d:%02d:%02d.%03d\\\" % ( now.year, now.month,now.day,\\n now.hour,now.minute,now.second,int(now.microsecond/1e3))\",\n \"def _get_time_since_tell_send(tell):\\n tell_time_sent = int(tell[3])\\n\\n current_time = int(time.time())\\n\\n dt1 = datetime.fromtimestamp(tell_time_sent)\\n dt2 = datetime.fromtimestamp(current_time)\\n rd = dateutil.relativedelta.relativedelta(dt2, dt1)\\n\\n out = ''\\n\\n if rd.days == 1:\\n out += f'{rd.days} day, '\\n elif rd.days != 0:\\n out += f'{rd.days} days, '\\n\\n if rd.hours == 1:\\n out += f'{rd.hours} hour, '\\n elif rd.hours != 0:\\n out += f'{rd.hours} hours, '\\n\\n if rd.minutes == 1:\\n out += f'{rd.minutes} minute and '\\n elif rd.minutes != 0:\\n out += f'{rd.minutes} minutes and '\\n\\n if rd.seconds == 1:\\n out += f'{rd.seconds} second ago'\\n elif rd.seconds != 0:\\n out += f'{rd.seconds} seconds ago'\\n elif current_time - tell_time_sent == 0:\\n out = 'just now'\\n\\n return out\",\n \"def timestamp_now():\\n return datetime.now().strftime(\\\"%A, %B %d, %Y, %I:%M %p\\\")\",\n \"def time_str(self):\\n return datetime.now().strftime('%c')\",\n \"def current_time(cls) -> float:\",\n \"def get_timestamp():\\n return datetime.datetime.now().strftime(\\\"%Y-%m-%d %H:%M\\\")\",\n \"def _get_inner_time(self):\\n timestamp = self.last_two_timestamps[0]\\n if not timestamp:\\n return '0000-00-00 00:00:00'\\n return str(timestamp)\",\n \"def current_time():\\n now = datetime.datetime.now()\\n time = now.strftime(\\\"%Y-%m-%d %H:%M:%S:%f\\\")\\n return time\",\n \"def timestamp():\\n my_date_object = datetime.utcnow()\\n my_date_string = my_date_object.strftime('%d-%m-%Y %H:%M:%S')\\n return my_date_string\",\n \"def time_stamper() :\\n\\treturn datetime.now().strftime(\\\"%Y-%m-%d-%H-%M-%S\\\")\",\n \"def _get_timestamp():\\n return str(int(time.time()))\",\n \"def get_now():\\r\\n now = dt.datetime.now()\\r\\n now_str = now.strftime(\\\"%d/%m %H:%M\\\")\\r\\n return now_str\",\n \"def get_time():\\n\\n time_format = \\\"%Y-%m-%d %H:%M:%S\\\"\\n now = str(datetime.datetime.now().strftime(time_format))\\n\\n return now\",\n \"def getTimeString():\\n\\tfrom time import strftime\\n\\treturn strftime(\\\"%d-%m-%Y__%H-%M-%S\\\")\",\n \"def get_now():\\n right_now = datetime.datetime.now()\\n return (\\\"%04d%02d%02d-%02d:%02d:%02d\\\"\\n % (right_now.year, right_now.month, right_now.day,\\n right_now.hour, right_now.minute, right_now.second))\",\n \"def get_time_stamp_str() -> str:\\n return datetime.datetime.now().strftime(DateFormat)\",\n \"def format_time(self, created):\\n return time.strftime(\\n '%Y-%m-%d %H:%M:%S',\\n time.localtime(created)\\n )\",\n \"def datetime_timeplotxml(self):\\n if self.time:\\n return self.date.strftime(\\\"%b %d %Y\\\") + \\\" \\\" + self.time.strftime(\\\"%H:%M:%S\\\") + \\\" GMT\\\"\\n else:\\n return self.date.strftime(\\\"%b %d %Y\\\") + \\\" \\\" + \\\"00:00:00\\\" + \\\" GMT\\\"\",\n \"def get_time_string(time):\\r\\n mins = time // 60\\r\\n secs = time % 60\\r\\n time_string = ''\\r\\n\\r\\n if mins < 10:\\r\\n time_string += ' '\\r\\n elif mins < 100:\\r\\n time_string += ' '\\r\\n\\r\\n time_string += '%dm ' % mins\\r\\n\\r\\n if secs < 10:\\r\\n time_string += ' '\\r\\n\\r\\n time_string += '%ds' % secs\\r\\n\\r\\n return time_string\",\n \"def timeStamp():\\n import time\\n return str(time.strftime(\\\"%a %d %b %Y %I:%M:%S %p\\\"))\",\n \"def time_hack(self):\\n now = datetime.datetime.now()\\n monthnames = ['jan', 'feb', 'mar', 'apr', 'may', 'jun',\\n 'jul', 'aug', 'sep', 'oct', 'nov', 'dec']\\n month = monthnames[now.month - 1].capitalize()\\n return ('[%02d/%s/%04d:%02d:%02d:%02d.%06d]' %\\n (now.day, month, now.year, now.hour, now.minute, now.second, now.microsecond))\",\n \"def get_now():\\n\\treturn datetime.datetime.now().strftime(\\\"%Y-%m-%d %H:%M:%S\\\")\",\n \"def adjustedCompareValue(self, value):\\n if value.startswith('now'):\\n return repr(GenDate())\\n return value\",\n \"def get_current_datetime_string ( ) :\\n return get_current_datetime( ).strftime( \\\"%Y%m%d-%H%M%S\\\" )\",\n \"def get_time(self):\\n return time.strftime(\\\"%d/%m/%y %M:%H:%S\\\", self.time)\",\n \"def timestamp():\\n return datetime.now().strftime(\\\"%Y%m%dT%H%M%S\\\")\",\n \"def timestamp():\\n return datetime.now().strftime('%H:%M:%S %m-%d')\",\n \"def get_timestamp():\\n return time.strftime('%Y-%m-%d %H:%M:%S')\",\n \"def pending_time_descriptive(self):\\n return get_time_descriptive(self.pending_time.seconds)\",\n \"def timestamp():\\n tmptz = time.timezone\\n sign_str = '+'\\n if tmptz > 0:\\n sign_str = '-'\\n tmptz_hours = int(tmptz / 3600)\\n\\n return str(\\\"%s%s%02d:%02d\\\" % (time.strftime(\\\"%Y-%m-%dT%H:%M:%S\\\", time.localtime()), sign_str, abs(tmptz_hours),\\n int(tmptz / 60 - tmptz_hours * 60)))\",\n \"def currentTime():\\n return strftime(\\\"%H:%M:%S\\\", time.localtime())\",\n \"def render_date_time_with_relative_into(into, date_time, add_ago):\\n into.append(format(date_time, DATETIME_FORMAT_CODE))\\n \\n into.append(' [*')\\n into.append(elapsed_time(date_time))\\n if add_ago:\\n into.append(' ago')\\n into.append('*]')\\n \\n return into\",\n \"def human_datetime(date_time):\\n current_datetime = datetime.datetime.now()\\n delta = str(current_datetime - date_time)\\n if delta.find(',') > 0:\\n days, hours = delta.split(',')\\n days = int(days.split()[0].strip())\\n hours, minutes = hours.split(':')[0:2]\\n else:\\n hours, minutes = delta.split(':')[0:2]\\n days = 0\\n days, hours, minutes = int(days), int(hours), int(minutes)\\n datelets = []\\n years, months, xdays = None, None, None\\n plural = lambda x: 's' if x != 1 else ''\\n if days >= 365:\\n years = int(days / 365)\\n datelets.append('%d year%s' % (years, plural(years)))\\n days = days % 365\\n if days >= 30 and days < 365:\\n months = int(days / 30)\\n datelets.append('%d month%s' % (months, plural(months)))\\n days = days % 30\\n if not years and days > 0 and days < 30:\\n xdays = days\\n datelets.append('%d day%s' % (xdays, plural(xdays)))\\n if not (months or years) and hours != 0:\\n datelets.append('%d hour%s' % (hours, plural(hours)))\\n if not (xdays or months or years):\\n datelets.append('%d minute%s' % (minutes, plural(minutes)))\\n return ', '.join(datelets) + ' ago.'\",\n \"def timesince_limited(d):\\n today = datetime.datetime.now()\\n delta = datetime.timedelta\\n interval = today - d\\n if today.strftime('%Y-%m-%d') == d.strftime('%Y-%m-%d'):\\n if interval < delta(days=0, hours=1):\\n return timesince(d) + ' ago '\\n else:\\n return d.strftime('%H:%M')\\n else:\\n return d\",\n \"def SAgeDdt(ddt):\\n if ddt.days < 0:\\n return \\\"in the future?\\\"\\n months = int(ddt.days*12/365)\\n years = int(ddt.days/365)\\n if years >= 1:\\n return \\\"%d year%s ago\\\" % (years, SPlural(years))\\n if months >= 3:\\n return \\\"%d months ago\\\" % months \\n if ddt.days == 1:\\n return \\\"yesterday\\\"\\n if ddt.days > 1:\\n return \\\"%d days ago\\\" % ddt.days\\n hrs = int(ddt.seconds/60/60)\\n if hrs >= 1:\\n return \\\"%d hour%s ago\\\" % (hrs, SPlural(hrs))\\n minutes = round(ddt.seconds/60)\\n if minutes < 1:\\n return \\\"seconds ago\\\"\\n return \\\"%d minute%s ago\\\" % (minutes, SPlural(minutes))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7112443","0.70603174","0.6994772","0.6923336","0.69147646","0.689994","0.68880904","0.68262726","0.6814668","0.6745085","0.67083603","0.6695963","0.66525495","0.6583381","0.6518557","0.65105355","0.6455629","0.63705647","0.62662446","0.6263275","0.625927","0.6259118","0.62478876","0.6245946","0.6245096","0.6238159","0.6220305","0.6217721","0.62121916","0.62121916","0.62121916","0.6211421","0.6211421","0.62045765","0.6173178","0.6170328","0.61701286","0.61687005","0.61687005","0.61621976","0.6161123","0.6160084","0.61595446","0.61437213","0.61397415","0.6136463","0.6123348","0.61174184","0.6113688","0.61133593","0.6101396","0.6098509","0.60966706","0.6095897","0.6092564","0.6090794","0.6090794","0.6086942","0.60807735","0.60782504","0.6073077","0.6054249","0.6049769","0.6042392","0.6037919","0.60333496","0.6026184","0.6024505","0.6022521","0.6010516","0.60090345","0.60078967","0.6006256","0.60046566","0.59818894","0.59792125","0.5977696","0.59538424","0.595124","0.5946832","0.5943667","0.59374386","0.59322894","0.59168607","0.59125215","0.5912224","0.59083045","0.59076345","0.590649","0.59053975","0.59019303","0.5898147","0.58885205","0.5880376","0.58761483","0.58718795","0.58677995","0.5866482","0.586327","0.5855926"],"string":"[\n \"0.7112443\",\n \"0.70603174\",\n \"0.6994772\",\n \"0.6923336\",\n \"0.69147646\",\n \"0.689994\",\n \"0.68880904\",\n \"0.68262726\",\n \"0.6814668\",\n \"0.6745085\",\n \"0.67083603\",\n \"0.6695963\",\n \"0.66525495\",\n \"0.6583381\",\n \"0.6518557\",\n \"0.65105355\",\n \"0.6455629\",\n \"0.63705647\",\n \"0.62662446\",\n \"0.6263275\",\n \"0.625927\",\n \"0.6259118\",\n \"0.62478876\",\n \"0.6245946\",\n \"0.6245096\",\n \"0.6238159\",\n \"0.6220305\",\n \"0.6217721\",\n \"0.62121916\",\n \"0.62121916\",\n \"0.62121916\",\n \"0.6211421\",\n \"0.6211421\",\n \"0.62045765\",\n \"0.6173178\",\n \"0.6170328\",\n \"0.61701286\",\n \"0.61687005\",\n \"0.61687005\",\n \"0.61621976\",\n \"0.6161123\",\n \"0.6160084\",\n \"0.61595446\",\n \"0.61437213\",\n \"0.61397415\",\n \"0.6136463\",\n \"0.6123348\",\n \"0.61174184\",\n \"0.6113688\",\n \"0.61133593\",\n \"0.6101396\",\n \"0.6098509\",\n \"0.60966706\",\n \"0.6095897\",\n \"0.6092564\",\n \"0.6090794\",\n \"0.6090794\",\n \"0.6086942\",\n \"0.60807735\",\n \"0.60782504\",\n \"0.6073077\",\n \"0.6054249\",\n \"0.6049769\",\n \"0.6042392\",\n \"0.6037919\",\n \"0.60333496\",\n \"0.6026184\",\n \"0.6024505\",\n \"0.6022521\",\n \"0.6010516\",\n \"0.60090345\",\n \"0.60078967\",\n \"0.6006256\",\n \"0.60046566\",\n \"0.59818894\",\n \"0.59792125\",\n \"0.5977696\",\n \"0.59538424\",\n \"0.595124\",\n \"0.5946832\",\n \"0.5943667\",\n \"0.59374386\",\n \"0.59322894\",\n \"0.59168607\",\n \"0.59125215\",\n \"0.5912224\",\n \"0.59083045\",\n \"0.59076345\",\n \"0.590649\",\n \"0.59053975\",\n \"0.59019303\",\n \"0.5898147\",\n \"0.58885205\",\n \"0.5880376\",\n \"0.58761483\",\n \"0.58718795\",\n \"0.58677995\",\n \"0.5866482\",\n \"0.586327\",\n \"0.5855926\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.64102644"},"document_rank":{"kind":"string","value":"17"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":13,"numItemsPerPage":100,"numTotalItems":95772,"offset":1300,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3Njk2ODQ4NCwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3NzY5NzIwODQsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.BJ-hXGgeTR34WLoOCs8j0A5qg1OFpRJz4-BuuZGZMCrnURWjzmtet_6TgNuU9MTBNNHoDd5S8_3fVOzFoMg7DQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Initialize this game state and set the current player based on is_p1_turn. | def __init__(self, is_p1_turn: bool, side_length: int) -> None:
super().__init__(is_p1_turn)
self.side_length = side_length
# ISSUE: what if node is more than 26 --> no need to handle side more than 5
# construct a list of uppercase and lower case letters
alph_lst_upper = list(st... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_first_player(self):\n if self.player2.won_previous:\n self.current_player = self.player2\n else: self.current_player = self.player1",
