feat: Set up comprehensive Python testing infrastructure

[llbbl]

Set Up Python Testing Infrastructure

Summary

This PR establishes a comprehensive testing infrastructure for the ArithmeticEncodingPython project using modern Python tooling and best practices.

Changes Made

Package Management

• Migrated to Poetry: Created pyproject.toml with Poetry configuration
• Dependency Management: Migrated project metadata from setup.py to pyproject.toml
• Testing Dependencies: Added pytest, pytest-cov, and pytest-mock as development dependencies

Testing Configuration

• pytest Configuration: Set up comprehensive pytest configuration with:
  • Test discovery patterns for test_*.py and *_test.py files
  • Custom markers: unit, integration, slow
  • Strict configuration options for robust testing
  • Verbose output formatting

Coverage Reporting

• Coverage Setup: Configured pytest-cov with:
  • 80% coverage threshold requirement
  • Multiple output formats: terminal, HTML, XML
  • Source code tracking with proper exclusions
  • HTML reports generated in htmlcov/ directory

Directory Structure

• Test Organization: Created structured test directories:

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

Shared Test Utilities

• Fixtures: Comprehensive set of reusable pytest fixtures in conftest.py:
  • temp_dir, temp_file for file system testing
  • sample_data, sample_text for data testing
  • sample_frequencies for arithmetic encoding tests
  • mock_file_operations for mocking file I/O
  • Parametrized fixtures for comprehensive input testing

Development Environment

• Git Configuration: Added comprehensive .gitignore with:
  • Testing artifacts (.pytest_cache/, .coverage, htmlcov/)
  • Python bytecode and build artifacts
  • Virtual environment directories
  • IDE and OS-specific files
  • Claude settings exclusion

Instructions for Running Tests

Install Dependencies

poetry install

Run All Tests

poetry run pytest

Run Tests with Coverage

poetry run pytest --cov=pyae --cov-report=html

Run Specific Test Categories

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

Generate Coverage Reports

• Terminal: Automatically shown with --cov-report=term-missing
• HTML: Open htmlcov/index.html in browser after running tests
• XML: Coverage data saved to coverage.xml for CI/CD integration

Testing Infrastructure Features

• ✅ 80% coverage threshold enforced
• ✅ Custom test markers for organizing test suites
• ✅ Comprehensive fixtures for common testing scenarios
• ✅ Parametrized testing support for thorough input validation
• ✅ Mocking utilities ready for file I/O and external dependencies
• ✅ Strict pytest configuration to catch configuration issues early
• ✅ Multiple output formats for coverage reporting

Validation

The setup includes validation tests that verify:

• Python version compatibility (3.8+)
• Pytest marker registration
• Project structure integrity
• Fixture availability and functionality
• Basic pytest and mocking capabilities

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

Next Steps

Developers can now:

1. Write unit tests in tests/unit/
2. Write integration tests in tests/integration/
3. Use the shared fixtures from conftest.py
4. Run tests with poetry run pytest
5. Generate coverage reports to ensure code quality