Uploaded source files

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc

app.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# # Perl to Python Code Generator
+# 
+# The requirement: use a Frontier model to generate high performance Python code from Perl code
+# 
+
+# In[ ]:
+
+
+#get_ipython().system('pip install -q transformers huggingface_hub')
+
+
+# In[ ]:
+
+
+# imports
+
+import os
+import io
+import sys
+from dotenv import load_dotenv
+from openai import OpenAI
+import google.generativeai
+import anthropic
+from IPython.display import Markdown, display, update_display
+import gradio as gr
+import subprocess
+import json
+#for Hugging face end points
+from huggingface_hub import login, InferenceClient
+from transformers import AutoTokenizer
+
+
+# In[ ]:
+
+
+# environment
+
+load_dotenv(override=True)
+os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')
+os.environ['ANTHROPIC_API_KEY'] = os.getenv('ANTHROPIC_API_KEY', 'your-key-if-not-using-env')
+os.environ['HF_TOKEN'] = os.getenv('HF_TOKEN', 'your-key-if-not-using-env')
+##for connecting to HF End point
+hf_token = os.environ['HF_TOKEN']
+login(hf_token, add_to_git_credential=True)
+
+
+# In[ ]:
+
+
+# initialize
+# NOTE - option to use ultra-low cost models by uncommenting last 2 lines
+
+openai = OpenAI()
+claude = anthropic.Anthropic()
+OPENAI_MODEL = "gpt-4o"
+CLAUDE_MODEL = "claude-3-5-sonnet-20240620"
+
+# Want to keep costs ultra-low? Uncomment these lines:
+#OPENAI_MODEL = "gpt-4o-mini"
+#CLAUDE_MODEL = "claude-3-haiku-20240307"
+
+#To access open source models from Hugging face end points
+code_qwen = "Qwen/CodeQwen1.5-7B-Chat"
+code_gemma = "google/codegemma-7b-it"
+CODE_QWEN_URL = "https://u9pv0u7a6uxrjubt.us-east-1.aws.endpoints.huggingface.cloud" #Paste your end point URL from Hugging face
+CODE_GEMMA_URL = "https://c5hggiyqachmgnqg.us-east-1.aws.endpoints.huggingface.cloud" #Paste your end point URL from Hugging face
+
+
+# In[ ]:
+
+
+system_message = "You are an assistant that reimplements Perl scripts code into a high performance Python for a Windows 11 PC. "
+system_message += "Respond only with Python code; use comments sparingly and do not provide any explanation other than occasional comments preceded by a # tag."
+system_message += "The Python response needs to produce an identical output in the fastest possible time."
+
+
+# In[ ]:
+
+
+def user_prompt_for(perl):
+    user_prompt = "Rewrite this Perl scripts code in Python with the fastest possible implementation that produces identical output in the least time. "
+    user_prompt += "Respond only with Python code; do not explain your work other than a few comments. "
+    user_prompt += "Pay attention to number types to ensure no int overflows. Remember to #include all necessary python libraries as needed,\
+    such as requests, os, json etc.\n\n"
+    user_prompt += perl
+    return user_prompt
+
+
+# In[ ]:
+
+
+def messages_for(perl):
+    return [
+        {"role": "system", "content": system_message},
+        {"role": "user", "content": user_prompt_for(perl)}
+    ]
+
+
+# In[ ]:
+
+
+# write to a file
+
+def write_output(python, file_path):
+    # Get the base filename from the path
+    base_name = os.path.basename(file_path)
+    filename = os.path.splitext(base_name)[0]
+    code = python.replace("```python","").replace("```","")
+    output_file = f"{filename}.py"
+    with open(output_file, "w") as f:
+        f.write(code)
+    return output_file
+
+
+# In[ ]:
+
+
+def stream_gpt(perl, file_path):    
+    stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for(perl), stream=True)
+    reply = ""
+    for chunk in stream:
+        fragment = chunk.choices[0].delta.content or ""
+        reply += fragment
+        cleaned_reply = reply.replace('```python\n','').replace('```','')
+        yield cleaned_reply, None
+    yield cleaned_reply, write_output(cleaned_reply, file_path)
+        
+
+
+# In[ ]:
+
+
+def stream_claude(perl, file_path):
+    result = claude.messages.stream(
+        model=CLAUDE_MODEL,
+        max_tokens=2000,
+        system=system_message,
+        messages=[{"role": "user", "content": user_prompt_for(perl)}],
+    )
+    reply = ""
+    with result as stream:
+        for text in stream.text_stream:
+            reply += text
+        cleaned_reply = reply.replace('```python\n','').replace('```','')
+        yield cleaned_reply, None
+    yield cleaned_reply, write_output(cleaned_reply, file_path)
+
+
+# In[ ]:
+
+
+def stream_code_qwen(perl, file_path):
+    tokenizer = AutoTokenizer.from_pretrained(code_qwen)
+    messages = messages_for(perl)
+    text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    client = InferenceClient(CODE_QWEN_URL, token=hf_token)