"def __init__(self, is_p1_turn, current_total):\n self.p1_turn = is_p1_turn\n self.current_total = current_total",
"def init_turn(... | [
"0.69196415",
"0.69193554",
"0.65942466",
"0.65815157",
"0.65624744",
"0.6533628",
"0.6411285",
"0.6408902",
"0.63886917",
"0.63440305",
"0.62498075",
"0.6223506",
"0.6214494",
"0.6212468",
"0.6181791",
"0.61318034",
"0.61269957",
"0.6113165",
"0.6105516",
"0.60997057",
"0.60... | 0.0 | -1 |
Return a string representation of the current state of the game. | def __str__(self) -> str:
side = self.side_length
hori_lst = self.hori_lst
hori_result = self.hori_result
left_lst = self.left_lst
left_result = self.left_result
right_lst = self.right_lst
right_result = self.right_result
total_line=''
for i in r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def stateString(self):\n return self._mdp.stateString(self._cur_state);",
"def __str__(self):\n s=\"\"\n for y in range(0,HEIGHT):\n for x in range(0,WIDTH):\n s+=str(self.gameState[x,y])\n return s",
"def __str__(self):\n s = \"\"\n for r in ... | [
"0.83233804",
"0.81567377",
"0.8026721",
"0.7843948",
"0.78436744",
"0.7827769",
"0.775942",
"0.77437556",
"0.76473355",
"0.7591848",
"0.7476206",
"0.7409211",
"0.7405296",
"0.7345735",
"0.7345735",
"0.7345735",
"0.7345735",
"0.7345735",
"0.7345735",
"0.7345735",
"0.7345735",... | 0.0 | -1 |
Return all possible moves that can be applied to this state. | def get_possible_moves(self) -> list:
result = []
for lst in self.hori_lst:
for item in lst:
if item.isalpha():
result.append(item)
# add nodes to result if it's not taken and its line is not taken
# for i in range(len(self.hori_lst)):
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def possible_moves(self):\n states = []\n possible_floors = self.possible_floors()\n possible_items = self.possible_items()\n\n for fl in possible_floors:\n for items in possible_items:\n new_floors = deepcopy(self.floors)\n for item in items:\n ... | [
"0.7898512",
"0.7898361",
"0.7858664",
"0.7847656",
"0.77333015",
"0.7536234",
"0.7532586",
"0.7498494",
"0.7485024",
"0.73975164",
"0.7325457",
"0.7318799",
"0.7273196",
"0.717939",
"0.71593887",
"0.7139039",
"0.71370745",
"0.7127056",
"0.71068263",
"0.70893526",
"0.70703286... | 0.6583351 | 68 |
Return 'p1' if the current player is Player 1, and 'p2' if the current player is Player 2. | def get_current_player_name(self) -> str:
if self.p1_turn:
return 'p1'
return 'p2' | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def other_player(cls, player):\n return 0 if player == 1 else 1",
"def checkval(self, P1, P2, winningval):\n if P1 == winningval:\n return \"Player 1\"\n elif P2 == winningval:\n return \"Player 2\"",
"def get_current_player(player_one_turn):\n \n # Get appropri... | [
"0.7322427",
"0.719487",
"0.71915984",
"0.71570975",
"0.7128614",
"0.7037134",
"0.7009901",
"0.69278514",
"0.6833396",
"0.6795355",
"0.6771366",
"0.6737287",
"0.64921343",
"0.6477016",
"0.63291126",
"0.63171285",
"0.62973",
"0.62973",
"0.62973",
"0.62903047",
"0.6243002",
"... | 0.73625857 | 0 |
Return the GameState that results from applying move to this GameState. | def make_move(self, move: Any) -> 'StonehengeState':
if type(move) == str:
new_state = StonehengeState(not self.p1_turn, self.side_length)
# copy the board information from current state
# make copy of current state information
hori_lst_copy = []
for l... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_move(self, game_state: BotGameState) -> BotMove:\n return",
"def result(self, board_state, move):\n # Create a copy of the current board state\n output_state = BoardState(other_state=board_state)\n # Swap pieces\n output_state.move_piece(move)\n # Eliminate piece... | [
"0.7312155",
"0.72799444",
"0.7227082",
"0.71650064",
"0.7120976",
"0.6810444",
"0.67236984",
"0.66773134",
"0.66662157",
"0.66595423",
"0.6642064",
"0.6626734",
"0.65865046",
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"0.65685004",
"0.65537447",
"0.6546836",
"0.65373135",
"0.653719",
"0.6526493",
"0.652... | 0.0 | -1 |
Return whether move is a valid move for this GameState. | def is_valid_move(self, move: Any) -> bool:
return move in self.get_possible_moves() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_valid_move(self, move):\n if self.game_state[move[0]][move[1]] is not None:\n return False\n return True",
"def valid_bool(self):\n return bool(self.piece.validate_move(self.board, self))",
"def is_valid_move(self, move):\n if type(move) == str:\n move... | [
"0.8282215",
"0.8074329",
"0.80526775",
"0.7981014",
"0.78986144",
"0.78754056",
"0.7871537",
"0.78681695",
"0.7756859",
"0.7713244",
"0.7703341",
"0.76398927",
"0.7610206",
"0.75776756",
"0.75525403",
"0.75510347",
"0.7432144",
"0.73722756",
"0.7332168",
"0.72985274",
"0.727... | 0.8471639 | 0 |
Return a representation of this state (which can be used for equality testing). | def __repr__(self) -> Any:
game_board = self.__str__() + "\n"
current_player_info = "Is p1 the current player? " + str(self.p1_turn)
result = game_board + current_player_info
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def state(self):\n return str(self)",
"def state(self):\r\n return str(self)",
"def state(self):\n\n\t\treturn str(self)",
"def __repr__( self ):\n\n return self.__class__.__name__ + \"( \" + repr(self.state) + \")\";",
"def __repr__(self):\r\n r = str(self.current_instance_state())... | [
"0.81590044",
"0.8067545",
"0.7992787",
"0.76251036",
"0.75809264",
"0.7424345",
"0.7290553",
"0.7284625",
"0.7240699",
"0.7135407",
"0.7102532",
"0.70908487",
"0.7075042",
"0.7063691",
"0.7046428",
"0.7046428",
"0.7046428",
"0.7046428",
"0.7046428",
"0.6999811",
"0.6971935",... | 0.0 | -1 |
Return an estimate in interval [LOSE, WIN] of best outcome the current player can guarantee from state self. | def rough_outcome(self) -> float:
# HUYNH YOU PRICK WHY THE FUCK DO YOU MAKE US WRITE THIS SHIT EVEN IT'S NOT USED ANYWHERE
# pick move based on this may not be optimal but better than random
# return 1 if win immediately
# return -1 if all states reachable will result the other player w... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rough_outcome(self) -> float:\n if is_win(self):\n return 1\n elif is_lose(self):\n return -1\n return 0",
"def rough_outcome_strategy(game: Any) -> Any:\n current_state = game.current_state\n best_move = None\n best_outcome = -2 # Temporarily -- just so w... | [
"0.7338502",
"0.7059583",
"0.7059583",
"0.7059583",
"0.7020939",
"0.6829376",
"0.6702647",
"0.6694379",
"0.66560304",
"0.6624065",
"0.6616302",
"0.6588654",
"0.6566183",
"0.6555869",
"0.6547012",
"0.6531186",
"0.6518109",
"0.6501664",
"0.6488798",
"0.6458663",
"0.6427033",
... | 0.73625016 | 0 |
Initialize this Game, using p1_starts to find who the first player is. | def __init__(self, p1_starts: bool) -> None:
side_length = int(input("Enter the side length of the board: "))
self.current_state = StonehengeState(p1_starts, side_length) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def start(self):\n self.__init__()\n self.set_n_players()\n self.init_players()\n self.init_territory_selection_phase()\n self.init_troop_deployment_phase()\n # self.game_phase()",
"def initGame(self):\n self.map = {}\n self.blocks = Group()\n self.C... | [
"0.6787327",
"0.64845306",
"0.64357686",
"0.6349507",
"0.62722546",
"0.626561",
"0.6244119",
"0.61926365",
"0.61749655",
"0.61128175",
"0.6096133",
"0.6081823",
"0.606986",
"0.6065711",
"0.6050611",
"0.5989051",
"0.59888893",
"0.59368724",
"0.592886",
"0.5927789",
"0.59158814... | 0.5549503 | 75 |
Return the instructions for this Game. | def get_instructions(self) -> str:
instruction = "Duck need to fill this blank _____, which I have no idea what it is #$%^&*"
return instruction | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_instructions(self) -> str:\n instructions = \"Players take turns to occupy available positions \" \\\n \"on the \" \\\n \"board. Once half or more of a ley-line has been \" \\\n \"occupied\" \\\n \"one player, th... | [
"0.77113837",
"0.7536874",
"0.74031675",
"0.6759023",
"0.6670727",
"0.6315557",
"0.5983526",
"0.5832342",
"0.5808417",
"0.57887095",
"0.5746708",
"0.5729109",
"0.56965",
"0.5680344",
"0.5596628",
"0.55811346",
"0.55728334",
"0.5472555",
"0.5458725",
"0.54577094",
"0.5449291",... | 0.66112 | 5 |
Return whether or not this game is over at state. | def is_over(self, state: StonehengeState) -> bool:
total_result = state.hori_result + state.left_result + state.right_result
total_line = len(total_result)
p1_taken = 0
p2_taken = 0
# all_taken = True
for item in total_result:
if item == '1':
p... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def game_over(self) -> bool:\n return self.rstate.game_over()",
"def is_over(self):\n return self.game.is_over()",
"def is_game_over(self) -> bool:\n return self._is_game_over",
"def game_over(self):\n # TODO: Define the game over condition for Adventure.\n # use self.over ... | [
"0.8707897",
"0.8566029",
"0.8421653",
"0.8119031",
"0.8112403",
"0.81087774",
"0.80789787",
"0.79621136",
"0.7939655",
"0.78865045",
"0.7864895",
"0.7863609",
"0.784667",
"0.7836293",
"0.78253675",
"0.7812383",
"0.76985806",
"0.7698057",
"0.7644452",
"0.76256573",
"0.7624914... | 0.67353415 | 64 |
Return whether player has won the game. | def is_winner(self, player: str) -> bool:
total_result = self.current_state.hori_result + self.current_state.left_result + self.current_state.right_result
total_line = len(total_result)
p1_taken = 0
p2_taken = 0
for item in total_result:
if item == '1':
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_game_won(self):\n return True",
"def has_won(board, player):\r\n return False",
"def has_won(board, player):\n return False",
"def player_has_won(self):\n return len(self._words_guessed) == self._num_words",
"def is_game_won(self):\n if self.game_is_tied():\n re... | [
"0.8601931",
"0.8356279",
"0.83288485",
"0.81141126",
"0.80790204",
"0.78687596",
"0.78639466",
"0.7839697",
"0.7838136",
"0.76941895",
"0.7626411",
"0.75731826",
"0.754925",
"0.74468017",
"0.74358803",
"0.74049085",
"0.7379903",
"0.7379802",
"0.7361152",
"0.7361038",
"0.7336... | 0.69783485 | 42 |
Return the move that string represents. If string is not a move, return some invalid move. | def str_to_move(self, str1: str) -> Any:
if not str1.strip().isalpha():
return -1
return str1.strip() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def str_to_move(self, string):\n if not string.strip().isalpha():\n return -1\n return string.strip()",
"def str_to_move(self, string):\n if not string.strip().isdigit():\n return -1\n\n return int(string.strip())",
"def get_move() -> str:\n msg = 'Enter a m... | [
"0.7124746",
"0.7086057",
"0.6942887",
"0.6783822",
"0.65344757",
"0.6471586",
"0.64489573",
"0.6421416",
"0.63550556",
"0.62944734",
"0.6270465",
"0.6264515",
"0.6182051",
"0.60790235",
"0.60481",
"0.60470694",
"0.60350966",
"0.601529",
"0.5998565",
"0.5966165",
"0.59147376"... | 0.65770066 | 4 |
