feat: Set up complete Python testing infrastructure with Poetry

[llbbl]

Set up Python Testing Infrastructure with Poetry

Summary

This PR establishes a comprehensive testing infrastructure for the project using Poetry as the package manager. The setup provides developers with a complete, ready-to-use testing environment that follows Python best practices.

Changes Made

Package Management

• Added pyproject.toml with Poetry configuration
• Configured dependencies: numpy, matplotlib, scikit-learn, scipy for existing ROC curve demo
• Added testing dependencies: pytest, pytest-cov, pytest-mock

Testing Configuration

• pytest configuration in pyproject.toml with:
  • 80% coverage threshold requirement
  • HTML and XML coverage reporting
  • Custom markers: unit, integration, slow
  • Strict configuration and test discovery patterns
• Coverage configuration with appropriate source paths and exclusions

Directory Structure

• Created testing directories: tests/, tests/unit/, tests/integration/
• Added __init__.py files for proper Python package structure
• Comprehensive conftest.py with shared fixtures including:
  • Temporary file/directory management
  • Mock configurations and data
  • Numpy random seed control
  • Matplotlib non-interactive backend setup
  • Parametrized fixtures for boolean/numeric testing

Development Environment

• Updated .gitignore with Python, testing, virtual environment, and IDE entries
• Preserved lock file tracking (poetry.lock not ignored as per best practices)
• Infrastructure validation tests to verify setup works correctly

Running Tests

Basic Commands

# Run all tests with coverage
poetry run pytest

# Run tests without coverage
poetry run pytest --no-cov

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

# Run with verbose output
poetry run pytest -v

Coverage Reports

• Terminal: Coverage summary shown after each test run
• HTML: htmlcov/index.html (detailed interactive report)
• XML: coverage.xml (CI/CD integration)

Validation

The setup includes comprehensive validation tests (tests/test_infrastructure.py) that verify:

• ✅ Python version compatibility (3.8+)
• ✅ All required packages import correctly
• ✅ Shared fixtures function properly
• ✅ Testing markers work as expected
• ✅ Project structure is correct
• ✅ Matplotlib uses non-interactive backend
• ✅ Coverage configuration is valid

All validation tests pass successfully, confirming the testing infrastructure is ready for use.

Next Steps

Developers can now:

1. Install dependencies: poetry install
2. Write unit tests in tests/unit/
3. Write integration tests in tests/integration/
4. Use shared fixtures from conftest.py
5. Run tests with coverage using poetry run pytest

The infrastructure is designed to support immediate test development for the existing ROC curve demo (ds-security/attach/py/roc.py) and any future Python components.