feat: Set up comprehensive Python testing infrastructure with Poetry

[llbbl]

Set up comprehensive Python testing infrastructure

Summary

This PR establishes a complete testing infrastructure for the cGAN Channel Estimation project using Poetry as the package manager. The setup provides a robust foundation for writing and running tests with comprehensive coverage reporting.

Changes Made

Package Management

• Poetry Configuration: Created pyproject.toml with Poetry configuration
• Dependency Migration: Identified and configured all project dependencies:
  • Core: tensorflow, numpy, matplotlib, scipy, h5py, hdf5storage, scikit-fuzzy
  • Testing: pytest, pytest-cov, pytest-mock (development dependencies)

Testing Infrastructure

• Directory Structure: Created organized test structure:

  tests/
  ├── __init__.py
  ├── conftest.py          # Shared fixtures
  ├── test_infrastructure.py  # Validation tests
  ├── unit/
  │   └── __init__.py
  └── integration/
      └── __init__.py
  

• pytest Configuration: Comprehensive configuration in pyproject.toml:

  • Custom markers: unit, integration, slow
  • Strict configuration for reliable testing
  • Warning filters for cleaner output

Coverage Reporting

• Coverage Settings: Configured with 80% threshold
• Multiple Formats: HTML, XML, and terminal reporting
• Source Mapping: Properly configured to cover cGAN_python module
• Exclusions: Smart exclusions for tests, migrations, and virtual environments

Shared Fixtures (conftest.py)

• TensorFlow Fixtures: Mock configurations, GPU settings, warning suppression
• Data Fixtures: Sample batch data, temporary directories, mock generators/discriminators
• Testing Utilities: Optimizers, loss values, file system utilities

Development Setup

• .gitignore: Comprehensive ignore patterns for:
  • Python artifacts (__pycache__, .pyc)
  • Testing outputs (.coverage, htmlcov/, .pytest_cache/)
  • ML-specific files (*.h5, checkpoints/, tensorboard_logs/)
  • IDE and OS files
  • Claude Code settings

Running Tests

Basic Commands

# Run all tests
poetry run pytest

# Run with coverage
poetry run pytest --cov=cGAN_python --cov-report=html --cov-report=term

# Run specific test categories
poetry run pytest -m unit          # Only unit tests
poetry run pytest -m integration   # Only integration tests
poetry run pytest -m "not slow"    # Exclude slow tests

Coverage Reports

• Terminal: Real-time coverage feedback
• HTML: Detailed interactive report in htmlcov/
• XML: Machine-readable format in coverage.xml

Validation

The infrastructure includes comprehensive validation tests that verify:

• ✅ Basic pytest functionality
• ✅ TensorFlow and NumPy imports
• ✅ Project structure integrity
• ✅ Fixture availability and functionality
• ✅ Coverage configuration
• ✅ Custom markers setup

Test Results: 12 passed, 1 skipped (GAN module import requires PYTHONPATH setup)

Notes

• Poetry Lock File: The poetry.lock file is included in version control for reproducible builds
• Python Version: Configured for Python 3.8+ compatibility
• TensorFlow: Uses TensorFlow 2.12+ with automatic GPU configuration
• Test Organization: Clear separation between unit, integration, and slow tests

Next Steps

Developers can now:

1. Install dependencies: poetry install
2. Write tests in appropriate directories (tests/unit/, tests/integration/)
3. Use shared fixtures from conftest.py
4. Run tests with coverage reporting
5. Follow TDD practices with the established infrastructure

The testing infrastructure is ready for immediate use and can be extended as the project grows.