Set Up Python Testing Infrastructure for MELD

Summary

This PR establishes a comprehensive testing infrastructure for the MELD (Multimodal EmotionLines Dataset) project using Poetry as the package manager and pytest as the testing framework.

Changes Made

Package Management

• Poetry Configuration: Added pyproject.toml with Poetry configuration for dependency management
• Package Structure: Configured packages to include baseline and utils modules
• Development Dependencies: Added pytest (7.4.0+), pytest-cov (4.1.0+), and pytest-mock (3.11.1+) as development dependencies

Testing Infrastructure

• Directory Structure: Created organized test directories:
  • tests/ - Root testing directory
  • tests/unit/ - For unit tests
  • tests/integration/ - For integration tests
  • All directories include __init__.py files for proper Python package recognition

Test Configuration

• pytest Configuration: Comprehensive pytest settings in pyproject.toml:

  • Test discovery patterns for flexible naming conventions
  • Coverage reporting with HTML and XML output formats
  • Strict markers and configuration
  • Custom test markers: unit, integration, slow
  • Verbose output with clear failure reporting

• Coverage Configuration:

  • Source tracking for baseline and utils modules
  • Exclusion patterns for test files and common Python artifacts
  • HTML coverage reports in htmlcov/ directory
  • XML coverage report for CI integration
  • Coverage threshold set to 0% initially (should be increased as tests are added)

Shared Test Fixtures

Created comprehensive fixtures in conftest.py:

• temp_dir: Temporary directory for test file operations
• mock_config: Configuration dictionary for testing
• sample_dialogue_data: Sample MELD dialogue structure
• emotion_labels: List of 7 MELD emotions
• sentiment_labels: List of 3 MELD sentiments
• mock_csv_data: Creates mock CSV files for data loading tests
• mock_pickle_data: Mock data structure for pickle file testing
• data_path: Creates mock data directory structure
• reset_environment: Ensures clean environment for each test
• capture_stdout: Captures print statements for testing

Validation Tests

Created test_setup_validation.py to verify the infrastructure:

• Confirms pytest installation
• Validates project structure
• Tests all fixture availability
• Verifies test markers work correctly
• Ensures coverage reporting is configured

Build Configuration

• Git Ignore: Comprehensive .gitignore file including:
  • Python artifacts (__pycache__, *.pyc, etc.)
  • Testing artifacts (.pytest_cache/, coverage.xml, htmlcov/)
  • Virtual environments
  • IDE files
  • Claude-specific directories (.claude/*)
  • Build and distribution files

Poetry Scripts

Configured convenient test commands:

• poetry run test - Run all tests with coverage
• poetry run tests - Alternative command (both work identically)

How to Use

1. Install Dependencies:

   poetry install

2. Run Tests:

   poetry run test
   # or
   poetry run tests

3. Run Specific Test Types:

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

4. View Coverage Reports:

   • HTML Report: Open htmlcov/index.html in a browser
   • Terminal Report: Automatically displayed after test runs
   • XML Report: Available at coverage.xml for CI tools

Notes

• Coverage threshold is currently set to 0% to allow initial setup. This should be increased to 80% (or appropriate level) as actual tests are added
• The infrastructure is ready for immediate test development
• All pytest standard options are available through the Poetry commands
• The validation tests confirm that the setup is working correctly

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. Gradually increase coverage thresholds as tests are added