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Contributing to MLContext

We welcome contributions to the MLContext project! This guide will help you get started with contributing to our collaborative movie recommendation platform.

📋 Getting Started​

Before contributing, please:

  1. Read our Project Overview
  2. Follow the Getting Started Guide
  3. Review our development workflow below

🛠️ Development Setup​

Prerequisites​

  • Node.js 18+ and pnpm
  • Python 3.9+
  • Git
  • Supabase account

Fork and Clone​

  1. Fork the repository on GitHub
  2. Clone your fork locally
  3. Add upstream remote for staying in sync

Environment Setup​

  1. Copy environment templates
  2. Configure Supabase connection
  3. Set up TMDB API keys
  4. Install dependencies for all services

📝 Contribution Guidelines​

Code Style​

  • Follow existing code patterns
  • Use TypeScript for frontend development
  • Follow Python PEP 8 for ML service
  • Run linters before submitting

Documentation​

  • Update documentation for new features
  • Include code examples where helpful
  • Follow our documentation structure
  • Test all documentation links

Testing​

  • Write tests for new features
  • Ensure existing tests pass
  • Include integration tests where appropriate
  • Document testing procedures

🔄 Development Workflow​

Branch Strategy​

  1. Create feature branches from main
  2. Use descriptive branch names
  3. Keep branches focused and small
  4. Regular rebasing to stay current

Pull Request Process​

  1. Create draft PR early for feedback
  2. Include clear description and context
  3. Link related issues
  4. Request reviews from relevant team members
  5. Address feedback promptly

Review Process​

  • All changes require review
  • Focus on code quality and architecture
  • Consider performance implications
  • Verify documentation updates

🧪 Testing Strategy​

Frontend (DAGGH)​

  • Unit tests with Jest
  • Component tests with React Testing Library
  • E2E tests with Playwright
  • Visual regression tests

ML Service​

  • Unit tests with pytest
  • Integration tests for API endpoints
  • ML model validation tests
  • Performance benchmarks

Documentation​

  • Link validation
  • Example code verification
  • Spelling and grammar checks
  • Accessibility validation

🚀 Release Process​

Version Management​

  • Semantic versioning for all components
  • Coordinated releases across services
  • Clear changelog maintenance
  • Tag releases appropriately

Deployment​

  • Staging environment validation
  • Production deployment checklist
  • Rollback procedures
  • Monitoring and alerts

💬 Communication​

Where to Get Help​

  • GitHub Discussions for questions
  • Issues for bug reports
  • Pull requests for feature discussions
  • Regular team sync meetings

Code of Conduct​

  • Be respectful and inclusive
  • Provide constructive feedback
  • Help newcomers get started
  • Celebrate contributions

🎯 Contribution Areas​

Frontend Development​

  • User interface improvements
  • Performance optimizations
  • Accessibility enhancements
  • Mobile responsiveness

Machine Learning​

  • Algorithm improvements
  • Performance optimizations
  • New recommendation features
  • Data pipeline enhancements

Documentation​

  • Content improvements
  • Example additions
  • Tutorial creation
  • Translation efforts

DevOps​

  • Infrastructure improvements
  • CI/CD pipeline enhancements
  • Monitoring and logging
  • Security improvements

📚 Resources​

Ready to contribute? Start by checking out our open issues or proposing a new feature!