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Development Workflow

This guide outlines the development workflow and best practices for contributing to the MLContext project.

🚀 Local Development Setup​

Initial Setup​

  1. Clone repositories: Get DAGGH frontend and ML service
  2. Install dependencies: Run setup scripts for each service
  3. Configure environment: Set up Supabase and API keys
  4. Start services: Launch development servers

Daily Development​

  1. Pull latest changes: Sync with main branch
  2. Create feature branch: Use descriptive naming
  3. Development cycle: Code, test, commit, repeat
  4. Submit for review: Create pull request

🔧 Service Development​

Frontend (DAGGH)​

  • Development server: pnpm dev on port 3000
  • Type checking: pnpm type-check
  • Linting: pnpm lint
  • Testing: pnpm test

ML Service​

  • Development server: python -m uvicorn main:app --reload
  • Testing: pytest
  • Type checking: mypy
  • Code formatting: black and isort

Documentation​

  • Development server: yarn start in docs directory
  • Build: yarn build
  • Link checking: yarn check-links

📝 Code Standards​

TypeScript/JavaScript​

  • Use TypeScript for all new code
  • Follow ESLint configuration
  • Write meaningful variable names
  • Include JSDoc comments for functions

Python​

  • Follow PEP 8 guidelines
  • Use type hints
  • Write docstrings for functions
  • Include unit tests

Documentation​

  • Use clear, concise language
  • Include code examples
  • Update with all changes
  • Test all links and examples

🧪 Testing Strategy​

Test Types​

  • Unit tests: Individual function testing
  • Integration tests: Service interaction testing
  • E2E tests: Full user workflow testing
  • Performance tests: Load and response time testing

Test Requirements​

  • All new features require tests
  • Maintain test coverage above 80%
  • Run tests before submitting PR
  • Update tests with changes

🔄 Git Workflow​

Branch Naming​

  • feature/description: New features
  • fix/description: Bug fixes
  • docs/description: Documentation updates
  • refactor/description: Code refactoring

Commit Messages​

  • Use conventional commit format
  • Include clear, descriptive messages
  • Reference issues when applicable
  • Keep commits focused and atomic

Pull Request Process​

  1. Create draft PR early
  2. Include comprehensive description
  3. Link related issues
  4. Request appropriate reviewers
  5. Address feedback promptly

📋 Definition of Done​

Feature Completion​

  • Code implemented and tested
  • Documentation updated
  • Tests passing
  • Code reviewed and approved
  • No linting errors
  • Performance impact assessed

Bug Fix Completion​

  • Root cause identified
  • Fix implemented and tested
  • Regression tests added
  • Documentation updated if needed
  • Verification in staging environment

🚀 Release Process​

Pre-Release​

  1. Feature freeze: Stop new feature development
  2. Testing phase: Comprehensive testing across services
  3. Documentation review: Ensure all docs are current
  4. Performance validation: Check system performance

Release​

  1. Version bump: Update version numbers
  2. Tag release: Create git tags
  3. Deploy to staging: Validate in staging environment
  4. Deploy to production: Coordinated production deployment
  5. Monitor: Watch for issues post-deployment

Post-Release​

  1. Monitor metrics: Track system performance
  2. Gather feedback: Collect user feedback
  3. Plan next iteration: Prepare for next development cycle

🔍 Quality Assurance​

Code Quality​

  • Regular code reviews
  • Automated linting and formatting
  • Static analysis tools
  • Performance profiling

Documentation Quality​

  • Regular content reviews
  • Link validation
  • Example testing
  • User feedback incorporation

📊 Monitoring and Metrics​

Development Metrics​

  • Pull request velocity
  • Code review turnaround time
  • Test coverage trends
  • Bug resolution time

Performance Metrics​

  • Application response times
  • ML model performance
  • Database query performance
  • User experience metrics

🤝 Team Collaboration​

Communication​

  • Daily standup meetings
  • Weekly sprint planning
  • Async updates in shared channels
  • Regular retrospectives

Knowledge Sharing​

  • Code review discussions
  • Technical documentation
  • Team learning sessions
  • Cross-training opportunities

Questions about the workflow? Check our Troubleshooting Guide or reach out to the team!