+    stream = client.text_generation(text, stream=True, details=True, max_new_tokens=3000)
+    result = ""
+    for r in stream:
+        result += r.token.text
+        cleaned_reply = result.replace('```python\n','').replace('```','')
+        yield cleaned_reply, None
+    yield cleaned_reply, write_output(cleaned_reply, file_path)
+
+
+# In[ ]:
+
+
+def generate(perl_script, model, file_path):
+    if model=="GPT":
+        for result, file in stream_gpt(perl_script, file_path):
+            yield result, file
+        yield result, file
+    elif model=="Claude":
+        for result, file in stream_claude(perl_script, file_path):
+            yield result, file
+        yield result, file
+    elif model=="CodeQwen":
+        for result, file in stream_code_qwen(perl_script, file_path):
+            yield result, file
+        yield result, file
+    else:
+        raise ValueError("Unknown model")
+
+
+# In[ ]:
+
+
+def execute_perl(perl_code):
+
+    import subprocess
+    #print(perl_file)
+    #perl_path = r"E:\Softwares\Perl\perl\bin\perl.exe"
+    # Run Perl script from Jupyter Lab
+    result = subprocess.run(["perl", '-e', perl_code], capture_output=True, text=True)
+
+    # Return the output of the Perl script
+    return result.stdout
+    
+
+
+# In[ ]:
+
+
+def execute_python(code):
+    try:
+        output = io.StringIO()
+        sys.stdout = output
+        exec(code)
+    finally:
+        sys.stdout = sys.__stdout__
+    return output.getvalue()
+
+
+# In[ ]:
+
+
+css = """
+.perl {background-color: #093645;}
+.python {background-color: #0948;}
+"""
+
+force_dark_mode = """
+function refresh() {
+    const url = new URL(window.location);
+    if (url.searchParams.get('__theme') !== 'dark') {
+        url.searchParams.set('__theme', 'dark');
+        window.location.href = url.href;
+    }
+}
+"""
+
+
+# In[ ]:
+
+
+with gr.Blocks(css=css, js=force_dark_mode) as ui:
+
+    gr.HTML("<h2 style='text-align: center; color: white;'> PERL to Python Code Generator</h2>")
+    with gr.Row(scale=0, equal_height=True):
+        model = gr.Dropdown(["GPT", "Claude", "CodeQwen"], label="Select model", value="GPT")
+        perl_file = gr.File(label="Upload Perl Script:")
+        convert = gr.Button("Convert to Python")
+        file_output = gr.File(label="Download Python script", visible=False)
+    with gr.Row():
+        perl_script = gr.Textbox(label="Perl Script:")
+        python_script = gr.Textbox(label="Converted Python Script:")        
+    with gr.Row():
+        perl_run = gr.Button("Run PERL")
+        python_run = gr.Button("Run Python")
+    with gr.Row():
+        perl_out = gr.TextArea(label="PERL Result:", elem_classes=["perl"])
+        python_out = gr.TextArea(label="Python Result:", elem_classes=["python"])
+    with gr.Row():        
+        clear_button = gr.Button("Clear")
+    
+    def extract_perl_code(file):
+        if file is None:
+            return "No file uploaded."
+        with open(file.name, "r", encoding="utf-8") as f:
+            perl_code = f.read()
+        return perl_code
+
+    convert.click(extract_perl_code, inputs=[perl_file], outputs=[perl_script]).then(
+        generate, inputs=[perl_script, model, perl_file], outputs=[python_script, file_output]).then(
+        lambda file_output: gr.update(visible=True), inputs=[file_output], outputs=[file_output]
+    )
+
+    perl_run.click(execute_perl, inputs=[perl_script], outputs=[perl_out])
+    python_run.click(execute_python, inputs=[python_script], outputs=[python_out]) 
+
+    def clear_all():
+        return None, "", "", gr.update(visible=False), "", ""
+
+    clear_button.click(
+        clear_all,
+        outputs=[perl_file, perl_script, python_script, file_output, perl_out, python_out]
+    )
+
+ui.launch(inbrowser=True)
+
+
+# In[ ]:
+
+
+
+

requirements.txt

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+openai
+google-generativeai
+anthropic
+gradio
+python-dotenv
+transformers
+huggingface_hub
+

squares.pl

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+use Time::HiRes qw(time);  # More precise timing
+
+$start_time = time();
+
+@numbers = (1, 2, 3, 4, 5);
+@squares = ();
+
+$i = 0;
+while ($i < scalar(@numbers)) {
+    $num = $numbers[$i];
+
+    $square = 0;
+    $k = 0;
+    while ($k < $num) {
+        $square = $square + $num;
+        $k = $k + 1;
+    }
+
+    push(@squares, $square);
+    $i = $i + 1;
+}
+
+$j = 0;
+print "Squares:\n";
+while ($j < scalar(@squares)) {
+    print $squares[$j], "\n";
+    $j = $j + 1;
+}
+
+$end_time = time();
+$duration = $end_time - $start_time;
+
+# Print with 6 decimal places
+printf("Execution Time: %.6f seconds\n", $duration);