Test that the transform function works for binary data | def test_CredL2_1b1_transform_smoketest_transformer_stack_binary(self):
np.random.seed(2525)
Xdata = np.random.choice(np.array(['A', 'B', 'C', 'D']), size=(100, 5),
p=[0.5, 0.3, 0.1, 0.1])
orig_columns = ['ColA', 'ColB', 'ColC', 'ColD', 'ColE']
Xdf = pd.DataFrame(Xdata, c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_transform(self):\n t = OneHotEncode(3)\n assert numpy.all(t.transform(0) == numpy.array((1.0, 0.0, 0.0)))\n assert numpy.all(t.transform(1) == numpy.array((0.0, 1.0, 0.0)))\n assert numpy.all(t.transform(2) == numpy.array((0.0, 0.0, 1.0)))\n with pytest.raises(AssertionE... | [
"0.68057483",
"0.65271544",
"0.64854556",
"0.6451207",
"0.637159",
"0.6202632",
"0.6188656",
"0.6060267",
"0.60558635",
"0.60416764",
"0.60387063",
"0.60317004",
"0.6017776",
"0.59574693",
"0.59446365",
"0.59305394",
"0.590178",
"0.5877073",
"0.5847465",
"0.5844245",
"0.58187... | 0.0 | -1 |
Test that the tranform functions functions for regression data | def test_CredL2_1b1_smoketest_transformer_stack_regression(self):
np.random.seed(2525)
Xdata = np.random.choice(np.array(['A', 'B', 'C', 'D']), size=(100, 5),
p=[0.5, 0.3, 0.1, 0.1])
orig_columns = ['ColA', 'ColB', 'ColC', 'ColD', 'ColE']
Xdf = pd.DataFrame(Xdata, columns... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_transform_interface_repr(example_tsds: TSDataset) -> None:\n trend_transform = TrendTransform(in_column=\"target\", detrend_model=LinearRegression(), model=\"rbf\")\n out_column = f\"regressor_{trend_transform.__repr__()}\"\n result = trend_transform.fit_transform(example_tsds.df)\n for seg in... | [
"0.64185077",
"0.6215986",
"0.6215151",
"0.6212859",
"0.6164075",
"0.60881317",
"0.6073903",
"0.60206157",
"0.60000205",
"0.5982403",
"0.5937053",
"0.5922052",
"0.59196836",
"0.5906585",
"0.58948827",
"0.5866362",
"0.5859663",
"0.5814201",
"0.5783901",
"0.57772166",
"0.577146... | 0.0 | -1 |
Reference values taken from NIST data base | def test_transport_sanity(self):
T = 400
cv_mole, W = 21005.045895231186, 28.014
species_name = "N2"
data = ct_properties.ctThermoTransport("gri30.cti", verbose=False)
data.evaluate_properties()
i = data.gas.species_index(species_name)
As, Ts, _, poly_mu, poly_k... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def referenzdaten_einlesen(self):\n self.refdata = np.genfromtxt(self.referencefile, skip_header=1, usecols=np.asarray(self.referenzspalte))\n self.Referencedata = Reference()",
"def prep_reference(self):\n\n # if basin\n if self.config.metric == 'basin':\n df = pd.read_csv... | [
"0.5812446",
"0.57540804",
"0.5708854",
"0.56447667",
"0.56308633",
"0.5510093",
"0.5462862",
"0.54256",
"0.53346974",
"0.5308915",
"0.52702427",
"0.52666277",
"0.52629995",
"0.52512944",
"0.52163595",
"0.52109677",
"0.5196691",
"0.519309",
"0.51905435",
"0.51647764",
"0.5161... | 0.0 | -1 |
This function help to build data that we need to train for CharCNN | def build_dataset(self, data_path, test_size):
dataset, label_dataset = self.load_dataset(data_path)
# shuffle
dataset, label_dataset = shuffle(dataset, label_dataset, random_state = 2111)
# split data
size = int(len(dataset) * (1 - test_size))
self.x_t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_dataset(self):\n print(\"reading data of images currently , please wait......\")\n x_train, y_train, _ = get_images(self.train_directory)\n x_test, y_test, _ = get_images(self.test_directory)\n x_train, y_train = image_subset(self.num_classes, x_train, y_train)\n x_test... | [
"0.68234545",
"0.6755744",
"0.6743118",
"0.6716415",
"0.67143404",
"0.6676263",
"0.66579074",
"0.65451914",
"0.6450987",
"0.6438156",
"0.639055",
"0.6383469",
"0.6370643",
"0.63556325",
"0.63493556",
"0.63293546",
"0.6261715",
"0.62448275",
"0.6217389",
"0.621433",
"0.6206522... | 0.61662716 | 23 |
Set common fields in layer to addressing dictonary. | def set_address_values(layer):
cursor = arcpy.SearchCursor(layer)
for row in cursor:
layer_fields = arcpy.ListFields(layer)
for x in range(len(layer_fields)):
layer_fields[x] = layer_fields[x].name
for key in address_dict:
if key in layer_fields and address_dict.g... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_attrs(self, **kwargs) -> None:\n self._obj.coords[GEO_MAP_COORD].attrs.update(**kwargs)",
"def update_asop_dict(asop_dict,region,coords,color,all_settings):\n # Set unique color\n asop_dict['color'] = color\n\n # Apply any general user settings\n asop_dict['grid_desc'] = all_settings.g... | [
"0.57628345",
"0.55964243",
"0.55274314",
"0.5520741",
"0.5513947",
"0.54532826",
"0.54528964",
"0.5352825",
"0.53380233",
"0.52978295",
"0.52767116",
"0.5263793",
"0.5233308",
"0.52296996",
"0.51820993",
"0.51604235",
"0.51503444",
"0.51213574",
"0.5110379",
"0.51047695",
"0... | 0.6680822 | 0 |
Only function in class. | def __init__(self, selected_address, side, ST_PREFIX, axis):
if ST_PREFIX == "W" or ST_PREFIX == "E":
self.axis_val = int(axis[0])
self.axis_dir = axis[2]
self.Neighbor_GRID_Val = str(self.axis_val - 1000)
self.axis_val_field = "AxisX_Val"
self.axis_di... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def func_in_class():\n return \"just a function hanging out in a class\"",
"def someMethod (self):\n pass",
"def __call__(self):\n pass",
"def __call__(self):\n pass",
"def independent_function():\n print(\"calling a function in exampleclass.py file that deos not belong to a ... | [
"0.7975919",
"0.6815057",
"0.6792388",
"0.6792388",
"0.67780167",
"0.6729474",
"0.6686155",
"0.6603621",
"0.6547703",
"0.6465931",
"0.6423527",
"0.639462",
"0.6383629",
"0.6363027",
"0.6363027",
"0.6363027",
"0.6363027",
"0.6363027",
"0.63594645",
"0.63594645",
"0.63387555",
... | 0.0 | -1 |
Get AWS ECS task information. For the puspose of getting the EC2 instance id by a given AWS ECS task name, for now, only the 'containerInstanceArn' is fetched from the AWS ECS task. | def get_tasks_information(
task: str,
list_tasks: str,
cluster=CLUSTER_NAME,
client=None,
region=REGION,
):
if not client:
session = boto3.session.Session()
client = session.client("ecs", region)
try:
# Get all tasks in the cluster.
cluster_tasks = client.list... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get(profile, cluster, tasks):\n client = boto3client.get(\"ecs\", profile)\n params = {}\n params[\"cluster\"] = cluster\n params[\"tasks\"] = tasks\n return client.describe_tasks(**params)",
"def get_task_details(self) -> task.TaskMetadata:\n return task.TaskMetadata(\n name... | [
"0.6348864",
"0.598766",
"0.5797471",
"0.5780299",
"0.57383114",
"0.56886894",
"0.56886894",
"0.56886894",
"0.56886894",
"0.5631942",
"0.55174756",
"0.5450972",
"0.5419298",
"0.54183954",
"0.54114175",
"0.5400899",
"0.53903484",
"0.53873485",
"0.5380392",
"0.53680474",
"0.536... | 0.68460375 | 0 |
Provide cli arguments. When used as executable script with command line options. | def main():
# import aws_ecs_services.arguments as arguments
from .arguments import get_cli_arguments
# args = arguments.get_cli_arguments()
args = get_cli_arguments()
by_service_dns = False
by_service_name = False
by_task_name = False
list_clusters = False
only_cluster_instances ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_cli_arguments(self):\n pass",
"def command_line_arguments():\n\n try:\n parser = argparse.ArgumentParser(description='Log Handler/Cleaner/Copier for Idemia DocAuth')\n\n # Add required arguments.\n parser.add_argument('action', choices=['clean', 'download'], type=str, help=... | [
"0.7795223",
"0.7400118",
"0.7389782",
"0.73847723",
"0.7258737",
"0.7255228",
"0.7248011",
"0.724467",
"0.7233422",
"0.717214",
"0.710672",
"0.7086328",
"0.7038673",
"0.70361656",
"0.7034294",
"0.70218986",
"0.68577576",
"0.6856456",
"0.6839717",
"0.6820217",
"0.68195426",
... | 0.0 | -1 |
Perform all graphical tasks for this frame. | def draw(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def render(self):\n self.delete()\n self.__create_background(self._imfname)\n # XXX must be last after successor implementation, but works without this line\n #self.c.event_generate(\"<Configure>\")\n #self.c.update_idletasks()",
"def __display(self):\n self.__rotate_mod... | [
"0.6894054",
"0.67451495",
"0.66122764",
"0.6550248",
"0.64933664",
"0.64838165",
"0.64499927",
"0.64354634",
"0.6388672",
"0.638855",
"0.6348826",
"0.6347117",
"0.6344852",
"0.63217235",
"0.6315397",
"0.6307719",
"0.6287468",
"0.62729156",
"0.62716115",
"0.6268537",
"0.62639... | 0.60316306 | 54 |
Perform all calculations for the amount of time that has passed. | def update(self, dt):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def compute(self, duration: Optional[Number]) -> None:\n await envs.sleep(duration)\n self.total_compute_time += duration",
"def _timed_execute(self):\n tstart = time.perf_counter()\n self._func(*self._func_args, **self._func_kwargs)\n tend = time.perf_counter() \n\n ... | [
"0.675693",
"0.64293903",
"0.6368792",
"0.61246926",
"0.6124316",
"0.6109275",
"0.6093881",
"0.6072631",
"0.6060954",
"0.60540646",
"0.60454965",
"0.6036691",
"0.6011635",
"0.6011255",
"0.59790087",
"0.5965647",
"0.5960139",
"0.59283966",
"0.5919275",
"0.59172326",
"0.5911589... | 0.0 | -1 |
automatically release blocks when blocks dict looses shape | def free_finalizer(self, dataset: dict):
# for gc being late
if dataset:
if dataset['vrtx']:
dataset['vrtx'].release()
if dataset['indx']:
dataset['indx'].release()
dataset.clear() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def finalize_block_construction(self, pyomo_block):\n pass",
"def blocks(self):\n pass",
"def _prepare_blocks():\n\n counter = blocks[0]['freeStart']\n maxBlocks = blocks[0]['maxBlocks']\n while(counter < maxBlocks) :\n try:\n # print (mount['parent'] + '/linddata.' + s... | [
"0.69011474",
"0.6140728",
"0.601313",
"0.59879786",
"0.59604454",
"0.58850497",
"0.581188",
"0.58049697",
"0.5709238",
"0.56697476",
"0.5665943",
"0.5652778",
"0.5647419",
"0.5641385",
"0.5623683",
"0.5622437",
"0.56117296",
"0.55557007",
"0.5543001",
"0.55420923",
"0.554209... | 0.50894725 | 94 |
Returns the details for a given plugin. | def load_details(self):
response = self._server._api_request("GET", "/plugins/plugin/%d" % self.id, "")
if response is not None:
self.id = response["id"]
self.name = response["name"]
self.family_name = response["family_name"]
self.attributes = response["at... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getPluginInfo(pluginId):\n url = f\"https://develop.roblox.com/v1/plugins?pluginIds={pluginId}\"\n r = requests.get(url)\n j = json.loads(r.text)\n return j['data']",
"def get_details(self):\n return PluginDetails(\n plugin_name=\"bad-string-detail-is-int\",\n ... | [
"0.72806084",
"0.71445906",
"0.7018347",
"0.6907199",
"0.6841461",
"0.683811",
"0.67773193",
"0.6708696",
"0.6622913",
"0.6553286",
"0.6524269",
"0.6480507",
"0.6399457",
"0.63910574",
"0.6374219",
"0.63439155",
"0.63216966",
"0.630637",
"0.62978387",
"0.62750924",
"0.626016"... | 0.6764841 | 7 |
Geeft bericht of iemand lang genoeg is voor de attractie. | def lang_genoeg(lengte):
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def substantiate():",
"def cliquer_sur_unité(self):",
