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How to Contribute Code to yt-dlp

Contributing code to yt-dlp is an excellent way to improve the project, add new features, and give back to the community. This comprehensive guide covers everything you need to know about contributing code effectively.

Prerequisites and Setup​

Development Environment Requirements​

Before contributing, ensure you have:

  • Python 3.8+: Latest stable version recommended
  • Git: For version control and collaboration
  • GitHub Account: For forking and pull requests
  • Code Editor: VS Code, PyCharm, or your preferred editor
  • FFmpeg: For testing media processing features

Knowledge Requirements​

  • Python Programming: Intermediate to advanced level
  • Git Workflow: Basic understanding of branching and merging
  • Web Technologies: HTML, HTTP, JSON for extractor development
  • Regular Expressions: For pattern matching and extraction
  • Testing: Unit testing and integration testing concepts

Getting Started​

1. Fork and Clone the Repository​

git clone https://github.com/YOUR_USERNAME/yt-dlp.git

Clone your fork.

cd yt-dlp
git remote add upstream https://github.com/yt-dlp/yt-dlp.git

Add upstream remote for staying updated.

2. Set Up Development Environment​

python -m venv venv

Create virtual environment.

venv\Scripts\activate

Activate virtual environment (Windows).

source venv/bin/activate

Activate virtual environment (macOS/Linux).

pip install -r requirements.txt

Install development dependencies.

pip install -r devscripts/requirements.txt

Install additional development dependencies.

pip install -e .

Install in development mode.

3. Verify Installation​

python -m yt_dlp --version

Test basic functionality (version).

python -m yt_dlp --help

Test basic functionality (help).

python -m pytest test/test_download.py -v

Run basic tests.

Development Workflow​

1. Stay Updated with Upstream​

git fetch upstream

Fetch latest changes from upstream.

git checkout master

Switch to main branch.

git merge upstream/master

Update your main branch.

git push origin master

Push updates to your fork.

2. Create Feature Branch​

git checkout -b feature/your-feature-name

Create and switch to feature branch.

git checkout -b fix/issue-description

Create and switch to bug fix branch.

3. Make Your Changes​

Follow these development practices:

  • Write Clean Code: Follow PEP 8 style guidelines
  • Add Documentation: Document new features and functions
  • Write Tests: Add tests for new functionality
  • Commit Frequently: Make small, focused commits

4. Testing Your Changes​

python -m pytest

Run all tests.

python -m pytest test/test_extractors.py

Run specific test category (extractors).

python -m pytest test/test_postprocessors.py

Run specific test category (postprocessors).

python -m pytest test/test_extractors.py::test_youtube

Test with specific extractor (YouTube).

python -m flake8 yt_dlp/

Run linting.

5. Commit Your Changes​

git add .

Stage your changes.

git commit -m "Add support for NewSite extractor

- Implement NewSiteIE class with video extraction
- Add support for playlists and channels
- Include metadata extraction for title, description
- Add tests for various URL patterns"

Commit with descriptive message.

Types of Contributions​

1. Extractor Development​

Extractors are the core of yt-dlp, handling video extraction from websites.

Basic Extractor Structure​

from .common import InfoExtractor
from ..utils import (
    extract_attributes,
    get_element_by_class,
    unified_strdate,
)

class NewSiteIE(InfoExtractor):
    _VALID_URL = r'https?://(?:www\.)?newsite\.com/watch/(?P<id>[0-9]+)'
    _TESTS = [{
        'url': 'https://newsite.com/watch/12345',
        'md5': 'expected_md5_hash',
        'info_dict': {
            'id': '12345',
            'ext': 'mp4',
            'title': 'Expected Video Title',
            'description': 'Expected description',
            'uploader': 'Expected uploader',
            'duration': 120,
        }
    }]

    def _real_extract(self, url):
        video_id = self._match_id(url)
        webpage = self._download_webpage(url, video_id)

        title = self._html_search_regex(
            r'<title>([^<]+)</title>', webpage, 'title')

        video_url = self._html_search_regex(
            r'video_url["\']:\s*["\']([^"\']+)', webpage, 'video url')

        return {
            'id': video_id,
            'title': title,
            'url': video_url,
            'ext': 'mp4',
        }

Extractor Best Practices​

  1. URL Pattern Matching:

    _VALID_URL = r'https?://(?:www\.)?site\.com/(?:video/)?(?P<id>[a-zA-Z0-9]+)'

  2. Comprehensive Tests:

    _TESTS = [{
        'url': 'test_url',
        'info_dict': {
            'id': 'expected_id',
            'ext': 'expected_extension',
            'title': 'expected_title',
            # ... other expected fields
        }
    }, {
        # Additional test cases
        'url': 'another_test_url',
        'only_matching': True,  # For URL pattern testing only
    }]

  3. Error Handling:

    try:
        data = self._download_json(api_url, video_id)
    except ExtractorError as e:
        if 'not found' in str(e):
            raise ExtractorError('Video not found', expected=True)
        raise

2. Post-Processor Development​

Post-processors handle media processing after download.

