kgirl/CONTRIBUTING.md

Contributing to Numbskull

Thank you for your interest in contributing to Numbskull! This document provides guidelines and information for contributors.

🚀 Getting Started

Prerequisites

• Python 3.8 or higher
• Git
• Basic understanding of embedding systems and machine learning

Development Setup

1. Fork the repository

   git clone https://github.com/your-username/numbskull.git
   cd numbskull
   

2. Create a virtual environment

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

3. Install dependencies

   pip install -r requirements.txt
   pip install -e .  # Install in development mode
   

4. Install development dependencies

   pip install pytest black flake8 mypy
   

5. Run tests

   cd advanced_embedding_pipeline
   python simple_test.py
   

🎯 How to Contribute

Types of Contributions

1. Bug Reports: Report issues you find
2. Feature Requests: Suggest new features
3. Code Contributions: Fix bugs or add features
4. Documentation: Improve documentation
5. Testing: Add tests or improve test coverage

Contribution Workflow

1. Create an Issue

   • Describe the problem or feature request
   • Provide context and examples
   • Assign appropriate labels

2. Fork and Branch

   git checkout -b feature/your-feature-name
   # or
   git checkout -b bugfix/your-bug-fix
   

3. Make Changes

   • Write clean, documented code
   • Add tests for new functionality
   • Update documentation as needed

4. Test Your Changes

   # Run basic tests
   python simple_test.py
   
   # Run full integration tests (if applicable)
   python integration_test.py
   
   # Run linting
   flake8 .
   black --check .
   

5. Commit and Push

   git add .
   git commit -m "Add: brief description of changes"
   git push origin feature/your-feature-name
   

6. Create Pull Request

   • Provide clear description
   • Link to related issues
   • Request reviews from maintainers

📝 Coding Standards

Python Code Style

• Follow PEP 8 guidelines
• Use type hints where possible
• Write docstrings for all functions and classes
• Keep functions small and focused

Example Code Style

from typing import List, Dict, Any, Optional
import logging

logger = logging.getLogger(__name__)


class ExampleEmbedder:
    """
    Example embedder following coding standards.
    
    Args:
        config: Configuration for the embedder
    """
    
    def __init__(self, config: Dict[str, Any]):
        self.config = config
        self.logger = logger
    
    async def embed_text(self, text: str) -> List[float]:
        """
        Embed a single text.
        
        Args:
            text: Input text to embed
            
        Returns:
            Embedding vector
            
        Raises:
            ValueError: If text is empty
        """
        if not text:
            raise ValueError("Text cannot be empty")
        
        # Implementation here
        return [0.1, 0.2, 0.3]  # Example return

Documentation Standards

• Use clear, concise language
• Provide examples for complex features
• Update README.md for user-facing changes
• Add docstrings for all public APIs

Testing Standards

• Write tests for new functionality
• Aim for >80% test coverage
• Test both success and failure cases
• Use descriptive test names

import pytest
from advanced_embedding_pipeline import ExampleEmbedder


class TestExampleEmbedder:
    """Test suite for ExampleEmbedder."""
    
    def test_embed_text_success(self):
        """Test successful text embedding."""
        embedder = ExampleEmbedder({})
        result = embedder.embed_text("test text")
        assert len(result) > 0
        assert all(isinstance(x, (int, float)) for x in result)
    
    def test_embed_text_empty_input(self):
        """Test embedding with empty input."""
        embedder = ExampleEmbedder({})
        with pytest.raises(ValueError):
            embedder.embed_text("")

🧪 Testing

Running Tests

# Basic functionality test
python simple_test.py

# Full integration test (requires external services)
python integration_test.py

# Comprehensive demo
python demo.py

# Unit tests (when available)
pytest tests/

Adding New Tests

1. Create test files in the tests/ directory
2. Use descriptive test names
3. Test both positive and negative cases
4. Mock external dependencies when possible

📚 Documentation

Types of Documentation

1. README.md: Main project documentation
2. Code Comments: Inline code documentation
3. Docstrings: Function and class documentation
4. Examples: Usage examples and tutorials

Writing Documentation

• Use clear, simple language
• Provide practical examples
• Keep documentation up-to-date
• Use consistent formatting

🐛 Bug Reports

Before Reporting

1. Check existing issues
2. Try the latest version
3. Reproduce the issue
4. Gather relevant information

Bug Report Template

**Bug Description**
A clear description of the bug.

**Steps to Reproduce**
1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error

**Expected Behavior**
What you expected to happen.

**Actual Behavior**
What actually happened.

**Environment**
- OS: [e.g., Ubuntu 20.04]
- Python Version: [e.g., 3.9]
- Numbskull Version: [e.g., 1.0.0]

**Additional Context**
Any other relevant information.

💡 Feature Requests

Feature Request Template

**Feature Description**
A clear description of the feature.

**Use Case**
Why is this feature needed?

**Proposed Solution**
How should this feature work?

**Alternatives Considered**
Other solutions you've considered.

**Additional Context**
Any other relevant information.

🔍 Code Review Process

For Contributors

• Respond to review feedback promptly
• Make requested changes
• Ask questions if feedback is unclear
• Test changes after addressing feedback

For Reviewers

• Be constructive and respectful
• Focus on code quality and correctness
• Provide specific, actionable feedback
• Approve when changes meet standards

📋 Pull Request Guidelines

PR Description Template

## Description
Brief description of changes.

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

## Testing
- [ ] Tests pass locally
- [ ] New tests added (if applicable)
- [ ] Documentation updated

## Checklist
- [ ] Code follows style guidelines
- [ ] Self-review completed
- [ ] Comments added for complex code
- [ ] No unnecessary debug code

🏷️ Labels and Milestones

Issue Labels

• bug: Something isn't working
• enhancement: New feature or request
• documentation: Improvements to documentation
• good first issue: Good for newcomers
• help wanted: Extra attention needed
• question: Further information is requested

PR Labels

• ready for review: Ready for code review
• work in progress: Still being worked on
• needs testing: Requires additional testing
• breaking change: Changes existing behavior

🚀 Release Process

1. Version Bumping: Update version in setup.py and __init__.py
2. Changelog: Update CHANGELOG.md with new features/fixes
3. Testing: Ensure all tests pass
4. Tagging: Create git tag for release
5. Documentation: Update documentation if needed

📞 Getting Help

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [Your contact information]

📄 License

By contributing to Numbskull, you agree that your contributions will be licensed under the MIT License.

🙏 Recognition

Contributors will be recognized in:

• CONTRIBUTORS.md file
• Release notes
• Project documentation

Thank you for contributing to Numbskull! 🎉