feat: Set up comprehensive Python testing infrastructure with Poetry

[llbbl]

Set Up Python Testing Infrastructure

Summary

This PR establishes a comprehensive testing infrastructure for the pytorch-gradual-warmup-lr project using Poetry as the package manager and pytest as the testing framework.

Changes Made

Package Management

• Migrated to Poetry: Created pyproject.toml with Poetry configuration
• Preserved existing metadata: Maintained version, description, and URLs from setup.py
• Note: setup.py is kept for backward compatibility

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

Testing Configuration

Configured in pyproject.toml:

• Test discovery: Configured to find tests in tests/ directory
• Coverage settings:
  • Source: warmup_scheduler package
  • Reports: Terminal, HTML, and XML formats
  • Threshold: 80% (currently disabled due to PyTorch dependency)
• Custom markers:
  • unit - For unit tests
  • integration - For integration tests
  • slow - For slow-running tests

Directory Structure

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

Shared Fixtures (conftest.py)

• temp_dir - Temporary directory management
• mock_config - Mock configuration objects
• mock_optimizer - Mock PyTorch optimizer
• mock_scheduler - Mock LR scheduler
• capture_output - Stdout/stderr capture
• mock_torch_module - Mock torch imports
• sample_data - Test data provider
• environment_vars - Environment variable management
• mock_time - Time-related mocking

Development Commands

Both commands are configured to run tests:

• poetry run test
• poetry run tests

Additional Updates

• Updated .gitignore with:
  • Testing artifacts (.pytest_cache/, htmlcov/, coverage.xml)
  • Claude settings (.claude/*)
  • IDE files
  • Note that poetry.lock should be committed

How to Use

1. Install Poetry (if not already installed):

   pip install poetry

2. Install dependencies:

   poetry install

3. Run tests:

   poetry run test
   # or
   poetry run tests

4. Run tests with specific markers:

   poetry run pytest -m unit        # Run only unit tests
   poetry run pytest -m integration # Run only integration tests
   poetry run pytest -m "not slow"  # Skip slow tests

5. View coverage report:

   # After running tests, open the HTML report
   open htmlcov/index.html

Notes

• The validation tests currently skip tests that require PyTorch, as it's not included in the base dependencies
• Coverage threshold is configured but not enforced during infrastructure setup
• The testing infrastructure is ready for developers to start writing actual unit and integration tests
• All pytest options remain available (e.g., -v for verbose, -k for keyword matching, etc.)

Next Steps

With this infrastructure in place, developers can now:

1. Write unit tests in tests/unit/
2. Write integration tests in tests/integration/
3. Use the provided fixtures for common testing scenarios
4. Add PyTorch as a dependency when needed for actual tests