feat: Set up comprehensive Python testing infrastructure

[llbbl]

Python Testing Infrastructure Setup

Summary

This PR sets up a comprehensive testing infrastructure for the DynaCam evaluation and visualization project. The setup provides a robust foundation for writing and running tests with proper coverage reporting, fixtures, and development workflows.

Changes Made

Package Management

• Added Poetry configuration in pyproject.toml with project metadata
• Configured Python ^3.9 requirement to ensure compatibility
• Added core testing dependencies: pytest, pytest-cov, pytest-mock

Testing Configuration

• pytest configuration with strict markers, verbose output, and comprehensive coverage settings
• Coverage configuration with 80% threshold, HTML/XML/terminal reporting
• Custom test markers: unit, integration, slow for test categorization
• Test discovery patterns for proper test file detection

Directory Structure

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

Shared Fixtures (tests/conftest.py)

• temp_dir: Temporary directory management
• sample_data_dir: Mock data directory structure
• sample_annotations: Sample annotation data for testing
• sample_trajectory: Mock trajectory data
• mock_config: Configuration fixtures
• numpy_random_seed: Reproducible random number generation
• Environment setup and session configuration

Development Commands

• poetry run test - Run all tests with coverage
• poetry run tests - Alternative test command
• Standard pytest options available (-v, -k, -m, etc.)

Git Configuration

• Updated .gitignore with testing artifacts:
  • .pytest_cache/, .coverage, htmlcov/, coverage.xml
  • Claude Code settings (.claude/*)
  • Additional testing artifacts (*traj_vis/, *.npz, *.npy)

Validation

The setup includes comprehensive validation tests that verify:

• ✅ Pytest is working correctly
• ✅ Custom fixtures are available and functional
• ✅ Test markers are properly configured
• ✅ Project structure is correct
• ✅ Coverage reporting is configured
• ✅ All fixtures provide expected data structures

All 14 validation tests pass successfully

Usage Instructions

Running Tests

# Run all tests
poetry run test

# Run with verbose output
poetry run test -v

# Run specific test markers
poetry run test -m unit
poetry run test -m integration

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

# Run specific test file
poetry run test tests/test_setup_validation.py

Coverage Reports

• Terminal: Shows coverage summary after test run
• HTML: Generated in htmlcov/ directory
• XML: Generated as coverage.xml for CI/CD integration

Writing New Tests

1. Create test files in tests/unit/ or tests/integration/
2. Use available fixtures from conftest.py
3. Apply appropriate markers: @pytest.mark.unit, @pytest.mark.integration, @pytest.mark.slow
4. Follow naming conventions: test_*.py, Test* classes, test_* functions

Notes

• The setup currently includes minimal production dependencies (only numpy) to avoid environment compatibility issues
• Additional project dependencies can be added to pyproject.toml as needed
• The poetry.lock file should be committed to ensure reproducible builds
• Coverage threshold is set to 80% but can be adjusted in pyproject.toml

This testing infrastructure provides a solid foundation for maintaining code quality and enabling test-driven development practices in the project.