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 Python project using Poetry as the package manager and pytest as the testing framework. The setup provides a solid foundation for test-driven development with proper configuration, coverage reporting, and shared fixtures.

Changes Made

Package Management

• Poetry Configuration: Created pyproject.toml with Poetry as the package manager
• Dependencies Migration: Migrated dependencies from the codebase (pandas, numpy, scikit-learn, matplotlib, xlrd, scipy)
• Development Dependencies: Added pytest (^7.4.0), pytest-cov (^4.1.0), and pytest-mock (^3.11.0)

Testing Configuration

• pytest Settings: Configured in pyproject.toml with:
  • Test discovery patterns for test_*.py and *_test.py
  • Coverage settings with 80% threshold
  • HTML and XML coverage report generation
  • Custom markers: unit, integration, slow
  • Strict mode and detailed output options

Directory Structure

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

Shared Fixtures (conftest.py)

• temp_dir: Temporary directory creation and cleanup
• sample_csv_file: CSV file generation for testing
• sample_excel_file: Excel file generation for testing
• sample_iris_data: Mock iris dataset
• sample_boston_data: Mock Boston housing dataset
• mock_sklearn_model: Mock scikit-learn model
• sample_config: Configuration dictionary
• capture_stdout: Stdout capture utility
• mock_file_operations: File operation tracking
• reset_random_seed: Reproducibility helper

Additional Setup

• Code Package: Added __init__.py to Code directory for proper packaging
• .gitignore: Comprehensive Python gitignore with testing artifacts and Claude settings
• Poetry Scripts: Configured poetry run test and poetry run tests commands

Testing the Infrastructure

Installation

poetry install

Running Tests

# Run all tests
poetry run test

# Run with coverage
poetry run pytest --cov

# Run specific markers
poetry run pytest -m unit
poetry run pytest -m integration
poetry run pytest -m slow

# Run validation tests
poetry run pytest tests/test_validation.py -v

Validation Results

All 17 validation tests pass successfully, confirming:

• pytest installation and functionality
• All dependencies are properly installed
• Fixtures are accessible and working
• Custom markers are registered
• Coverage configuration is active
• Test discovery is functioning

Notes

• Python version requirement set to ^3.11 for compatibility with latest scipy
• The existing random_forest.py file has some syntax issues causing coverage warnings, but this doesn't affect the testing infrastructure
• Coverage is currently at 0% as no production code is being tested (only infrastructure validation)
• The poetry.lock file is committed to ensure reproducible builds

Next Steps

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. Run tests with coverage to ensure code quality
5. Use custom markers to organize and run specific test suites