"def makeGerund(self):\r\n clean_s = self.cleanString(self.text)\r\n LoW = clean_s.split()\r\n for x in LoW: \r\n if 'ing' in x and x not in self.gerund: \r\n self.gerund[x] = 1\r\n elif 'ing' in x a... | [
"0.6085675",
"0.60812867",
"0.5822387",
"0.5812007",
"0.56937695",
"0.56634116",
"0.5626631",
"0.56246907",
"0.56246907",
"0.56246907",
"0.56246907",
"0.56246907",
"0.5621488",
"0.5621488",
"0.5549839",
"0.55467236",
"0.5458848",
"0.5457804",
"0.5457804",
"0.54571193",
"0.545... | 0.7161606 | 0 |
This method is used to postprocess the form data. By default, it returns the raw `form.data` dictionary. | def process_step(self, form):
#print(form.data)
#print(form.data)
#print(self)
institution = {}
inst_list = []
if self.steps.current == '1':
institution['institution'] = form.data['1-0-institution']
institution['date_from'] =... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_post_data(self):\n if not self._form_data:\n self._form_data = async_to_sync(self.request.form)()\n return self._form_data",
"def get_form_data(self) -> dict:\n with logging.LogCall(__file__, \"get_form_data\", self.__class__):\n return self.serialize()",
"def... | [
"0.79507184",
"0.76475173",
"0.738958",
"0.73285085",
"0.7258168",
"0.6955681",
"0.6792374",
"0.65343493",
"0.65144867",
"0.6490603",
"0.6459408",
"0.6415936",
"0.63819605",
"0.63031137",
"0.6298642",
"0.6277921",
"0.62373143",
"0.6232082",
"0.62192225",
"0.60904664",
"0.6056... | 0.0 | -1 |
maps must match for joining to work | def mapsMatch(m1,m2):
same = True
f1 = file(m1,'r').readlines()
f2 = file(m2,'r').readlines()
for i, row in enumerate(f1):
row = row.strip().split()
row2 = f2[i].strip().split()
if row[0] <> row2[0]:
same = False
break
return same | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_mappingtojoin(self):\n usersaddresses = sql.join(users, addresses, users.c.user_id == addresses.c.user_id)\n m = mapper(User, usersaddresses, primary_key=[users.c.user_id])\n q = create_session().query(m)\n l = q.all()\n self.assert_result(l, User, *user_result[0:2])",
... | [
"0.6610568",
"0.63814634",
"0.61559236",
"0.6086679",
"0.58406264",
"0.5825378",
"0.5764346",
"0.57383496",
"0.57372516",
"0.5714955",
"0.56882495",
"0.5687337",
"0.5668063",
"0.56529844",
"0.56490266",
"0.56440884",
"0.56300807",
"0.56268895",
"0.5618193",
"0.56174135",
"0.5... | 0.54061365 | 31 |
geno codes must be appended row (marker) wise in subject (.ind file) order | def joinRows(r1,r2,outfname):
outf = open(outfname,'w')
f1 = file(r1,'r')
f2 = file(r2,'r')
for row1 in f1:
if row1.strip() > '':
row2 = f2.next()
outf.write('%s%s\n' % (row1.strip(),row2.strip()))
outf.close() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gencode_dic(gencode_file,gene_type_dic):\n gen_dic = {}\n for i in range(1,len(gencode_file)):\n words_gen = gencode_file[i].strip().split('\\t')\n chr_no = words_gen[2]\n trans_id = words_gen[1]\n cds_info = words_gen[13]\n cde_info = words_gen[14]\n gene_type =... | [
"0.5696215",
"0.5680898",
"0.5666527",
"0.55099",
"0.54899204",
"0.5471716",
"0.5390018",
"0.53788966",
"0.53691655",
"0.5336136",
"0.533134",
"0.5327106",
"0.5315752",
"0.5311932",
"0.52991354",
"0.5275869",
"0.52664924",
"0.5263865",
"0.5257725",
"0.5240358",
"0.52117866",
... | 0.0 | -1 |
individual data must be appended in same order as genos are being added | def joinInds(r1,r2,outfname):
outf = open(outfname,'w')
f1 = file(r1,'r')
f2 = file(r2,'r')
for row1 in f1:
outf.write('%s\n' % (row1.strip()))
for row1 in f2:
outf.write('%s\n' % (row1.strip()))
outf.close() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def apilar(self,dato):\r\n\t\tself.elementos.append(dato)\r\n\t\tself.len += 1",
"def concatenate_data():",
"def append(self, batch: Batch):",
"def append(self, data):\n if self._expand_mode:\n new_keys = set(data.keys()) - self.keys & self._keys\n self._expand(new_keys)\n ... | [
"0.6317219",
"0.62716526",
"0.60660607",
"0.5965007",
"0.5827419",
"0.58169585",
"0.58123124",
"0.57943267",
"0.57887346",
"0.5719474",
"0.5695228",
"0.5687933",
"0.5677406",
"0.56611586",
"0.5614816",
"0.5614328",
"0.55467606",
"0.5543412",
"0.55387115",
"0.55334795",
"0.553... | 0.0 | -1 |
provide both input file names up to extension and outfile path including name up to extension | def dojoin(ipath1,ipath2,opath):
r1 = '%s.map' % ipath1
r2 = '%s.map' % ipath2
if not mapsMatch(r1,r2):
print '### maps %s and %s do not match' % (r1,r2)
sys.exit(1)
outpath = '%s.map' % opath
shutil.copyfile(r1,outpath)
r1 = '%s.eigenstratgeno' % ipath1
r2 = '%s.eigenstrat... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ConvertFileName(cls,infile,band):\r\n try:\r\n import os\r\n except:\r\n raise ImportError(\"Can not find module os\")\r\n try:\r\n base = str.split(infile,\"_metadata.xml\")[0]\r\n print base\r\n ext=\"_band\"+str(band)+\".ntf\"\r\n ... | [
"0.66169494",
"0.6289752",
"0.62640893",
"0.62422895",
"0.6218007",
"0.62115467",
"0.61658305",
"0.61075085",
"0.6085868",
"0.60749346",
"0.60616755",
"0.60532296",
"0.60232437",
"0.5990847",
"0.5986506",
"0.59429944",
"0.5934633",
"0.59320587",
"0.5926914",
"0.59200156",
"0.... | 0.0 | -1 |
Initialize your data structure here. | def __init__(self):
self.queue = [] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _init_empty(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__... | [
"0.7765608",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7595176",
"0.75853467",
"0.7558298",
"0.7530608",
"0.7530608",
"0.7530608",
"0.7530608",
"0.7530608",
"0.74971247",
"0.74971247",
"0.7478105",
"0.7477832",
"0.7477832",
"0.7477832",
... | 0.0 | -1 |
Push element x to the back of queue. | def enqueue(self, x):
self.queue.append(x)
return self.queue | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def push(self, x): # time O(n)\n self.queue.append(x)\n for _ in range(len(self.queue)-1):\n self.queue.append(self.queue.popleft())",
"def push(self, x: int) -> None:\n self.queue.append(x)\n for _ in range(len(self.queue)-1):\n self.queue.append(... | [
"0.8549472",
"0.83887035",
"0.8322536",
"0.8316233",
"0.8296685",
"0.8249803",
"0.82164633",
"0.81946427",
"0.81946427",
"0.8059892",
"0.79438967",
"0.7901358",
"0.7855948",
"0.78556633",
"0.78169864",
"0.77913237",
"0.77355105",
"0.76975566",
"0.767749",
"0.76648164",
"0.764... | 0.7416999 | 31 |
Removes the element from in front of queue and returns that element. | def dequeue(self):
return self.queue.pop(0) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pop(self):\n self.queue.insert(len(self.queue), self.queue[0])\n self.queue.remove(self.queue[0])\n return self.queue.pop()",
"def front(self):\n return self.queue[0] if not self.empty() else None",
"def dequeue(self):\n if not self.front:\n raise AttributeErro... | [
"0.80894065",
"0.7844948",
"0.7837598",
"0.7796653",
"0.779448",
"0.7678269",
"0.76743865",
"0.7673315",
"0.7659757",
"0.7606835",
"0.75895596",
"0.7558154",
"0.7557646",
"0.7546004",
"0.7543471",
"0.75360584",
"0.7531314",
"0.75289166",
"0.752424",
"0.7517075",
"0.74940664",... | 0.7609435 | 9 |
Get the front element. | def peek(self):
return self.queue[0] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getFront(self):\n\t\tfront = self.queue[self.front]\n\t\treturn front\n\t\tpass",
"def getFront(self):\n if not self.isEmpty():\n return self._data[0]\n else:\n return -1",
"def front(self):\n return self.queue[0] if not self.empty() else None",
"def peek_front(... | [
"0.82009244",
"0.79261875",
"0.7852642",
"0.7791182",
"0.77886623",
"0.75723046",
"0.752337",
"0.7510604",
"0.7478953",
"0.7379256",
"0.7379256",
"0.734284",
"0.7323573",
"0.7320296",
"0.7291721",
"0.72772557",
"0.7269801",
"0.72657627",
"0.7253295",
"0.72355044",
"0.72213495... | 0.66313344 | 60 |
Returns whether the queue is empty. | def empty(self):
return self.queue == [] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_empty(self):\n return len(self.the_queue) == 0",
"def is_empty(self):\n return len(self.__queue) > 0",
"def is_empty(self):\n return len(self.queue) == 0",
"def is_empty(self):\n return len(self.queue) == 0",
"def is_empty(self):\n return self.queue == []",
"def ... | [
"0.9270249",
"0.92506766",
"0.923635",
"0.923635",
"0.9155843",
"0.9098441",
"0.9095006",
"0.90922606",
"0.90731245",
"0.9053733",
"0.89205354",
"0.89137155",
"0.8877591",
"0.88436323",
"0.88436323",
"0.88038146",
"0.8758203",
"0.87577534",
"0.87310195",
"0.86462456",
"0.8628... | 0.8835949 | 15 |
Define the class balanced cross entropy loss to train the network | def class_balanced_cross_entropy_loss(output, label):
labels = tf.cast(tf.greater(label, 0.5), tf.float32)
num_labels_pos = tf.reduce_sum(labels)
num_labels_neg = tf.reduce_sum(1.0 - labels)
num_total = num_labels_pos + num_labels_neg
output_gt_zero = tf.cast(tf.greater_equal(output, 0), tf.float... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup_loss(self):\n self.loss = nn.CrossEntropyLoss(weight = self.to_device(self.datasetManager.class_weights))\n #self.loss = nn.CrossEntropyLoss()",
"def cross_entropy_loss():\n return nn.CrossEntropyLoss()",
"def _classification_loss(self, logits, labels, num_classes):\n labels = tf.... | [
"0.7614255",
"0.72014856",
"0.7150281",
"0.7139225",
"0.7041426",
"0.69943374",
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"0.69841796",
"0.69580585",
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"0.691163",
"0.691163",
"0.6885535",
"0.67836154",
"0.6734367",
"0.6716514",
"0.6716514... | 0.6909369 | 16 |
Add a Pseudocode Operation at the actual active buffer. | def AddPseudoCode(self, pcode):
self.buffers[self.buffergrade].append(pcode) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_code(self, code):\n self.code += code",
"def add_operation(self):\n arg1 = self.memory[self.memory[self._cursor + 1]]\n arg2 = self.memory[self.memory[self._cursor + 2]]\n arg3 = self.memory[self._cursor + 3]\n self.memory[arg3] = arg1 + arg2\n # print(f'Cursor: ... | [
"0.5870351",
"0.5767791",
"0.57653064",
"0.5667283",
"0.5466743",
"0.54478973",
"0.52387804",
"0.52152646",
"0.5208209",
"0.5186463",
"0.51665425",
"0.51497793",
"0.51468796",
"0.5108849",
"0.5103262",
"0.50743014",
"0.5067011",
"0.50647295",
"0.5024439",
"0.50223887",
"0.498... | 0.7316713 | 0 |
Increment the BufferGrade and initialize a new empty buffer. | def IndentBuffer(self):
self.buffergrade += 1
self.buffers[self.buffergrade] = [] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fillBuffer():\n buff[bufferCounter].next = dataIn",
"def __init__(self, capacity):\n self.experiences = RingBuf(capacity)",
"def init_buffer(self):\n \n self.shape.buf = [pi3d.Buffer(self.shape, self.verts, self.texcoords, self.inds, self.norms)]\n self.shape.set_draw_det... | [
"0.58674264",
"0.5741333",
"0.5509345",
"0.54187745",
"0.537456",
"0.53408396",
"0.5315984",
"0.5291879",
"0.52720207",
"0.5246771",
"0.5140495",
"0.51366794",
"0.51127",
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"0.5096625",
"0.5072083",
"0.5029141",
"0.5018385",
"0.4994677",
"0.4994677",
"0.4994677",
... | 0.730155 | 0 |
Decrement the BufferGrade and pop out the buffer active before. | def DeIndentBuffer(self):
if self.buffergrade == 0:
raise Exception("You can't deindent more.")
