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Contributing to AI Backtest Engine

Thank you for your interest in contributing! This document provides guidelines for contributing to this project.

Getting Started

  1. Fork the repository
  2. Clone your fork: git clone https://github.com/your-username/ai-backtest-engine.git
  3. Create a feature branch: git checkout -b feature/your-feature-name
  4. Install dependencies: pip install -r requirements.txt

Development Guidelines

Code Style

  • Follow PEP 8 conventions
  • Use type hints for function signatures
  • Include docstrings for all public classes and methods (NumPy style)
  • Keep functions focused and under 50 lines where practical

Financial Data Handling

  • Never use random train/test splits — always use TimeSeriesSplit or temporal splits
  • Validate that no look-ahead bias exists in features or signals
  • Include realistic transaction costs in all backtest evaluations
  • Document any assumptions about data frequency or market hours

Testing

  • Write tests for new features: pytest tests/
  • Ensure all existing tests pass before submitting
  • Include edge cases (empty data, single row, missing columns)

Commit Messages

Use conventional commit format:

feat: add new feature description
fix: correct bug in module
docs: update documentation
test: add tests for module
refactor: restructure code without behavior change

Pull Request Process

  1. Update documentation if you've changed APIs
  2. Add or update tests for your changes
  3. Ensure all tests pass: pytest tests/ -v
  4. Update requirements.txt if you've added dependencies
  5. Submit a pull request with a clear description of changes

Reporting Issues

  • Use GitHub Issues for bug reports and feature requests
  • Include steps to reproduce for bugs
  • Include Python version and OS information

License

By contributing, you agree that your contributions will be licensed under the MIT License.