Contributing to PyTorch Graph

We welcome contributions to PyTorch Graph! This document provides guidelines for contributing to the project.

Getting Started

  1. Fork the repository on GitHub

  2. Clone your fork locally:

    git clone https://github.com/your-username/pytorch-graph.git
cd pytorch-graph

  3. Install in development mode:

    pip install -e .[dev]

  4. Create a new branch for your feature:

    git checkout -b feature/your-feature-name

Development Setup

Install development dependencies:

pip install -e .[dev]

This installs: * The package in editable mode * Development dependencies (testing, linting, etc.) * Documentation tools

Running Tests

Run the test suite:

pytest

Run with coverage:

pytest --cov=pytorch-graph

Code Quality

We use several tools to maintain code quality:

Linting: .. code-block:: bash

flake8 pytorch-graph/ black pytorch-graph/ isort pytorch-graph/

Type checking: .. code-block:: bash

mypy pytorch-graph/

Format code: .. code-block:: bash

black pytorch-graph/ isort pytorch-graph/

Building Documentation

Build documentation locally:

cd docs
make html

View documentation:

cd docs
make serve

Then open http://localhost:8000 in your browser.

Types of Contributions

Bug Reports

When reporting bugs, please include:

  • Python version

  • PyTorch version

  • Operating system

  • Minimal code example that reproduces the issue

  • Expected vs actual behavior

  • Error messages and stack traces

Feature Requests

For feature requests, please:

  • Check existing issues first

  • Provide a clear description of the feature

  • Explain the use case and benefits

  • Consider implementation complexity

Code Contributions

We welcome contributions for:

  • Bug fixes

  • New features

  • Documentation improvements

  • Performance optimizations

  • Test coverage improvements

Pull Request Process

  1. Create a feature branch from the main branch

  2. Make your changes following our coding standards

  3. Add tests for new functionality

  4. Update documentation if needed

  5. Run the test suite and ensure all tests pass

  6. Submit a pull request with a clear description

Pull Request Guidelines

  • Clear title and description

  • Reference related issues

  • Include tests for new features

  • Update documentation as needed

  • Keep changes focused (one feature per PR)

  • Follow coding standards

Coding Standards

  • Follow PEP 8 style guidelines

  • Use type hints where appropriate

  • Write docstrings for all public functions

  • Add tests for new functionality

  • Keep functions focused and small

  • Use meaningful variable names

Documentation Standards

  • Write clear, concise docstrings

  • Include examples in docstrings

  • Update README.md for significant changes

  • Add documentation for new features

  • Use proper Sphinx formatting

Testing Guidelines

  • Write tests for all new functionality

  • Aim for high test coverage

  • Test edge cases and error conditions

  • Use descriptive test names

  • Keep tests simple and focused

Release Process

Releases are managed by maintainers:

  1. Update version numbers

  2. Update CHANGELOG.md

  3. Create release notes

  4. Tag the release

  5. Build and upload to PyPI

Community Guidelines

  • Be respectful and inclusive

  • Help others learn and grow

  • Provide constructive feedback

  • Follow the code of conduct

  • Welcome newcomers

Getting Help

  • GitHub Issues: For bug reports and feature requests

  • GitHub Discussions: For questions and general discussion

  • Documentation: Check the docs for usage examples

  • Code Examples: Look at the demo scripts

Recognition

Contributors will be recognized in:

  • CONTRIBUTORS.md file

  • Release notes

  • Documentation acknowledgments

Thank you for contributing to PyTorch Graph! 🚀