self.buffergrade -= 1
tmp = self.buffers[self.buffergrade + 1]
del self.buffers[self.buffergrade + 1]
return tmp | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def decrease(self):\n self.score -= self.score",
"def decrement(self):\n self.data[self.pointer] -= 1\n self.data[self.pointer] %= 256",
"def IndentBuffer(self):\n self.buffergrade += 1\n self.buffers[self.buffergrade] = []",
"def RemoveGrade(self, grade):\n if not s... | [
"0.62998307",
"0.6187696",
"0.6057455",
"0.5972686",
"0.58809793",
"0.578995",
"0.5724787",
"0.57013",
"0.5689314",
"0.5660951",
"0.5610543",
"0.5608327",
"0.55659264",
"0.55524766",
"0.5540197",
"0.55076224",
"0.5456718",
"0.5449712",
"0.5409593",
"0.54038453",
"0.53746724",... | 0.71859 | 0 |
Will return the shared buffer of all the self subclasses. | def GetMainBuffer(self):
tmp = self.buffers[0]
self.buffers[0] = []
return tmp | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getAll(self):\n return self.dataBuffer",
"def read_shared(self):\n return self._read_all()",
"def read_shared(self):\n return self._read_all()",
"def common(self):\n return self._common",
"def get_bases(self):\n # TODO: subclassing\n return (self.py_class,)",
... | [
"0.58079183",
"0.5729144",
"0.5729144",
"0.5667983",
"0.5634361",
"0.5608551",
"0.5481564",
"0.54492664",
"0.5438543",
"0.5438543",
"0.5438543",
"0.5422512",
"0.54199225",
"0.5405491",
"0.539883",
"0.53901875",
"0.53715754",
"0.53574383",
"0.53372616",
"0.5331279",
"0.5319714... | 0.5415913 | 13 |
Get a reference to the actual buffer activated. | def RefBuffer(self):
return self.buffers[self.buffergrade] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def current_buffer(self):\n return self.layout.current_buffer",
"def getBuffer(self):\n return self.buffer",
"def buffer_backend(cls, *args, **kwargs):\n return cls._buffer_context",
"def current_buffer_app(self):\n return self.session.current_buffer",
"def buffer(self):\n ... | [
"0.70962286",
"0.69201726",
"0.67237633",
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"0.6613722",
"0.62484485",
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"0.61454296",
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"0.5955822",
"0.5955822",
"0.59430313",
"0.58911574",
"0.5882561",
"0.5830065",
"0.58167... | 0.7871913 | 0 |
Track a code indentation index for successive utilization. | def TrackIfIndex(self, index):
self.indentindex.append(index) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def increase_code_indent(self) -> None:\n self._parent_node.increase_code_indent()",
"def _increaseindentation(self):\n self._indentlist.append(self._curindent)\n if not self._equalsigns[-1]:\n self._curindent = self._curindent + self._indent",
"def getIndentationLevel(self, cod... | [
"0.61810654",
"0.60863245",
"0.5817759",
"0.5709027",
"0.5614261",
"0.5614261",
"0.5520226",
"0.55129415",
"0.54851073",
"0.54282254",
"0.53754544",
"0.53624535",
"0.532262",
"0.52931166",
"0.5262821",
"0.52572817",
"0.5244937",
"0.52138895",
"0.5192445",
"0.5161051",
"0.5153... | 0.70099694 | 0 |
Get the last code indentation index tracked as reference. | def GetIfIndex(self):
return self.indentindex[-1] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def last_index(self) -> int:\n return self._last_index",
"def indentation_level(self):\n return self._indentation_levels[-1]",
"def last_sequence_ind(self,):\n return self.last_sequence_ind_",
"def _get_last_code_line():\n return max(_code_lines) + 2",
"def get_last_index(self):\n ... | [
"0.6989419",
"0.68731844",
"0.67984694",
"0.65894204",
"0.64901143",
"0.64773256",
"0.63904345",
"0.6377186",
"0.6306196",
"0.6305273",
"0.62961644",
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"0.62961644",
"0.62961644",
"0.62961644",
"0.62961644",
"0.6286268",
"0.62604773",
"0.6259666",
"0.61679256",
"0... | 0.66052157 | 3 |
Pop (get and remove) the last code indentation index tracked. | def PopIfIndex(self):
return self.indentindex.pop() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _decreaseindentation(self):\n self._curindent = self._indentlist.pop()",
"def pop(self) -> int:\n return self.stack.pop()",
"def pop(self) -> int:\n return self._stack.pop()",
"def pop(self) -> int:\n for i in range(len(self.stack) - 1):\n self.stack.append(self.sta... | [
"0.687736",
"0.662047",
"0.65572536",
"0.64603764",
"0.6362599",
"0.6348772",
"0.63447845",
"0.630998",
"0.6291612",
"0.6259269",
"0.624546",
"0.61962366",
"0.6184571",
"0.61161476",
"0.611117",
"0.60742784",
"0.6037302",
"0.60337037",
"0.60090023",
"0.59744895",
"0.5953556",... | 0.802693 | 0 |
Initialization of protected Operation Object attribute for subclasses. | def __init__(self):
self._OPERATION = None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self):\n\n self.operations = {}",
"def _init(self):\n raise NotImplementedError",
"def __init__(self):\r\n self.operation_map = {}",
"def init(self):\n raise NotImplementedError",
"def init(self):\n raise NotImplementedError",
"def __init__(self):\n ... | [
"0.69042325",
"0.6817324",
"0.66968143",
"0.65770996",
"0.65770996",
"0.6513839",
"0.6513839",
"0.6513839",
"0.6513839",
"0.64662194",
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"0.6404217",
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"0.6404217",
"0.6404217",
"0.6404217",
"0.6404217",
"0.6404217",
"0.6404217",
"0.6404217",... | 0.7562495 | 0 |
Get the Operation Object generated by the command. | def getOp(self):
return self._OPERATION | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_operation_obect(self, method):\n pass",
"def get_operation(\n self,\n ) -> Callable[[operations_pb2.GetOperationRequest], operations_pb2.Operation]:\n # Generate a \"stub function\" on-the-fly which will actually make\n # the request.\n # gRPC handles serialization a... | [
"0.6874343",
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"0.67712283",
"0.67712283",
"0.67545724",
"0.6746998",
"0.6746998",
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"0.6541429",
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"0.64114374",
"0.640891",
"0.64030427",
"0.6372547",
"0.6367869",
"0.6367869",
"0.63323... | 0.71553755 | 0 |
Creates a temporary image for manipulation, and handles optional RGB conversion. | def _create_tmp_image(self, content):
content.seek(0)
image = Image.open(content)
if self.force_rgb and image.mode not in ('L', 'RGB', 'RGBA'):
image = image.convert('RGB')
return image | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def temporary_unsupported_image(self):\n image = Image.new('RGB', (1, 1))\n tmp_file = tempfile.NamedTemporaryFile(suffix='.ppm')\n image.save(tmp_file, 'ppm')\n # important because after save(),\n # the fp is already at the end of the file\n tmp_file.seek(0) # retrieves ... | [
"0.67979735",
"0.6447679",
"0.6425846",
"0.6331001",
"0.6304116",
"0.6232688",
"0.6175286",
"0.60538095",
"0.6020988",
"0.6015573",
"0.59706867",
"0.59613866",
"0.5947222",
"0.5861616",
"0.5856823",
"0.5853021",
"0.5808916",
"0.5805031",
"0.57975703",
"0.5789881",
"0.57089484... | 0.70588124 | 0 |
Returns image data as a ``ContentFile``. | def _create_content_file(self, content):
io = BytesIO()
content.save(io, self._normalize_format(), quality=self.quality)
return ContentFile(io.getvalue()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getImgContentFile(img):\n format, imgstr = img.split(';base64,')\n ext = format.split('/')[-1]\n file = ContentFile(base64.b64decode(imgstr), name='temp.' + ext)\n return file",
"def contents(self):\n if not self._contents:\n if self._path:\n # Read file into memo... | [
"0.74447596",
"0.6932529",
"0.67421204",
"0.67015547",
"0.65835774",
"0.6578695",
"0.6555087",
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"0.63615793",
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"0.61542207",
"0.61115354",
"0.6059986",
"0.6055182",
"0.6054496",
"0.60452163",
"0.601... | 0.63306314 | 9 |
Resizes a valid image, and returns as a Django ``ContentFile``. | def generate(self, content):
tmp = self._create_tmp_image(content)
rendered = self._render(tmp)
return self._create_content_file(rendered) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def resize_img(self,scale=1):\n reduced = self.image.reduce((scale,scale))\n reduced.save(\"../edited/{}\".format(self.image.filename))\n\n reduced = Image.open(\"../edited/{}\".format(self.image.filename))\n return reduced",
"def resize_image(first_image, width, height):\n resizin... | [
"0.6446886",
"0.63090426",
"0.6298052",
"0.61945766",
"0.60929877",
"0.6076873",
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"0.6004527",
"0.5964197",
"0.59304476",
"0.59220564",
"0.5894676",
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"0.5864532",
"0.58378077",
"0.58318716",
"0.5828034",
"0.58193",
"0.57947105",
"0.5785676",
"0.57840... | 0.0 | -1 |
Renders the image. Override this method when creating a custom renderer. | def _render(self, image):
raise NotImplementedError('Override this method to render images!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def render(self) -> None:\n if self.native_rendering:\n self._render()\n else:\n self.renderer.render_image(self.get_rendered_image())",
"def _render(self):\n self.dirty = False\n self.image = self.font.render(self._text, self.aa, self.color_fg)\n self.rec... | [
"0.83629304",
"0.7514363",
"0.738157",
"0.71521425",
"0.7143713",
"0.7124317",
"0.7027804",
"0.69824153",
"0.697108",
"0.69224477",
"0.69172174",
"0.69109416",
"0.68451834",
"0.676605",
"0.6748223",
"0.66155213",
"0.660075",
"0.660075",
"0.65852135",
"0.64857286",
"0.64756054... | 0.86215574 | 0 |
Version management for migrations. | def __eq__(self, other):
return (
self.bleed == other.bleed and
self.width == other.width and
self.height == other.height
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def migration():",
"def migrate(cr, version):\n pass",
"def version(self):\r\n print migration.db_version()",
"def post_migrations(self):",
"def _run_migrations(self, current_migration_version: int):\n logger.debug(\"Checking for necessary database migrations...\")\n\n while current... | [
"0.7271674",
"0.6912402",
"0.6781953",
"0.66197056",
"0.6540998",
"0.64763844",
"0.63564444",
"0.6351916",
"0.6346999",
"0.627028",
"0.6214616",
"0.61989695",
"0.61721605",
"0.61721605",
"0.6119614",
"0.6112119",
"0.60870755",
"0.6083832",
"0.6082907",
"0.6082181",
"0.5973878... | 0.0 | -1 |
Version management for migrations. | def __eq__(self, other):
return (
self.constrain == other.constrain and
self.width == other.width and
self.height == other.height and
self.upscale == other.upscale
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def migration():",
"def migrate(cr, version):\n pass",
"def version(self):\r\n print migration.db_version()",
"def post_migrations(self):",
"def _run_migrations(self, current_migration_version: int):\n logger.debug(\"Checking for necessary database migrations...\")\n\n while current... | [
"0.7271674",
"0.6912402",
"0.6781953",
"0.66197056",
"0.6540998",
"0.64763844",
"0.63564444",
"0.6351916",
"0.6346999",
"0.627028",
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"0.6112119",
"0.60870755",
"0.6083832",
"0.6082907",
"0.6082181",
"0.5973878... | 0.0 | -1 |
Version management for migrations. | def __eq__(self, other):
return (
self.bg_color == other.bg_color and
self.width == other.width and
self.height == other.height
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def migration():",
"def migrate(cr, version):\n pass",
"def version(self):\r\n print migration.db_version()",
"def post_migrations(self):",
"def _run_migrations(self, current_migration_version: int):\n logger.debug(\"Checking for necessary database migrations...\")\n\n while current... | [
"0.7271674",
"0.6912402",
"0.6781953",
"0.66197056",
"0.6540998",
"0.64763844",
"0.63564444",
"0.6351916",
"0.6346999",
"0.627028",
"0.6214616",
"0.61989695",
"0.61721605",
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"0.6119614",
"0.6112119",
"0.60870755",
"0.6083832",
"0.6082907",
"0.6082181",
"0.5973878... | 0.0 | -1 |
Normalize, pad and batch the input images. | def preprocess_image(self, batched_inputs):
images = [x.to(self.device) for x in batched_inputs]
norms = [self.normalizer(x) for x in images]
size = (norms[0].shape[1],norms[0].shape[2])
images = ImageList.from_tensors(norms, self.backbone.size_divisibility)
return images, size | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def normalize_images(data, blend_cat, Args):\n im = data['X_train']['blend_image']\n std = np.std(im)\n mean = np.mean(im)\n data['X_train']['blend_image'] = (im - mean) / std\n data['X_val']['blend_image'] = (data['X_val']['blend_image'] - mean) / std\n data['X_train'] = normalize_other_inputs(d... | [
"0.7097169",
"0.66408646",
"0.65812963",
"0.6465365",
"0.6464898",
"0.6406874",
"0.63755596",
"0.63661265",
"0.6324502",
"0.6318984",
"0.63017005",
"0.6297598",
"0.6261444",
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"0.6226007",
"0.6213169",
"0.6194187",
"0.6189247",
"0.61866045",
"0.6185736",
"0.618346... | 0.67390656 | 1 |
Read a key file, if the key file does not exist create one | def keys(self) -> None:
path = Path('./config/key')
global key
# If the file path does not exist, create one
if not path.exists():
os.makedirs(path)
while True:
# read key.key file
try:
file = open(path / 'key.key', 'r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_key(key_name):\n if not p.exists(key_name):\n write_key(key_name)\n\n return open(key_name, \"rb\").read()",
"def read_key(self, keyfile_name):\n\n with open(keyfile_name, 'rb') as f:\n self.key = f.read()\n self.cryptor = Fernet(self.key)",
"def readKey(self,... | [
"0.75079066",
"0.70167714",
"0.6591259",
"0.6573006",
"0.65389",
"0.6534434",
"0.6523295",
