CONTRIBUTING.md

Contributing to Kipu API Python library

Thank you for your interest in contributing to the Kipu API Python library! This document provides guidelines and information for contributors.

🚀 Getting Started

Prerequisites

• Python 3.8 or higher
• Git
• A GitHub account

Setting Up Development Environment

1. Fork and Clone

   git clone https://github.com/Rahulkumar010/kipu-python.git
   cd kipu-python

2. Create Virtual Environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Development Dependencies

   Traditional (pip):

   pip install -e ".[dev]"

   Fast (UV - recommended): 10x faster!

   pip install uv
   uv pip install -e ".[dev]"

   Or use Makefile:

   make install-dev

4. Install Pre-commit Hooks

   pre-commit install

🧪 Development Workflow

Code Quality

try maintaining code quality standards:

• Formatting: Use black for code formatting
• Import Sorting: Use isort for import organization
• Linting: Use flake8 for code linting
• Type Checking: Use mypy for static type checking
• Security: Use bandit and safety for security checks

Running Tests

# Run all tests
make test

# Run tests with coverage
make test-cov

# Run specific test file
pytest tests/test_auth.py -v

Code Formatting

# Format code
make format

# Check formatting
make lint

Type Checking

make type-check

Security Checks

make security

📝 Contribution Guidelines

Pull Request Process

1. Create Feature Branch

   git checkout -b feature/amazing-feature

2. Make Changes

   • Write clear, concise code
   • Add tests for new functionality
   • Update documentation as needed
   • Follow existing code style

3. Commit Changes

   git add .
   git commit -m "Add amazing feature"

4. Push and Create PR

   git push origin feature/amazing-feature

Commit Message Guidelines

Use conventional commit messages:

• feat: New feature
• fix: Bug fix
• docs: Documentation changes
• style: Code style changes
• refactor: Code refactoring
• test: Test additions or modifications
• chore: Maintenance tasks

Examples:

feat: add support for new patient endpoint
fix: resolve authentication signature generation issue
docs: update README with new examples
test: add unit tests for flattener module

Code Style

• Follow PEP 8 guidelines
• Use type hints for all functions and methods
• Write docstrings for all public functions
• Keep line length under 88 characters
• Use descriptive variable and function names

Testing Requirements

• All new code must have corresponding tests
• Tests should cover both success and error cases
• Aim for >90% test coverage
• Use descriptive test names
• Mock external API calls in tests

Documentation

• Update README.md for new features
• Add docstrings to all public functions
• Update CHANGELOG.md
• Include code examples for new functionality

🏥 Healthcare Code Guidelines

Since this library handles healthcare data:

Security Considerations

• Never log sensitive patient data
• Use secure credential handling
• Follow HIPAA compliance guidelines
• Validate all inputs thoroughly

Data Handling

• Respect PHI (Protected Health Information) guidelines
• Implement proper error handling for sensitive operations
• Use secure HTTP practices
• Follow data minimization principles

🐛 Bug Reports

When reporting bugs, please include:

1. Environment Information

   • Python version
   • library version
   • Operating system

2. Reproduction Steps

   • Clear steps to reproduce the issue
   • Minimal code example
   • Expected vs actual behavior

3. Error Details

   • Full error messages
   • Stack traces
   • Relevant logs

💡 Feature Requests

For feature requests:

1. Check Existing Issues

   • Search for similar requests
   • Check project roadmap

2. Provide Context

   • Use case description
   • Expected functionality
   • Potential implementation approach

3. Healthcare Context

   • Explain healthcare-specific requirements
   • Consider compliance implications

📋 Development Tasks

Common Tasks

1. Adding New Endpoint

   # In client.py
   async def get_new_endpoint(self, params: Optional[Dict[str, Any]] = None,
                             flatten: Optional[bool] = None) -> Union[Dict[str, Any], pd.DataFrame]:
       """Get data from new endpoint"""
       response = await self.get("/api/new_endpoint", params)
       return await self._process_response(response, flatten)

2. Adding New Exception

   # In exceptions.py
   class KipuNewError(KipuAPIError):
       """Raised when new specific error occurs"""
       pass

3. Adding Tests

   # In tests/test_new_feature.py
   class TestNewFeature:
       def test_new_functionality(self):
           """Test new functionality"""
           # Test implementation
           pass

Release Process

1. Update Version

   • Update __version__ in __init__.py
   • Update version in setup.py and pyproject.toml

2. Update Documentation

   • Update CHANGELOG.md
   • Update README.md if needed

3. Create Release

   • Tag release in Git
   • GitHub Actions will handle PyPI deployment

🤝 Code of Conduct

Our Standards

• Be respectful and inclusive
• Focus on constructive feedback
• Help newcomers learn and grow
• Maintain professional communication

Healthcare Context

• Respect patient privacy in all discussions
• Consider compliance implications
• Prioritize security and data protection
• Follow healthcare industry best practices

❓ Getting Help

• Documentation: Check existing docs and examples
• Issues: Search existing GitHub issues
• Discussions: Use GitHub Discussions for questions
• Email: Contact maintainers at rahul01110100@gmail.com

🏆 Recognition

Contributors will be recognized in:

• CHANGELOG.md
• GitHub contributors list
• Project documentation

Thank you for contributing to the Kipu API Python library! 🎉