Contributing to RL-IDS

We welcome contributions from the community! This document provides guidelines for contributing to the RL-IDS Adaptive System.

Quick Start

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and add tests
4. Run the test suite: pytest tests/ -v --cov=rl_ids
5. Update documentation if needed
6. Submit a pull request

Development Setup

Prerequisites

• Python 3.8+
• Git
• Docker (optional)

Local Development

# Clone your fork
git clone https://github.com/yashpotdar-py/rl-ids.git
cd rl-ids

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/Mac
# or
venv\Scripts\activate     # Windows

# Install development dependencies
pip install -r requirements-dev.txt

# Install pre-commit hooks
pre-commit install

Testing

Running Tests

# Run all tests
pytest tests/ -v

# Run with coverage
pytest tests/ -v --cov=rl_ids --cov-report=html

# Run specific test categories
pytest tests/unit/ -v
pytest tests/integration/ -v

Writing Tests

• Place unit tests in tests/unit/
• Place integration tests in tests/integration/
• Follow the naming convention: test_*.py
• Use descriptive test names: test_dqn_agent_training_convergence

Code Style

We use several tools to maintain code quality:

# Format code
black rl_ids/ tests/
isort rl_ids/ tests/

# Type checking
mypy rl_ids/

# Linting
flake8 rl_ids/ tests/

Style Guidelines

• Follow PEP 8 for Python code style
• Use type hints for all public functions
• Write docstrings for modules, classes, and functions
• Keep line length under 88 characters (Black default)

Documentation

Building Documentation

# Install documentation dependencies
pip install mkdocs-material

# Serve locally with hot reload
cd docs/
mkdocs serve

# Build static documentation
mkdocs build

Documentation Guidelines

• Update relevant documentation for any API changes
• Add new tutorials for significant features
• Keep examples up-to-date and tested
• Use clear, concise language

Bug Reports

When reporting bugs, please include:

1. Environment Information
2. Python version
3. Operating system

4. Package versions (pip freeze)

5. Reproduction Steps

6. Minimal code example
7. Expected vs. actual behavior

8. Error messages and stack traces

9. Additional Context

10. Configuration files
11. Log outputs
12. Screenshots (if applicable)

Feature Requests

For new features:

1. Check existing issues to avoid duplicates
2. Describe the problem the feature would solve
3. Propose a solution or implementation approach
4. Consider backwards compatibility

Pull Request Process

Before Submitting

• [ ] Tests pass: pytest tests/ -v
• [ ] Code is formatted: black rl_ids/ tests/
• [ ] Imports are sorted: isort rl_ids/ tests/
• [ ] Type checks pass: mypy rl_ids/
• [ ] Documentation is updated
• [ ] CHANGELOG.md is updated

Pull Request Template

## Description
Brief description of changes

## Type of Change
- [ ] Bug fix
- [ ] New feature
- [ ] Breaking change
- [ ] Documentation update

## Testing
- [ ] New tests added
- [ ] All tests pass
- [ ] Manual testing completed

## Checklist
- [ ] Code follows style guidelines
- [ ] Self-review completed
- [ ] Documentation updated
- [ ] CHANGELOG.md updated

Architecture Guidelines

Code Organization

rl_ids/
├── agents/          # RL agents (DQN, etc.)
├── environments/    # Gymnasium environments
├── modeling/        # Training and evaluation
├── make_dataset.py  # Data processing
├── plots.py         # Visualization
└── config.py        # Configuration

api/
├── main.py          # FastAPI application
├── models/          # Pydantic models
├── routes/          # API endpoints
└── services/        # Business logic

Design Principles

• Modularity: Keep components loosely coupled
• Testability: Design for easy testing
• Configuration: Make components configurable
• Documentation: Document public APIs

Contribution Areas

High Priority

• Performance optimizations
• Additional RL algorithms
• Enhanced monitoring and alerting
• Security improvements

Medium Priority

• Additional dataset support
• Visualization enhancements
• API feature additions
• Documentation improvements

Welcome Contributions

• Bug fixes and improvements
• Test coverage expansion
• Example scripts and tutorials
• Typo fixes and documentation clarity

Getting Help

• Documentation: Check docs/ for comprehensive guides
• Issues: Search existing issues or create a new one
• Discussions: Use GitHub Discussions for questions
• Email: Contact maintainers for security issues

Recognition

Contributors will be recognized in: - README.md contributors section - Release notes - Documentation credits

Thank you for contributing to RL-IDS!