"0.6516931",
"0.6431083",
"0.64273334",
"0.64232206",
"0.6402406",
"0.6346148",
"0.63321847",
"0.62482345",
"0.62318903",
"0.6229613",
"0.61933273",
"0.6170967",
"0.6168514",
"0.616238"... | 0.60398936 | 28 |
Ensure that apigateway v1 and apigateway v2 actions are both present in the ses namespace | def test_services_with_multiple_pages_apigateway(self):
# API Gateway Management V1: https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonapigatewaymanagement.html
self.assertTrue("apigateway:AddCertificateToDomain" in self.all_actions)
self.assertTrue("apigateway:Remove... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_gh_226_elasticloadbalancing_v1_and_v2(self):\n results = get_actions_for_service(\"elasticloadbalancing\")\n # print(json.dumps(results, indent=4))\n lb_v1_only_action = \"elasticloadbalancing:CreateTargetGroup\"\n lb_v2_only_action = \"elasticloadbalancing:SetSecurityGroups\"\... | [
"0.59183055",
"0.57958144",
"0.5341116",
"0.51459986",
"0.5056637",
"0.5025083",
"0.49718618",
"0.49709255",
"0.49639255",
"0.4939532",
"0.48318732",
"0.47402886",
"0.47391623",
"0.47184974",
"0.4717983",
"0.47155645",
"0.47113252",
"0.4703302",
"0.46926475",
"0.46769983",
"0... | 0.5989848 | 0 |
Ensure that awsmarketplace actions from all the different awsmarketplace SAR pages are present in the IAM definition. | def test_services_with_multiple_pages_aws_marketplace(self):
# Overlap: AWS Marketplace, Marketplace Catalog, and AWS Marketplace Entitlement service, AWS Marketplace Image Building Service, AWS Marketplace Metering Service, AWS Marketplace Private Marketplace, and AWS Marketplace Procurement Systems
# ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_actions_with_arn_type_and_access_level_case_3(self):\n desired_output = [\n 's3:PutAccountPublicAccessBlock',\n 's3:PutAccessPointPublicAccessBlock'\n ]\n output = get_actions_with_arn_type_and_access_level(\n # \"ram\", \"resource-share\", \"Write... | [
"0.58062184",
"0.57554114",
"0.5695702",
"0.5673701",
"0.5447731",
"0.5414008",
"0.53181934",
"0.5090683",
"0.5057209",
"0.49688128",
"0.49623215",
"0.49491638",
"0.49443293",
"0.49354288",
"0.4900723",
"0.48934472",
"0.48312107",
"0.48288488",
"0.47950754",
"0.4768656",
"0.4... | 0.66148233 | 0 |
Ensure that greengrass v1 and greengrass v2 actions are both present in the greengrass namespace | def test_services_with_multiple_pages_greengrass(self):
# Greengrass V1: https://docs.aws.amazon.com/service-authorization/latest/reference/list_awsiotgreengrass.html
self.assertTrue("greengrass:CreateResourceDefinition" in self.all_actions)
# Greengrass V2: https://docs.aws.amazon.com/service-a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_gh_226_elasticloadbalancing_v1_and_v2(self):\n results = get_actions_for_service(\"elasticloadbalancing\")\n # print(json.dumps(results, indent=4))\n lb_v1_only_action = \"elasticloadbalancing:CreateTargetGroup\"\n lb_v2_only_action = \"elasticloadbalancing:SetSecurityGroups\"\... | [
"0.62013024",
"0.5185163",
"0.51849663",
"0.50805354",
"0.50188154",
"0.49678308",
"0.49544063",
"0.49272656",
"0.49225903",
"0.49052584",
"0.4849131",
"0.48472935",
"0.47611517",
"0.4737386",
"0.47336262",
"0.46869755",
"0.46836528",
"0.4678428",
"0.46226096",
"0.46140948",
... | 0.6528508 | 0 |
Ensure that elb v1 and elb v2 actions are both present in the elasticloadbalancing namespace | def test_services_with_multiple_pages_elb(self):
results = get_actions_for_service("elasticloadbalancing")
actions = [
"elasticloadbalancing:ApplySecurityGroupsToLoadBalancer",
"elasticloadbalancing:AttachLoadBalancerToSubnets",
"elasticloadbalancing:ConfigureHealthCh... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_gh_226_elasticloadbalancing_v1_and_v2(self):\n results = get_actions_for_service(\"elasticloadbalancing\")\n # print(json.dumps(results, indent=4))\n lb_v1_only_action = \"elasticloadbalancing:CreateTargetGroup\"\n lb_v2_only_action = \"elasticloadbalancing:SetSecurityGroups\"\... | [
"0.7524008",
"0.5502818",
"0.53605366",
"0.5155062",
"0.50617534",
"0.5045359",
"0.49514994",
"0.4864293",
"0.48232004",
"0.47804296",
"0.47697622",
"0.4720676",
"0.47133136",
"0.4713231",
"0.47080573",
"0.4707765",
"0.47045755",
"0.46887946",
"0.46873748",
"0.4683964",
"0.46... | 0.5852793 | 1 |
Ensure that lex v1 and lex v2 actions are both present in the lex namespace | def test_services_with_multiple_pages_lex(self):
# Lex V1: https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonlex.html
self.assertTrue("lex:DeleteUtterances" in self.all_actions)
# Lex V2: https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonle... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_user_grammar_actions():\n grammar = \"\"\"\n S: A B C;\n @nonterm_action\n C: A B;\n A: \"a\";\n @term_action\n B: \"b\";\n \"\"\"\n\n called = [False, False]\n\n def nonterm_action(_, __):\n called[0] = True\n\n def term_action(_, __):\n called[1] = True\n\n... | [
"0.5523519",
"0.54551274",
"0.52533966",
"0.4947026",
"0.49150628",
"0.4877916",
"0.4869475",
"0.4861803",
"0.47912464",
"0.47661808",
"0.47431847",
"0.47416365",
"0.4730279",
"0.47081596",
"0.46722156",
"0.46685877",
"0.46628264",
"0.46338037",
"0.463026",
"0.46180958",
"0.4... | 0.6062302 | 0 |
Ensure that Kinesis Analytics V1 actions are both present in the ses namespace | def test_services_with_multiple_pages_kinesis_analytics(self):
# Kinesis Analytics V1
results = get_actions_for_service("kinesisanalytics")
actions = [
"kinesisanalytics:GetApplicationState", # Only in v1, not v2
"kinesisanalytics:ListApplications", # In both
]
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_action_names_overlap_issue(self):\n # Kafka actions used to be in two pages but are now one. This verifies the current state.\n # results = get_actions_for_service(\"kafka\")\n # print(results)\n actions = [\n \"kafka:BatchAssociateScramSecret\",\n \... | [
"0.57531",
"0.5480236",
"0.5119307",
"0.5114083",
"0.50098765",
"0.49987218",
"0.4811319",
"0.47456703",
"0.4734747",
"0.4714206",
"0.4702901",
"0.4696541",
"0.46635452",
"0.46622923",
"0.4657708",
"0.46406722",
"0.46395832",
"0.45904428",
"0.45893326",
"0.45853838",
"0.45726... | 0.55055636 | 1 |
Ensure that ses v1 and ses v2 actions are both present in the ses namespace | def test_services_with_multiple_pages_ses(self):
# SES V1: https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonses.html
self.assertTrue("ses:PutIdentityPolicy" in self.all_actions)
# SES V2: https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazons... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_gh_226_elasticloadbalancing_v1_and_v2(self):\n results = get_actions_for_service(\"elasticloadbalancing\")\n # print(json.dumps(results, indent=4))\n lb_v1_only_action = \"elasticloadbalancing:CreateTargetGroup\"\n lb_v2_only_action = \"elasticloadbalancing:SetSecurityGroups\"\... | [
"0.5713234",
"0.550883",
"0.5373594",
"0.53643465",
"0.5290291",
"0.5130985",
"0.5121447",
"0.48156258",
"0.479505",
"0.479243",
"0.47852328",
"0.47827813",
"0.47478974",
"0.4735454",
"0.4725077",
"0.47070414",
"0.46997523",
"0.4678125",
"0.46708792",
"0.4640849",
"0.46401328... | 0.62560695 | 0 |
Other missing actions from GH 393 | def test_other_iam_data_fixes_in_GH_393(self):
# Cassandra: https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonkeyspacesforapachecassandra.html
results = get_actions_for_service("cassandra")
self.assertTrue("cassandra:Restore" in results)
# Comprehend Medical: ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def actions() -> None:\n pass",
"def actions():\n pass",
"def test_10_unsupported_actions(self):\n\n def __count_pulled_packages(pth):\n self.pkgrepo(\"list -F tsv -H -s {0}\".format(pth))\n return len(self.output.splitlines())\n\n ... | [
"0.67267066",
"0.65667135",
"0.64318216",
"0.6355506",
"0.6210274",
"0.6148939",
"0.6109755",
"0.60450846",
"0.60199803",
"0.5994511",
"0.5994511",
"0.59711343",
"0.5918675",
"0.591639",
"0.59116274",
"0.5877087",
"0.5877087",
"0.5775038",
"0.57616264",
"0.5738314",
"0.571399... | 0.60793984 | 7 |
Ensure that kafka actions are not overwritten in the IAM definition | def test_kafka_action_names_overlap_issue(self):
# Kafka actions used to be in two pages but are now one. This verifies the current state.
# results = get_actions_for_service("kafka")
# print(results)
actions = [
"kafka:BatchAssociateScramSecret",
"kafka:BatchDisa... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def legal_actions(self):\n raise NotImplementedError",
"def get_actions(self, request):\n actions = super().get_actions(request)\n if not settings.PUBLISHER_CODE:\n del actions['create_cwr']\n if 'delete_selected' in actions:\n del actions['delete_selected']\n ... | [
"0.57733667",
"0.5674129",
"0.5623118",
"0.55654687",
"0.54859173",
"0.5416407",
"0.53971905",
"0.5386766",
"0.5313959",
"0.5262459",
"0.52369434",
"0.5227309",
"0.5218352",
"0.5207143",
"0.51959413",
"0.51855755",
"0.5174657",
"0.51633334",
"0.51326454",
"0.51265115",
"0.506... | 0.67827463 | 0 |
1. Maintain a decreasing stack by scanning nums from left to right. 2. Then scan the nums from right to left and calculate the maxWidth between each ramp. | def maxWidthRamp(self, nums: list[int]) -> int:
maxWidth = 0
descStack = []
# Generate decreasing stack.
for i, num in enumerate(nums):
if not descStack or nums[descStack[-1]] > num:
descStack.append(i)
# Check elements from right to left.
fo... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def peg_width_per_levels(base_width):\n limiter = 2\n decrementer = -2\n decrementing_width = int(base_width)\n peg_count_per_level = []\n while decrementing_width >= limiter:\n peg_count_per_level.append(int(decrementing_width))\n decrementing_width += decrementer\n return peg_coun... | [
"0.6181188",
"0.61154115",
"0.61118263",
"0.58728755",
"0.5702233",
"0.5701698",
"0.5680999",
"0.55414397",
"0.553379",
"0.5523938",
"0.55195713",
"0.5513929",
"0.5513566",
"0.550096",
"0.54771763",
"0.5460938",
"0.5459851",
"0.5444232",
"0.5441669",
"0.54264915",
"0.54041374... | 0.8285866 | 0 |
A little function to make graphing less of a pain. Creates a plot with titles and axis labels. Adds a new line to a blank figure and labels it. | def plothusly(ax, x, y, *, xtitle='', ytitle='',
datalabel='', title='', linestyle = '-',
marker = ''):
ax.set_xlabel(xtitle)
ax.set_ylabel(ytitle)
ax.set_title(title)
out = ax.plot(x, y, zorder=1, label=datalabel, linestyle = linestyle,
marker = marker)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def newGraph(self, xlab, ylab):\r\n if (not self.doMPL):\r\n newGraph = Gnuplot(debug=0)\r\n\t #newGraph('set data style linespoints')\r\n\t newGraph.set_label('xlabel', xlab)\r\n\t newGraph.set_label('ylabel', ylab)\r\n return newGraph\r\n else:\r\n self.mplFigCou... | [
"0.73383814",
"0.726306",
"0.71619123",
"0.7137723",
"0.70683104",
"0.70184547",
"0.69500715",
"0.6938889",
"0.6920055",
"0.69195294",
"0.6891798",
"0.67042345",
"0.6702502",
"0.66961604",
"0.6673671",
"0.66625386",
"0.66425776",
"0.66200614",
"0.66146296",
"0.6595933",
"0.65... | 0.6106391 | 57 |
A little function to make graphing less of a pain Adds a new line to a blank figure and labels it | def plothus(ax, x, y, *, datalabel='', linestyle = '-',
marker = ''):
out = ax.plot(x, y, zorder=1, label=datalabel, linestyle = linestyle,
marker = marker)
return out | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_graph(self, x, y, label):\n pyplot.plot(x[:len(y)], y[:len(x)], label=label)",
"def line_graph():\r\n #create the data in an array\r\n xval = np.arange(0,6,(np.pi*(1./10)))\r\n yval = np.cos(xval)\r\n data = np.array([xval,yval])\r\n data = data.transpose()\r\n y = np.arange(-1,1... | [
"0.6918902",
"0.6715607",
"0.66300875",
"0.6610081",
"0.6605",
"0.65108675",
"0.6509052",
"0.6483655",
"0.64417446",
"0.6436465",
"0.64165217",
"0.64094067",
"0.6303501",
"0.6279875",
"0.62422055",
"0.6156551",
"0.61285985",
"0.6121611",
"0.6119316",
"0.61107874",
"0.61096317... | 0.5919027 | 36 |
Given an input (instance of the BenchInput tuple), constructs and validates a disjunctive ChaumPedersen proof, returning the time (in seconds) to do each operation. | def chaum_pedersen_bench(bi: BenchInput) -> Tuple[float, float]:
(keypair, r, s) = bi
ciphertext = get_optional(elgamal_encrypt(0, r, keypair.public_key))
start1 = timer()
proof = make_disjunctive_chaum_pedersen_zero(
ciphertext, r, keypair.public_key, ONE_MOD_Q, s
)
end1 = timer()
v... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def part2(input):\n ps = PlanetSystem(input)\n c = ps.total_cycle_time()\n return c",
"def part_2():\n input_ = parse_input() + list(range(10, 1_000_001))\n cups = turn_input_into_cups(input_)\n cups = solve(cups, first_cup=cups[input_[0]], turns=10_000_000)\n\n return cups[1].next.number * ... | [
"0.57208085",
"0.54804933",
"0.5131725",
"0.50099516",
"0.49980843",
"0.49875277",
"0.4948482",
"0.49447292",
"0.49406472",
"0.4887707",
"0.4879715",
"0.48475006",
"0.48428223",
"0.4833638",
"0.48149478",
"0.48010787",
"0.4800391",
"0.4798947",
"0.47890905",
"0.47886792",
"0.... | 0.60869694 | 0 |
Placeholder function used just to warm up the parallel mapper prior to benchmarking. | def identity(x: int) -> int:
return x | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def warmup():\n return ''",
"def warmup():\n return ''",
"def warmup():\n return ''",
"def parallelizer(func, arg=False):\n if arg:\n func(arg)\n else:\n func()",
"def pfmap(func, workers=8):\n return fmap(func)",
"def mapper(fun: Callable[[str], Pin], /) -> None:",
... | [
"0.58914787",
"0.58914787",
"0.58914787",
"0.58523786",
"0.58267385",
"0.5818383",
"0.5795961",
"0.5795961",
"0.5604408",
"0.5542775",
"0.5542228",
"0.54952943",
"0.5452233",
"0.5393733",
"0.5384684",
