feat: Set up comprehensive Python testing infrastructure

[llbbl]

Set up comprehensive Python testing infrastructure

Summary

This PR establishes a complete testing infrastructure for the GraphCLIP project using Poetry as the package manager and pytest as the testing framework. The setup provides a solid foundation for developers to write and run tests effectively.

Changes Made

Package Management

• Created pyproject.toml with Poetry configuration
• Added core dependencies: torch, torchvision, numpy, Pillow, ftfy, regex, tqdm
• Added testing dependencies: pytest, pytest-cov, pytest-mock as dev dependencies
• Installed all dependencies successfully with Poetry

Testing Configuration

• Configured pytest in pyproject.toml with:
  • Test discovery patterns for test_*.py and *_test.py files
  • Coverage reporting with 80% threshold requirement
  • HTML and XML coverage report generation
  • Custom markers: unit, integration, slow
  • Strict configuration and verbose output

Directory Structure

• Created testing directory structure:

  tests/
  ├── __init__.py
  ├── conftest.py
  ├── unit/
  │   └── __init__.py
  ├── integration/
  │   └── __init__.py
  └── test_infrastructure.py
  

Shared Testing Resources

• Created comprehensive conftest.py with 15+ shared fixtures:
  • temp_dir: Temporary directory for file operations
  • sample_image, sample_tensor: Test data fixtures
  • mock_clip_model, mock_config: Mock objects for CLIP components
  • mock_dataloader, mock_optimizer: Mock training components
  • device, set_random_seeds: Environment setup fixtures
  • And many more for comprehensive testing support

Validation and Quality Assurance

• Created test_infrastructure.py with 22 validation tests covering:

  • Python version compatibility
  • All dependencies import correctly
  • Project structure validation
  • All fixtures work as expected
  • Coverage reporting functionality
  • Pytest markers functionality

• Updated .gitignore with comprehensive Python project exclusions:

  • Testing artifacts (.pytest_cache, .coverage, htmlcov/)
  • Python build artifacts, virtual environments
  • IDE files, OS files, model/data files
  • Claude Code settings (.claude/*)

How to Use

Running Tests

# Install dependencies (first time setup)
poetry install

# Run all tests
poetry run pytest

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

# Run specific test types
poetry run pytest -m unit          # Unit tests only
poetry run pytest -m integration   # Integration tests only
poetry run pytest -m slow         # Slow tests only

# Run with verbose output
poetry run pytest -v

Coverage Reporting

• Terminal output: Shows coverage summary with missing lines
• HTML report: Generated in htmlcov/ directory
• XML report: Generated as coverage.xml for CI/CD integration
• Minimum threshold: 80% coverage required for passing builds

Writing Tests

• Place unit tests in tests/unit/
• Place integration tests in tests/integration/
• Use fixtures from conftest.py for common test setup
• Mark tests appropriately (@pytest.mark.unit, etc.)

Testing Infrastructure Validation

All validation tests pass (22/22 ✅), confirming:

• ✅ Python 3.8+ compatibility
• ✅ All dependencies install and import correctly
• ✅ Project structure is properly recognized
• ✅ All fixtures work as expected
• ✅ Coverage reporting generates properly
• ✅ Custom markers function correctly
• ✅ Mocking capabilities are available

Notes

• Poetry is configured as the primary package manager
• Dependencies locked in poetry.lock (not in .gitignore)
• No actual unit tests for the codebase are included - this PR sets up the infrastructure only
• Ready for development: Developers can immediately start writing tests using the provided fixtures and structure

The testing infrastructure is now ready for use. Developers can start writing comprehensive tests for the GraphCLIP implementation with all necessary tooling and fixtures in place.