Basic Post-Processor Structure​

from .common import PostProcessor
from ..utils import PostProcessingError

class CustomPP(PostProcessor):
    def __init__(self, downloader=None, **kwargs):
        super().__init__(downloader)
        # Initialize custom parameters

    def run(self, info):
        # Process the downloaded file
        filepath = info['filepath']

        try:
            # Perform custom processing
            self.to_screen(f'Processing {filepath}')
            # ... processing logic ...

            return [], info  # Return (files_to_delete, info_dict)
        except Exception as e:
            raise PostProcessingError(f'Custom processing failed: {str(e)}')

3. Core Functionality Improvements​

Contributing to core functionality requires understanding of:

  • YoutubeDL class: Main downloader logic
  • Format selection: Video/audio format handling
  • Network handling: HTTP requests and responses
  • File system operations: Path handling and file management

Contribution Guidelines​

Code Style and Standards​

  1. Follow PEP 8: Use consistent Python coding style
  2. Use Type Hints: Add type annotations for new code
  3. Write Docstrings: Document classes and functions
  4. Keep Functions Small: Break complex logic into smaller functions
  5. Use Meaningful Names: Choose descriptive variable and function names

Testing Requirements​

  1. Unit Tests: Test individual functions and methods
  2. Integration Tests: Test complete extraction workflows
  3. Edge Cases: Test error conditions and unusual inputs
  4. Performance Tests: Ensure changes don't degrade performance
# Example test structure
def test_new_site_extraction(self):
    """Test NewSite video extraction"""
    ie = NewSiteIE()
    result = ie.extract('https://newsite.com/watch/12345')

    self.assertEqual(result['id'], '12345')
    self.assertEqual(result['title'], 'Expected Title')
    self.assertIsNotNone(result['url'])

Documentation Requirements​

  1. Code Comments: Explain complex logic
  2. Docstrings: Document public methods and classes
  3. README Updates: Update documentation for new features
  4. Changelog Entries: Document user-facing changes

Pull Request Process​

1. Prepare Your Pull Request​

git checkout master

Switch to main branch.

git pull upstream master

Ensure your branch is up to date.

git checkout your-feature-branch

Switch to feature branch.

git rebase master

Rebase onto master.

python -m pytest

Run final tests.

python -m flake8 yt_dlp/

Run final linting.

git push origin your-feature-branch

Push your changes.

2. Create Pull Request​

  1. Go to GitHub: Navigate to your fork on GitHub
  2. Click "New Pull Request": Compare your branch with upstream master
  3. Fill PR Template: Complete all required sections
  4. Add Reviewers: Request review from maintainers

3. Pull Request Template​

## Description

Brief description of changes made

## Type of Change

- [ ] Bug fix
- [ ] New feature
- [ ] Breaking change
- [ ] Documentation update

## Testing

- [ ] Existing tests pass
- [ ] New tests added
- [ ] Manual testing completed

## Checklist

- [ ] Code follows project style guidelines
- [ ] Self-review completed
- [ ] Documentation updated
- [ ] Tests added/updated

4. Code Review Process​

  1. Initial Review: Maintainers review code and architecture
  2. Feedback: Address review comments and suggestions
  3. Iterate: Make requested changes and push updates
  4. Final Review: Maintainers approve and merge

Advanced Contribution Topics​

Extractor Maintenance​

  1. Site Changes: Update extractors when sites change
  2. Format Updates: Handle new video/audio formats
  3. API Changes: Adapt to site API modifications
  4. Performance: Optimize extraction speed and reliability

Security Considerations​

  1. Input Validation: Sanitize user inputs
  2. URL Handling: Prevent malicious URL exploitation
  3. File Operations: Secure file system access
  4. Network Security: Handle SSL/TLS properly

Performance Optimization​

  1. Caching: Implement appropriate caching strategies
  2. Async Operations: Use asynchronous programming where beneficial
  3. Memory Management: Optimize memory usage for large files
  4. Network Efficiency: Minimize unnecessary requests

Getting Help and Support​

Communication Channels​

  1. GitHub Issues: For bug reports and feature requests
  2. GitHub Discussions: For questions and general discussion
  3. Code Review: Through pull request comments
  4. Documentation: Comprehensive guides and references

Learning Resources​

  1. Existing Code: Study current extractors and implementations
  2. Test Cases: Learn from existing test patterns
  3. Documentation: Read all available documentation
  4. Community: Engage with other contributors

Recognition and Advancement​

Contribution Recognition​

  • Changelog: Contributors listed in release notes
  • Git History: Permanent record of contributions
  • Community: Recognition within the community
  • Skills: Improved programming and collaboration skills

Becoming a Maintainer​

Regular, high-quality contributions may lead to:

  • Commit Access: Direct repository access
  • Review Privileges: Ability to review other contributions
  • Decision Making: Input on project direction
  • Mentoring: Helping new contributors

Quick Reference​

Common Commands​

git clone https://github.com/YOUR_USERNAME/yt-dlp.git

Clone repository.

cd yt-dlp

Navigate to repository.

python -m venv venv

Create virtual environment.

source venv/bin/activate

Activate virtual environment (macOS/Linux).

venv\Scripts\activate

Activate virtual environment (Windows).

pip install -e .

Install in development mode.

python -m pytest

Run all tests.

python -m pytest test/test_extractors.py::TestYoutube

Test specific extractor.

python -m flake8 yt_dlp/

Run linting.

git checkout -b feature/new-feature

Create feature branch.

git add .

Stage changes.

git commit -m "Descriptive commit message"

Commit changes.

git push origin feature/new-feature

Push to feature branch.

Contribution Checklist​

  • Fork and clone repository
  • Set up development environment
  • Create feature branch
  • Make changes following guidelines
  • Add comprehensive tests
  • Update documentation
  • Run all tests and linting
  • Create pull request
  • Respond to review feedback
  • Celebrate your contribution!

Contributing to yt-dlp is rewarding and helps millions of users worldwide. Start small, learn continuously, and don't hesitate to ask for help when needed. Your contributions make a real difference!