"0.5382945",
"0.5378095",
"0.5368914",
"0.53356403",
"0.52627987",
"0.52194... | 0.0 | -1 |
Average of a list of numbers | def average(l: List[float]) -> float:
n = len(l)
if n == 0:
return 0
return sum(l) / n | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def number_list_average(numbers):\n return sum(numbers)/len(numbers)",
"def avg(list):\n return sum(list) / len(list)",
"def avg(l):\n return (sum(l)/float(len(l)))",
"def mean(num_list):\n i = 0\n num_sum = 0.0\n for item in num_list:\n num_sum += item\n i... | [
"0.88870585",
"0.848456",
"0.8434734",
"0.8398049",
"0.83776134",
"0.8336529",
"0.8316348",
"0.83155566",
"0.82814676",
"0.8269709",
"0.8267124",
"0.8266494",
"0.8249835",
"0.82441944",
"0.8243413",
"0.8158804",
"0.815238",
"0.81390256",
"0.80972695",
"0.80799866",
"0.8048972... | 0.8089239 | 19 |
Standard deviation of a list of numbers | def std(l: List[float]) -> float:
n = len(l)
if n == 0:
return 0
avg = average(l)
return sqrt(sum([(avg - i) * (avg - i) for i in l])) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def standard_deviation(xs: List[float]) -> float:\n return math.sqrt(variance(xs))",
"def standard_deviation(xs: List[float]) -> float:\n return math.sqrt(variance(xs))",
"def standard_deviation(list):\n num_items = len(list)\n mean = sum(list) / num_items\n differences = [x - mean for x in list... | [
"0.85239553",
"0.85239553",
"0.82795185",
"0.8250837",
"0.811858",
"0.8115698",
"0.81116855",
"0.80819494",
"0.80761546",
"0.8022738",
"0.79791003",
"0.7964581",
"0.7951416",
"0.7936604",
"0.79159623",
"0.7855638",
"0.7839232",
"0.7821115",
"0.7801466",
"0.7798936",
"0.779461... | 0.7768153 | 21 |
Test of function choosing if log rotation is needed | def test_need_to_rotate_log(self):
self.assertTrue(need_to_rotate_log(0, 20, 'daily', 15, 'daily'), 'rotate log by time')
self.assertFalse(need_to_rotate_log(10, 20, 'daily', 15, 'hourly'), 'do not rotate log by time')
self.assertTrue(need_to_rotate_log(10, 20, 'daily', 25, None), 'rotate log by... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_log_rotation(self):\n self.conveyer.execute(self.conveyer.log(\"{message: \\\"first\\\"}\"))\n self.conveyer.execute(self.conveyer.log(\"{message: \\\"second\\\"}\"))\n self.conveyer.execute(self.conveyer.log(\"{message: \\\"third\\\"}\"))\n filename = self.conveyer.rotate_logs... | [
"0.62220013",
"0.61344224",
"0.58783966",
"0.58642936",
"0.5808232",
"0.5750104",
"0.5715419",
"0.5713662",
"0.5678804",
"0.56212765",
"0.55951023",
"0.5573171",
"0.5567551",
"0.5551365",
"0.55413747",
"0.5514498",
"0.5495516",
"0.5494864",
"0.54912615",
"0.5475333",
"0.54750... | 0.7284713 | 0 |
Test of conversion human like file size units to integer | def test_human_size_units_to_base(self):
self.assertEqual(human_size_units_to_base(1), 1)
self.assertEqual(human_size_units_to_base('1'), 1)
self.assertEqual(human_size_units_to_base('1b'), 1)
self.assertEqual(human_size_units_to_base('1k'), 1000)
self.assertEqual(human_size_unit... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _file_scale(fn):\n s = utils.file_word(fn)\n try:\n n = int(s, 0)\n except ValueError:\n n = float(s)\n return n",
"def test_human_size(self):\n\n human_size = pyCompressor.human_size\n\n self.assertEqual(human_size(2), \"2.0 bytes\")\n self.assertEqual(human_si... | [
"0.7208111",
"0.70847607",
"0.70484537",
"0.7023813",
"0.692497",
"0.6893805",
"0.6853747",
"0.6853747",
"0.68404585",
"0.6745593",
"0.66911465",
"0.66774565",
"0.6614509",
"0.6607619",
"0.659698",
"0.65692264",
"0.6559572",
"0.6522625",
"0.6506409",
"0.65063375",
"0.647743",... | 0.6409324 | 27 |
Tests of try rotation without configuration | def test_process_log_without_configuration(self):
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
compressors = process_log(
datetime.datetime(year=2019, month=1, day=10, hour=21, minute=30),
{},
'hourly',
'/tmp/pokus.l... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_rotated(self):\n self._calibration_test(\"rotated\")",
"def test_skel_rotation_fail(self):\n cmds.file(f=1, new=1)\n cmds.mayaUSDImport(file=self.skel_file, ani=1)\n\n values = cmds.keyframe('joint1.rx', q=1, vc=1)\n self.assertNotAlmostEqual(0.0, values[-1])",
"def... | [
"0.7053024",
"0.6514648",
"0.6510062",
"0.64673233",
"0.6354083",
"0.6268674",
"0.62312365",
"0.6228066",
"0.6227956",
"0.6155046",
"0.6153381",
"0.61482006",
"0.6102702",
"0.6070507",
"0.60431606",
"0.6037593",
"0.60291284",
"0.60207057",
"0.59471196",
"0.593792",
"0.5898857... | 0.0 | -1 |
Tests of try rotation without configuration | def test_process_log_without_target_configuration(self):
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
compressors = process_log(
datetime.datetime(year=2019, month=1, day=10, hour=21, minute=30),
{'max_size': 0},
'hourly',
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_rotated(self):\n self._calibration_test(\"rotated\")",
"def test_skel_rotation_fail(self):\n cmds.file(f=1, new=1)\n cmds.mayaUSDImport(file=self.skel_file, ani=1)\n\n values = cmds.keyframe('joint1.rx', q=1, vc=1)\n self.assertNotAlmostEqual(0.0, values[-1])",
"def... | [
"0.7053024",
"0.6514648",
"0.6510062",
"0.64673233",
"0.6354083",
"0.6268674",
"0.62312365",
"0.6228066",
"0.6227956",
"0.6155046",
"0.6153381",
"0.61482006",
"0.6102702",
"0.6070507",
"0.60431606",
"0.6037593",
"0.60291284",
"0.60207057",
"0.59471196",
"0.593792",
"0.5898857... | 0.0 | -1 |
Tests of try rotation with ignore in configuration | def test_process_log_with_ignore_in_configuration(self):
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
compressors = process_log(
datetime.datetime(year=2019, month=1, day=10, hour=21, minute=30),
{'ignore': True},
'hourly',
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_rotated(self):\n self._calibration_test(\"rotated\")",
"def test_need_to_rotate_log(self):\n self.assertTrue(need_to_rotate_log(0, 20, 'daily', 15, 'daily'), 'rotate log by time')\n self.assertFalse(need_to_rotate_log(10, 20, 'daily', 15, 'hourly'), 'do not rotate log by time')\n ... | [
"0.6419533",
"0.63577354",
"0.59528947",
"0.5869784",
"0.58633524",
"0.5819878",
"0.57872254",
"0.5771617",
"0.5742969",
"0.57247704",
"0.57068",
"0.5701424",
"0.5659168",
"0.555079",
"0.5517062",
"0.5510512",
"0.54531544",
"0.5388795",
"0.53871274",
"0.5342193",
"0.53315157"... | 0.0 | -1 |
Tests of try rotation with min_size in configuration | def test_process_log_with_min_size_in_configuration(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
srcfile = Path(sandbox, 'pokus.log')
srcfile.touch()
destfile = Path(sandbox, 'ba... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _optimise_rotation(self):\n logger.info(\n f\"Minimising dimer rotation up to \"\n f'δϕ = {self.phi_tol.to(\"degrees\"):.4f}º'\n )\n\n for i in range(self._ratio_rot_iters):\n\n result = self._rotate()\n\n if (\n result == _StepRes... | [
"0.5948658",
"0.5849822",
"0.5711593",
"0.5711048",
"0.5682156",
"0.565054",
"0.563231",
"0.56153196",
"0.5595372",
"0.55438685",
"0.55225056",
"0.54687154",
"0.5414168",
"0.5409983",
"0.5369747",
"0.5347305",
"0.5310389",
"0.52922046",
"0.5289117",
"0.52687037",
"0.52551305"... | 0.54828143 | 11 |
Tests of try rotation with target and interval in configuration | def test_process_log_with_target_in_configuration(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
srcfile = Path(sandbox, 'pokus.log')
srcfile.touch()
destfile = Path(sandbox, 'back... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_arbitrary_rotation(self):\n \n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\n\t\t# (16.667%).\n for i in range(2, 7):\n \n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubi... | [
"0.6687461",
"0.6452325",
"0.6416947",
"0.62044525",
"0.6084357",
"0.5957329",
"0.5694046",
"0.56862086",
"0.56001717",
"0.556808",
"0.5566651",
"0.5540372",
"0.5497633",
"0.54841346",
"0.54720324",
"0.54684687",
"0.5468463",
"0.5463228",
"0.53882957",
"0.53821856",
"0.535683... | 0.0 | -1 |
Tests of try rotation with relative target and interval in configuration | def test_process_log_with_relative_target_in_configuration(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
srcfile = Path(sandbox, 'pokus.log')
srcfile.touch()
destfile = Path(sandb... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_arbitrary_rotation(self):\n \n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\n\t\t# (16.667%).\n for i in range(2, 7):\n \n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubi... | [
"0.6849133",
"0.66332906",
"0.64928585",
"0.63230497",
"0.621054",
"0.6208657",
"0.6164278",
"0.59979725",
"0.5994086",
"0.5906198",
"0.5899471",
"0.5757551",
"0.5706605",
"0.5610273",
"0.56079453",
"0.560449",
"0.56034946",
"0.5596018",
"0.55945164",
"0.55886596",
"0.5548625... | 0.0 | -1 |
Tests of try rotation with compress in configuration | def test_process_log_with_compress_in_configuration(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
srcfile = Path(sandbox, 'pokus.log')
srcfile.touch()
destfile = Path(sandbox, 'ba... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_compress_works(self):\n tau = 45.0\n mrate = 60.0\n Mrate = 100.0\n gain = 5\n\n tmax = 50.0\n dt = 0.2\n\n self.rule.tau = tau\n self.rule.min_rate = mrate\n self.rule.max_rate = Mrate\n self.rule.compress_rates = False\n self.rule.gain = gain\n\n self.motor.error_fct ... | [
"0.63947666",
"0.61248237",
"0.6114381",
"0.6083236",
"0.6082104",
"0.6062771",
"0.59740895",
"0.59541243",
"0.5930159",
"0.5895802",
"0.57862955",
"0.5755226",
"0.5731432",
"0.56462026",
"0.56308395",
"0.5578965",
"0.5572358",
"0.55638254",
"0.5525263",
"0.5516631",
"0.55155... | 0.62119424 | 1 |
Tests of try rotation with exec_pre in configuration | def test_process_log_with_exec_pre_in_configuration(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stderr', new=io.StringIO()) as fake_stderr:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
stream_handler = logging.Str... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_relaunch_deployment_run(self):\n pass",
"def test_retest_deployment_run(self):\n pass",
"def test_retry_run(self):\n pass",
"def test_pre_hooks(self):\n os.makedirs('/tmp/localhost/pacha_pre')\n touch_script = open('/tmp/localhost/pacha_pre/foo.sh', 'w')\n t... | [
"0.62804943",
"0.62302554",
"0.5996128",
"0.59816766",
"0.58999544",
"0.57469875",
"0.5720267",
"0.5683897",
"0.5645453",
"0.55972165",
"0.5577958",
"0.55499387",
"0.54937345",
"0.54752177",
"0.5470032",
"0.53967464",
"0.5395424",
"0.53703004",
"0.5367641",
"0.53619397",
"0.5... | 0.6106966 | 2 |
Tests of try rotation with exec_post in configuration | def test_process_log_with_exec_post_in_configuration(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stderr', new=io.StringIO()) as fake_stderr:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
stream_handler = logging.St... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_relaunch_deployment_run(self):\n pass",
"def test_retest_deployment_run(self):\n pass",
"def test_retry_run(self):\n pass",
"def test_redeploy(self):\n pass",
"def test_encrypt_creates_and_restores_backup(\n self,\n mock_os,\n mock_shutil,\n ... | [
"0.642584",
"0.63849103",
"0.63836694",
"0.5834038",
"0.5756419",
"0.56373674",
"0.56172615",
"0.5577163",
"0.55671585",
"0.5550985",
"0.5545134",
"0.5540187",
"0.55376",
"0.5514732",
"0.5497733",
"0.5491249",
"0.54792863",
"0.54780215",
"0.5450571",
"0.543589",
"0.5422628",
... | 0.61695516 | 3 |
Tests of try rotation with positive pre and post exec in configuration | def test_process_log_with_pre_and_post_in_configuration(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
srcfile = Path(sandbox, 'pokus.log')
srcfile.touch()
destfile = Path(sandbox,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_need_to_rotate_log(self):\n self.assertTrue(need_to_rotate_log(0, 20, 'daily', 15, 'daily'), 'rotate log by time')\n self.assertFalse(need_to_rotate_log(10, 20, 'daily', 15, 'hourly'), 'do not rotate log by time')\n self.assertTrue(need_to_rotate_log(10, 20, 'daily', 25, None), 'rotat... | [
"0.60960656",
"0.6015227",
"0.6008511",
"0.5992133",
"0.55971855",
"0.553978",
"0.5513998",
"0.55035573",
"0.54847586",
"0.5416907",
"0.5409339",
"0.5401802",
"0.5393093",
"0.5367785",
"0.53527",
"0.53498495",
"0.5327782",
"0.53196454",
"0.5276392",
"0.5270697",
"0.52541757",... | 0.5355824 | 14 |
Tests of try rotation with target exists | def test_process_log_with_target_exists(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
srcfile = Path(sandbox, 'pokus.log')
srcfile.touch()
destfile = Path(sandbox, 'backup', 'poku... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_skel_rotation_fail(self):\n cmds.file(f=1, new=1)\n cmds.mayaUSDImport(file=self.skel_file, ani=1)\n\n values = cmds.keyframe('joint1.rx', q=1, vc=1)\n self.assertNotAlmostEqual(0.0, values[-1])",
"def check_rotation_fault(self, current_pos, target_pos):\n \n f... | [
"0.63469565",
"0.633046",
"0.5920605",
"0.58786756",
"0.58433646",
"0.58242995",
"0.57923526",
"0.5692897",
"0.5678962",
"0.5639551",
"0.55446136",
"0.5513295",
"0.5480883",
"0.5480366",
"0.5454172",
"0.5421362",
"0.5417596",
"0.54171485",
"0.53870094",
"0.53733045",
"0.53608... | 0.5124146 | 41 |
Tests of try rotation with OS error while file move | def test_process_log_with_os_error_at_move(self):
with tempfile.TemporaryDirectory() as sandbox:
with mock.patch('sys.stdout', new=io.StringIO()) as fake_stdout:
with self.assertLogs() as logger:
srcfile = Path(sandbox, 'pokus.log')
srcfile.tou... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_rotatePermissionFileNotOk(self):\n log = logfile.DailyLogFile(self.name, self.dir)\n self.addCleanup(log.close)\n\n os.chmod(log.path, 0o444)\n previousFile = log._file\n log.rotate()\n self.assertEqual(previousFile, log._file)",
