Contributing

Thank you for your interest in contributing to GGE!

Development Setup

1. Clone the repository:

   git clone https://github.com/AndreaRubbi/GGE.git
   cd GGE
   

2. Install in development mode:

   pip install -e ".[dev]"
   

3. Install pre-commit hooks:

   pip install pre-commit
   pre-commit install
   

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=gge

# Run specific test file
pytest tests/test_metrics.py

# Run with verbose output
pytest -v

Code Style

We use: - black for code formatting - isort for import sorting - flake8 for linting - mypy for type checking

# Format code
black src/ tests/
isort src/ tests/

# Check linting
flake8 src/ tests/

# Type check
mypy src/

Pull Request Process

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass
6. Update documentation if needed
7. Commit your changes (git commit -m 'Add amazing feature')
8. Push to your branch (git push origin feature/amazing-feature)
9. Open a Pull Request

Adding New Metrics

1. Create a new metric class in src/gge/metrics/:

from gge.metrics.base_metric import BaseMetric, MetricResult

class MyNewMetric(BaseMetric):
    name = "my_metric"
    higher_is_better = True  # or False

    def _compute_per_gene(self, real, generated):
        # Implement per-gene computation
        return per_gene_values

1. Add to src/gge/metrics/__init__.py
2. Add tests in tests/test_metrics.py
3. Update documentation

Adding New Visualizations

1. Add method to src/gge/visualization/visualizer.py
2. Add tests in tests/test_visualization.py
3. Update documentation

Reporting Issues

When reporting issues, please include: - GGE version (gge --version) - Python version - Operating system - Minimal reproducible example - Full error traceback

Questions?

Feel free to open an issue or discussion on GitHub!