feat: Set up comprehensive Python testing infrastructure

[llbbl]

Set up Python Testing Infrastructure

Summary

This PR establishes a comprehensive testing infrastructure for the Phantom-Wan video generation project. It transitions the project from simple pip-based dependency management to Poetry, and sets up a complete pytest-based testing framework ready for developers to write tests.

Changes Made

Package Management

• Migrated to Poetry: Created pyproject.toml with all dependencies from requirements.txt
• Python Version: Set to Python 3.10+ (required by Gradio)
• Optional Dependencies: Made flash-attn optional for CPU environments via Poetry extras

Testing Framework

• Testing Dependencies: Added as development dependencies:
  • pytest (^8.0.0) - Core testing framework
  • pytest-cov (^5.0.0) - Coverage reporting
  • pytest-mock (^3.14.0) - Mocking utilities
  • pytest-xdist (^3.6.0) - Parallel test execution
  • pytest-timeout (^2.3.0) - Test timeout management

Testing Configuration

• pytest Configuration in pyproject.toml:

  • Test discovery patterns for various naming conventions
  • Custom markers: unit, integration, slow, gpu, network
  • Strict mode enabled for better error detection
  • Coverage configuration with 80% threshold (configurable)

• Coverage Settings:

  • Source: phantom_wan package
  • Output formats: Terminal, HTML, XML
  • Exclusions for test files, __init__.py, virtual environments

Directory Structure

tests/
├── __init__.py
├── conftest.py              # Shared fixtures
├── test_setup_validation.py # Infrastructure validation
├── unit/
│   └── __init__.py
└── integration/
    └── __init__.py

Shared Fixtures (conftest.py)

• temp_dir: Temporary directory management
• mock_config: Configuration dictionary for testing
• sample_image: Creates test images
• sample_video_frames: Creates test video frame sequences
• mock_torch_tensor, mock_numpy_array: Test data
• mock_model, mock_pipeline: Model/pipeline mocks
• env_vars: Environment variable management
• capture_logs: Log capture for testing
• gpu_available: GPU availability check
• And more...

Development Tools

• Added linting/formatting tools: black, isort, flake8, mypy
• Added pre-commit for git hooks
• Poetry scripts: poetry run test and poetry run tests

Updated .gitignore

• Added testing artifacts: .pytest_cache/, .coverage, htmlcov/, etc.
• Added Claude settings: .claude/
• Added development tools and IDE files
• Preserved existing project-specific ignores

How to Use

Installation

# Install Poetry if not already installed
curl -sSL https://install.python-poetry.org | python3 -

# Install dependencies
poetry install

# Install with CUDA support (optional)
poetry install -E cuda

Running Tests

# Run all tests
poetry run test

# Run with coverage
poetry run pytest --cov=phantom_wan

# Run specific test categories
poetry run pytest -m unit
poetry run pytest -m integration
poetry run pytest -m "not slow"

# Run tests in parallel
poetry run pytest -n auto

Writing Tests

1. Create test files in tests/unit/ or tests/integration/
2. Use fixtures from conftest.py for common test needs
3. Mark tests appropriately: @pytest.mark.unit, @pytest.mark.slow, etc.
4. Follow naming convention: test_*.py for test files

Notes

• The project requires Python 3.10+ due to Gradio dependency
• flash-attn is optional and only installs with CUDA support
• Coverage is currently disabled in pytest.ini_options to avoid issues with the CUDA-dependent codebase
• The validation tests pass successfully, confirming the infrastructure is working

Next Steps

With this infrastructure in place, developers can now:

1. Write unit tests for individual components
2. Create integration tests for pipelines
3. Add performance benchmarks
4. Set up CI/CD with the test suite
5. Enable coverage reporting once the codebase is more test-friendly