"def test_move_badtgzfile(self):... | [
"0.684734",
"0.6769702",
"0.67119235",
"0.6446284",
"0.6391524",
"0.6390081",
"0.6323381",
"0.6310103",
"0.62937844",
"0.6224313",
"0.6208974",
"0.6208974",
"0.61933196",
"0.619122",
"0.6079188",
"0.6045162",
"0.598325",
"0.59720737",
"0.5965603",
"0.5938034",
"0.58546984",
... | 0.6581009 | 3 |
Test get_spec_config on empty conf | def test_get_spec_config_empty(self):
spec_conf = get_spec_config({}, '')
self.assertEqual(spec_conf, {}) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_spec_config_defaults(self):\n spec_conf = get_spec_config({\n 'defaults': {\n 'foo': 'bar'\n }\n }, '')\n self.assertEqual(spec_conf, {'foo': 'bar'})",
"def test_config_spec(self):\n spec = self._gen.config_spec()\n self.assertIn('Numbe... | [
"0.76028246",
"0.7311133",
"0.72477543",
"0.7058012",
"0.69974715",
"0.69667923",
"0.68360406",
"0.6766845",
"0.67532086",
"0.6709966",
"0.6709966",
"0.66910833",
"0.66852343",
"0.6642581",
"0.6638022",
"0.6632264",
"0.66242176",
"0.661909",
"0.661713",
"0.6613062",
"0.660850... | 0.84538144 | 0 |
Test get_spec_config on conf with defaults | def test_get_spec_config_defaults(self):
spec_conf = get_spec_config({
'defaults': {
'foo': 'bar'
}
}, '')
self.assertEqual(spec_conf, {'foo': 'bar'}) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_spec_config_match(self):\n spec_conf = get_spec_config({\n 'defaults': {\n 'default_foo': 'default_bar',\n 'foo': 'bar'\n },\n 'specific': [\n {'mask': ['filenomatch'], 'foo': 'bar_nomatch'},\n {'mask':... | [
"0.77164143",
"0.7436098",
"0.7076511",
"0.7013907",
"0.6881537",
"0.6805723",
"0.678276",
"0.6729274",
"0.6729274",
"0.66931385",
"0.66794413",
"0.6565056",
"0.6563163",
"0.65287656",
"0.6503387",
"0.64884305",
"0.64868605",
"0.6484734",
"0.6454509",
"0.6409027",
"0.63939387... | 0.8287769 | 0 |
Test get_spec_config on matching conf | def test_get_spec_config_match(self):
spec_conf = get_spec_config({
'defaults': {
'default_foo': 'default_bar',
'foo': 'bar'
},
'specific': [
{'mask': ['filenomatch'], 'foo': 'bar_nomatch'},
{'mask': ['filematch'... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_config_spec(self):\n spec = self._gen.config_spec()\n self.assertIn('Number of examples', spec)\n self.assertIn('Maximum number of columns to change', spec)\n self.assertIn('Regression threshold', spec)\n self.assertIn('Prediction key', spec)",
"def test_get_spec_config_defaults(self):\n ... | [
"0.7582333",
"0.67213416",
"0.6621223",
"0.66077214",
"0.6536261",
"0.65335846",
"0.64342177",
"0.6432759",
"0.6411313",
"0.6303535",
"0.62789136",
"0.6260329",
"0.62516683",
"0.6249136",
"0.6229848",
"0.6223742",
"0.6223742",
"0.62210363",
"0.61939514",
"0.617981",
"0.615186... | 0.8165602 | 0 |
Check that given modifier name is valid one. If not raise exception based on violation. | def _isValidModifier(self, modifiers, modifierName):
if Modifiers.ILLEGAL_MODIFIER_PATTER.search(modifierName):
msg = ('Modifier named "{0}" in sheet {1} contains illegal characters. '
'Supported characters are a to z, A to Z, 0 to 9 and underscore "_". '
'Space... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def validateName(name):\r\n if not name:\r\n raise IllegalName('Name can not be an empty string.')\r\n\r\n m = _NAME_RE.match(name)\r\n\r\n if m is None or m.group(0) != name:\r\n raise IllegalName('Name has to start with a letter followed by an '\r\n 'arbitrary numb... | [
"0.64032656",
"0.63721097",
"0.6336271",
"0.62860745",
"0.62444806",
"0.6232126",
"0.6111689",
"0.6085224",
"0.60028106",
"0.59533495",
"0.5930594",
"0.59233236",
"0.5870704",
"0.58153677",
"0.5802187",
"0.5795572",
"0.57821715",
"0.5776781",
"0.5740856",
"0.5735548",
"0.5728... | 0.78125316 | 0 |
Supported functions for the user in boolean equations. | def _evalContext(self):
def xor(*args):
return sum(args) == 1
def neg(result):
return not result
context = {
'xor': xor,
'neg': neg
}
return context | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def boolean_func(experiment):",
"def true(func):\n return MultipleChoice(_text_from_func(func), Answer('True'), Answer('False'), is_code=True)",
"def __bool__(self):\n raise RuntimeError(\"Cannot evaluate CrypTensors to boolean values\")",
"def main():\n var_num = int(input(\"Please, enter the n... | [
"0.6549295",
"0.6121206",
"0.59864044",
"0.59644145",
"0.5946533",
"0.5924393",
"0.5879584",
"0.58733624",
"0.58189994",
"0.58100283",
"0.58097804",
"0.57936394",
"0.5781556",
"0.5762648",
"0.57621485",
"0.57520574",
"0.5727584",
"0.57086086",
"0.56952477",
"0.56867784",
"0.5... | 0.0 | -1 |
The process_song_data function extracts song data in JSON file format from an AWS S3 bucket(input_data), transforms data into specified tables and then loads the tables back into a designated AWS S3 bucket(output_data) in parquet file format. | def process_song_data(spark, input_data, output_data):
# get filepath to song data file
song_data = os.path.join(input_data, 'song_data/*/*/*/*.json')
#specify schema for increased performance and control
song_schema = StructType([
StructField("artist_id", StringType()),
StructField("artist... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def process_song_data(spark, input_data, output_data):\n \n # get filepath to song data file\n song_data = input_data + \"song_data/*/*/*/*.json\"\n \n # read song data file\n df = spark.read.json(song_data).dropDuplicates()\n\n # extract columns to create songs table\n global songs_table\n... | [
"0.82500315",
"0.82351744",
"0.82207996",
"0.82134485",
"0.82060736",
"0.8200832",
"0.81907237",
"0.81895614",
"0.81846154",
"0.8184577",
"0.81579006",
"0.8133783",
"0.81304675",
"0.8083736",
"0.80220705",
"0.8002966",
"0.79769325",
"0.7895738",
"0.7668537",
"0.6478855",
"0.6... | 0.804698 | 14 |
The process_log_data function extracts log data in JSON file format from an AWS S3 bucket(input_data), transforms data into specified tables and then loads the tables back into a designated AWS S3 bucket(output_data) in parquet file format. | def process_log_data(spark, input_data, output_data):
# get filepath to log data file
log_data = os.path.join(input_data, 'log_data/*/*/*.json')
# read log data file
dfl = spark.read.json(log_data)
# filter by actions for song plays
dfl = dfl.filter(dfl.page == "NextSong")
#create... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def process_log_data(spark, input_data, output_data):\n\n # get filepath to log data file\n log_data = input_data + \"log_data/2018/11/*.json\"\n\n # read log data file\n log_data_schema = StructType([\n StructField(\"artist\", StringType(), True),\n StructField(\"auth\", StringType(), Fa... | [
"0.7315748",
"0.73054594",
"0.6975627",
"0.69641143",
"0.6958745",
"0.6947524",
"0.6941278",
"0.69293684",
"0.6911164",
"0.6907852",
"0.686215",
"0.6784478",
"0.6759412",
"0.6692344",
"0.66841125",
"0.6366269",
"0.62756515",
"0.6237044",
"0.62061685",
"0.61751795",
"0.5997216... | 0.66948694 | 13 |
View function that handles inserting new comments via POST data (form submission) | def post_comment_form(request):
try:
comment, previous_version = get_comment(request)
except InvalidCommentException as e:
raise
parent_comment = comment.parent
tree_root = parent_comment.get_root()
parent_object = tree_root.content_object
if not user_can_post_comment(request, c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def comments_new():\n comment = {\n \"title\": request.form.get(\"title\"),\n \"content\": request.form.get(\"content\"),\n \"playlist_id\": ObjectId(request.form.get(\"playlist._id\")),\n }\n print(comment)\n comment_id = db.comments.insert_one(comment).inserted_id\n return red... | [
"0.7209647",
"0.7182928",
"0.70809394",
"0.70615923",
"0.7031212",
"0.70248646",
"0.70202553",
"0.6970048",
"0.6925778",
"0.69036263",
"0.68516064",
"0.68059367",
"0.6770113",
"0.6715247",
"0.6710386",
"0.67016625",
"0.6607484",
"0.66067475",
"0.6575949",
"0.65087175",
"0.649... | 0.70013684 | 7 |
View function that handles inserting new/editing previously existing comments via Ajax | def post_comment(request, send_signal=True):
# Based on variables passed in we get the comment the user is attempting to create/edit
try:
comment, previous_version = get_comment(request)
except InvalidCommentException as e:
transaction.rollback()
return JsonResponse({
'ok... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save_comments():\n potential_deal_id = int(request.form.get(\"id\"))\n action = request.form.get(\"action\")\n if action.lower() == \"none\":\n action = None\n comments = request.form.get(\"comments\")\n db_handler = DBHandler()\n db_handler.update_by_id(potential_deal_id, action, comm... | [
"0.67972344",
"0.6647041",
"0.663194",
"0.66208017",
"0.65695584",
"0.6565645",
"0.6551287",
"0.65155035",
"0.6482362",
"0.6476776",
"0.6422695",
"0.6392417",
"0.6366266",
"0.6361407",
"0.63019305",
"0.6271926",
"0.6269781",
"0.6195616",
"0.61950845",
"0.61534417",
"0.6148189... | 0.6193762 | 19 |
View function that returns the comment tree for the desired parent object. | def load_comments(request):
# TODO: Add the ability to return comment tree in JSON format.
# First we get the root of the comment tree being requested
try:
tree_root, parent_object = _get_or_create_tree_root(request)
except InvalidCommentException as e:
return JsonResponse({
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_by_parent(parent_id):\n return CommentsTreeDAO(root_id=parent_id)",
"def parent(self) -> Comment | praw.models.Submission:\n # pylint: disable=no-member\n if self.parent_id == self.submission.fullname:\n return self.submission\n\n if self.parent_id in self.submis... | [
"0.69411963",
"0.67797315",
"0.6721547",
"0.66233695",
"0.65036964",
"0.64508355",
"0.63603806",
"0.63551664",
"0.6318134",
"0.6311694",
"0.6311694",
"0.6311694",
"0.6236535",
"0.6184287",
"0.6184287",
"0.61701477",
"0.6166827",
"0.6166827",
"0.6166827",
"0.6166827",
"0.61653... | 0.5738746 | 76 |
Interpret and store the decoded json dictionary from the handshake header file. Start an empty data tracking dictionary, according to data_labels. | def __init__(self, sock, header_dict):
super().__init__(header_dict)
self.sock = sock | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _read_header(\n self, header, filename, run_check_acceptability=True, background_lsts=True\n ):\n # get telescope information\n latitude = header[\"latitude\"][()]\n longitude = header[\"longitude\"][()]\n altitude = header[\"altitude\"][()]\n self.telescope_locatio... | [
"0.5554169",
"0.5521527",
"0.53812873",
"0.5335025",
"0.5277362",
"0.5266372",
"0.5250536",
"0.52459896",
"0.5201471",
"0.5174532",
"0.5169621",
"0.5158002",
"0.5134929",
"0.5060775",
"0.5059112",
"0.5053946",
"0.50465447",
"0.50403374",
"0.50372404",
"0.50230026",
"0.5013707... | 0.0 | -1 |
Called by the GUI clock at regular intervals according to self.sampling_rate. Send a data request signal to the Arduino and interpret the json output. Return the entire history of all recorded data (regardless of whether or not a null value was read or if the data series are not 'checked' in the GUI). | def sample(self):
print("sampling bluetooth arduino")
self.sock.send(b'B')
data = b''
'''while True:
data += self.sock.recv(1024)
if data.endswith(b'\n'):
break
'''
#self.sock.settimeout(2)
try:
while True:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def recive_data(self):\n # read all available data\n while self.ser.inWaiting() > self.INPUT_DATA_SIZE+1:\n data = array.array('c')\n # search the header\n data.append(self.ser.read(1))\n while data[0] != chr(1):\n data[0] = self.ser.read(1)\... | [
"0.6700092",
"0.6360538",
"0.6166242",
"0.60464233",
"0.6038091",
"0.6023963",
"0.60063523",
"0.5908595",
"0.58683914",
"0.5861097",
"0.58507204",
"0.5833523",
"0.5832018",
"0.57664955",
"0.57027274",
"0.5638211",
"0.5628629",
"0.5615999",
"0.56110036",
"0.56060934",
"0.55733... | 0.6273694 | 2 |
Determines if a given datetime.datetime is aware. | def is_aware(value):
return value.tzinfo is not None and value.tzinfo.utcoffset(value) is not None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_aware(value: datetime) -> bool:\n\n return value.utcoffset() is not None",
"def test_make_datetime_aware(settings):\n # Set the TIME_ZONE in the settings.\n settings.TIME_ZONE = \"America/New_York\"\n\n # Calling make_datetime_aware() returns a timezone-aware datetime referring\n # to the m... | [
"0.7423152",
"0.6706246",
"0.656491",
"0.65267324",
"0.6137775",
"0.60896856",
"0.6019291",
"0.59568536",
"0.57755363",
"0.57708514",
"0.5679119",
"0.5660917",
"0.56022364",
"0.55941117",
"0.5527686",
"0.55162454",
"0.54947275",
"0.5432787",
"0.5420078",
"0.5379313",
"0.53406... | 0.6891435 | 1 |
For date and time values shows how many seconds, minutes or hours ago compared to current timestamp returns representing string. | def naturaltime(value):
if not isinstance(value, date): # datetime is a subclass of date
return value
now = datetime.now(utc if is_aware(value) else None)
if value < now:
delta = now - value
if delta.days != 0:
return 'hace %(delta)s' % {'delta': defaultfilters.timesince... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def humanize_ts(timestamp=False):\n now = datetime.now()\n diff = now - datetime.fromtimestamp(timestamp)\n second_diff = diff.seconds\n day_diff = diff.days\n\n if day_diff < 0:\n return ''\n\n if day_diff == 0:\n if second_diff < 10:\n return \"just now\"\n if se... | [
"0.7112443",
"0.70603174",
"0.6994772",
"0.6923336",
"0.69147646",
"0.689994",
"0.68880904",
"0.68262726",
"0.6814668",
"0.6745085",
"0.67083603",
"0.6695963",
"0.66525495",
"0.6583381",
"0.6518557",
"0.65105355",
"0.6455629",
"0.63705647",
"0.62662446",
"0.6263275",
"0.62592... | 0.64102644 | 17 |
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