feat: Add comprehensive Python testing infrastructure with Poetry

[llbbl]

Add Python Testing Infrastructure

Summary

This PR establishes a comprehensive testing infrastructure for the PDVC (Parallel Decoding for Video Captioning) project. It introduces Poetry as the package manager, sets up pytest with coverage reporting, and creates a foundation for writing unit and integration tests.

Changes Made

Package Management

• Poetry Setup: Created pyproject.toml with Poetry configuration
• Dependency Migration: Migrated all dependencies from requirement.txt to Poetry
• Development Dependencies: Added pytest, pytest-cov, and pytest-mock as dev dependencies

Testing Configuration

• pytest Configuration:
  • Configured test discovery patterns
  • Set up coverage reporting with 80% threshold
  • Added custom test markers: unit, integration, and slow
  • Configured HTML and XML coverage reports
• Coverage Settings:
  • Included all main source directories
  • Excluded test files and CUDA operation sources from coverage

Directory Structure

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

Test Fixtures

Created comprehensive fixtures in conftest.py:

• temp_dir: Temporary directory management
• mock_config: Configuration mocking
• sample_video_features: Test data for video features
• sample_captions: Test data for captions
• mock_model: PyTorch model mocking
• mock_dataloader: DataLoader mocking
• sample_yaml_config: YAML configuration testing
• mock_h5_file: HDF5 file mocking
• device: CUDA/CPU device selection
• reset_random_seeds: Reproducibility fixture

Additional Updates

• Updated .gitignore to exclude testing artifacts and poetry.lock
• Created validation tests to ensure infrastructure works correctly

Running Tests

Using Poetry Commands

# Install dependencies
poetry install

# Run all tests
poetry run test
# or
poetry run tests

# Run with specific markers
poetry run pytest -m unit
poetry run pytest -m integration
poetry run pytest -m "not slow"

# Run with coverage report
poetry run pytest --cov-report=html

Direct pytest Usage

# After activating the virtual environment
pytest
pytest -v  # Verbose output
pytest tests/unit/  # Run only unit tests

Notes

• The coverage threshold is set to 80% but currently the project has 0% coverage as no actual unit tests have been written yet
• The testing infrastructure is ready for developers to start writing tests immediately
• All test dependencies are isolated in the development dependency group
• The validation tests confirm that all components are properly installed and configured

Next Steps

1. Write unit tests for core modules (pdvc, video_backbone, data)
2. Add integration tests for the full pipeline
3. Set up continuous integration to run tests automatically
4. Consider adding additional testing tools (e.g., hypothesis for property-based testing)