A043-studios-ComfyUI_HunyuanWorldnode/CONTRIBUTING.md

Contributing to ComfyUI-HunyuanWorld

Thank you for your interest in contributing to ComfyUI-HunyuanWorld! We welcome contributions from the community.

🤝 How to Contribute

Reporting Bugs

1. Check if the bug has already been reported in Issues
2. If not, create a new issue using the bug report template
3. Include as much detail as possible (OS, Python version, error logs, etc.)

Suggesting Features

1. Check if the feature has already been requested
2. Create a new issue using the feature request template
3. Describe your use case and why the feature would be valuable

Contributing Code

Setting Up Development Environment

# Fork the repository on GitHub
# Clone your fork
git clone https://github.com/A043-studios/ComfyUI_HunyuanWorldnode.git
cd ComfyUI_HunyuanWorldnode

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

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

# Install pre-commit hooks
pre-commit install

Making Changes

1. Create a new branch for your feature/fix:

   git checkout -b feature/your-feature-name
   

2. Make your changes following our coding standards:

   • Use Black for code formatting: black .
   • Use isort for import sorting: isort .
   • Follow PEP 8 guidelines
   • Add type hints where appropriate
   • Write docstrings for new functions/classes

3. Add tests for new functionality:

   # Run tests
   pytest tests/
   
   # Run with coverage
   pytest --cov=hunyuanworld tests/
   

4. Update documentation:

   • Update README.md if needed
   • Update CHANGELOG.md
   • Add docstrings to new code
   • Update example workflows if applicable

5. Commit your changes:

   git add .
   git commit -m "feat: add new feature description"
   

   Use conventional commit messages:

   • feat: for new features
   • fix: for bug fixes
   • docs: for documentation changes
   • style: for formatting changes
   • refactor: for code refactoring
   • test: for adding tests
   • chore: for maintenance tasks

6. Push to your fork and create a Pull Request:

   git push origin feature/your-feature-name
   

Pull Request Guidelines

• Fill out the PR template completely
• Ensure all tests pass
• Update documentation as needed
• Keep PRs focused on a single feature/fix
• Write clear commit messages
• Be responsive to feedback

🧪 Testing

Running Tests

# Run all tests
pytest

# Run specific test file
pytest tests/test_nodes.py

# Run with coverage
pytest --cov=hunyuanworld --cov-report=html

Test Categories

• Unit tests: Test individual functions/classes
• Integration tests: Test node interactions
• Compatibility tests: Test with different Python/PyTorch versions
• Performance tests: Test memory usage and speed

Writing Tests

• Place tests in the tests/ directory
• Name test files test_*.py
• Use descriptive test names
• Test both success and failure cases
• Mock external dependencies when appropriate

📝 Documentation

Code Documentation

• Write clear docstrings for all public functions/classes
• Use Google-style docstrings
• Include parameter types and return types
• Provide usage examples for complex functions

User Documentation

• Update README.md for user-facing changes
• Add examples to example_workflows.json
• Update troubleshooting section for common issues
• Keep documentation up-to-date with code changes

🎨 Code Style

Python Style Guide

• Follow PEP 8
• Use Black for formatting (line length: 100)
• Use isort for import sorting
• Use type hints where possible
• Prefer descriptive variable names

Example:

from typing import Optional, Tuple
import torch
from PIL import Image

def process_image(
    image: Image.Image, 
    target_size: Tuple[int, int] = (512, 512),
    normalize: bool = True
) -> torch.Tensor:
    """
    Process an input image for 3D generation.
    
    Args:
        image: Input PIL image
        target_size: Target dimensions (width, height)
        normalize: Whether to normalize pixel values to [0,1]
        
    Returns:
        Processed image tensor
        
    Example:
        >>> img = Image.open("test.jpg")
        >>> tensor = process_image(img, (1024, 1024))
    """
    # Implementation here
    pass

🚀 Release Process

Version Numbering

We follow Semantic Versioning:

• MAJOR.MINOR.PATCH
• Major: Breaking changes
• Minor: New features (backward compatible)
• Patch: Bug fixes (backward compatible)

Release Checklist

• Update version in setup.py and pyproject.toml
• Update CHANGELOG.md
• Run full test suite
• Update documentation
• Create release PR
• Tag release after merge
• Publish to PyPI (if applicable)

🏷️ Issue Labels

• bug: Something isn't working
• enhancement: New feature or request
• documentation: Improvements or additions to docs
• good first issue: Good for newcomers
• help wanted: Extra attention is needed
• question: Further information is requested
• wontfix: This will not be worked on

💬 Community Guidelines

Be Respectful

• Use welcoming and inclusive language
• Be respectful of differing viewpoints
• Accept constructive criticism gracefully
• Focus on what's best for the community

Be Helpful

• Help newcomers get started
• Share knowledge and experience
• Provide constructive feedback
• Be patient with questions

📞 Getting Help

• Questions: Open a GitHub issue with the question label
• Bugs: Use the bug report template
• Features: Use the feature request template
• Security: Email security issues privately (if applicable)

🙏 Recognition

Contributors will be recognized in:

• CONTRIBUTORS.md file
• Release notes
• GitHub contributors page

Thank you for contributing to ComfyUI-HunyuanWorld! 🌍✨