README.md

metadata

title: Python C Extension Generator
app_file: app.py
sdk: gradio
sdk_version: 6.14.0
license: mit
emoji: 🐉
colorFrom: blue
colorTo: green
short_description: High-performance Python C Extension generator from Python.
pinned: true
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/67caf50af30e4fe450042ac4/7DVx6daYTcVfiqhfRHCI9.png

Python C Extension code generator

A Gradio app that provides an interactive interface for users to input Python code and generate C extension code

Optionally, a compile and eval stage can be activated for local deployments to compare its performance against the original Python code.

Always review the generated codes before running them, as they will be executed in your local environment and may contain code that could be harmful or unwanted.

AI-generated code may contain errors or unsafe practices, so it's crucial to thoroughly review and test on a sandboxed environment any code before using it in a production environment.

Never run code generated by AI models without understanding its implications and ensuring it adheres to your security and safety standards.

Disclaimer: This App and Notebook are provided for educational purposes only. Use it at your own risk.

Installation

• Install the required Python dependencies:

  pip install -r requirements.txt
  

• Or, if you prefer Pipenv:

  pipenv install
  

Configuration

The app reads configuration from environment variables and from a .env file if present.

• MODELS: Colon-separated list of models to expose in the dropdown.

  • Examples:

    bash:

    export MODELS="gpt-5.1-codex-mini:gpt-5.4-mini"
    

    powershell:

    $env:MODELS = "gpt-5.1-codex-mini:gpt-5.4-mini"
    

  If not set, the app defaults to gpt-5.1-codex-mini and gpt-5.4-mini.

• COMPILE_STAGE: Set to true, 1, or yes to enable the compile and test stage.

  • Examples:

    bash:

    export COMPILE_STAGE=true
    

    powershell:

    $env:COMPILE_STAGE = "true"
    

Running locally

• Run the app locally with:

  python app.py
  

• For autoreload during development, use the Gradio CLI:

  gradio app.py
  

Gradio app overview

In this image, you can see the Gradio app dashboard whose main sections are described below.

Image: Gradio app dashboard with default example hello world code loaded. (compile output redacted for privacy)

Sections:

• Dropdown selectors and input fields:

  • Module name input:

    A text input field where users can specify the name of the C extension module to be generated.

    That name will be used to create the C extension file <module_name>.c and the setup.py file required to compile the extension.

    That name will also be used to import the compiled module as usual in Python:

    import <module_name>
    

    Or

    from <module_name> import <function_name>
    

  • Model selector:

    A dropdown menu to select the model used for code generation.

    The available options are taken from the MODELS environment variable if set. Otherwise the app defaults to gpt-5.1-codex-mini and gpt-5.4-mini.

  • Platform selector:

    A dropdown menu to select the target platform for the generated C extension.

    This affects how the app frames the prompt for the model and ensures the generated code targets the selected platform (Windows or Linux).

  • Examples selector:

    A list of ready-made Python examples to load into the input field.

    Built-in examples include Hello world, Sum array, Fibonacci, Leibniz pi, and Max subarray sum.

• Text input areas:

  These areas are all editable, including those filled with generated code by the model. This allows users to modify and experiment with the code as needed.

  • Python code: A text area where users can input their Python code.

    We are creating an importable module not an executable program so the code to be optimized must contain only declarations such as DEF or CLASS.

  • C extension code:

    A text area that displays the generated C extension code.

  • Compilation code:

    A text area that shows the generated setup.py code. This file is required to compile the C extension.

  • Test compare code:

    A text area that provides example code to run the compiled C extension.

• Output areas:

  These are non-editable areas that display the results of various operations.

  • C Extension result: (Only with Compile Stage Enabled)

    A text area that displays the output of the C extension code build.

    Beware that this area can contain a large amount of text including warnings during the compilation process and sensible information about the local environment, like: paths, Python version, etc may be included.

    Redact that information if you plan to share the output.

  • Test result: (Only with Compile Stage Enabled)

    A text area that displays the output of the test code run.

• Buttons:

  • Generate extension code:

    A button that triggers the generation of the C extension code from the provided Python code.

    It will call the model to generate the C code, the setup.py file and the test code, filling the corresponding text areas automatically.

  • Compile extension: (Only with Compile Stage Enabled)

    A button that compiles the generated C extension using the provided setup.py file. It will create the extension C file, <module_name>.c, and the setup.py file in the local folder, then it will run the compilation command and build the C extension, <module_name>.<arch_info>.pyd.
    arch_info represents architecture info the extension has been compiled for:

    • hello_world.cp313-win_amd64.pyd: CPython 3.13 + Windows + Amd64 Architecture.

    Always review the setup.py code before running it, as it will be executed in your local environment and may contain code that could be harmful or unwanted.

    Also review the generated C code, as it will be compiled and executed in your local environment and may contain code that could be harmful or unwanted.

    It will display the compilation output in the "C Extension result" area.

  • Test code: (Only with Compile Stage Enabled)

    A button that executes the test code to compare the performance of the original Python code and the generated C extension.

    Always review the test code before running it, as it will be executed in your local environment and may contain code that could be harmful or unwanted.

    Will save the test code provided in the "Test compare code" into the usage_example.py file and execute it, showing the output in the "Test result" area.

Notebook

The notebooks folder contains an example notebook demonstrating the usage and workflow of the Python C Extension Generator app.

It provides a step-by-step, interactive overview for users who prefer a notebook-based approach.

TO DO

• Add an Anthropic Claude based optimizer