feat: Set up comprehensive Python testing infrastructure

[llbbl]

Set Up Complete Python Testing Infrastructure

Summary

This PR establishes a comprehensive testing infrastructure for the MeshGPT PyTorch research project, providing a robust foundation for developers to write and run tests effectively.

Changes Made

Package Management Setup

• Poetry Configuration: Migrated from requirements.txt to Poetry-based dependency management
• pyproject.toml: Created complete Poetry configuration with proper project metadata
• Dependency Migration: All 23 production dependencies successfully migrated from requirements.txt
• Test Dependencies: Added pytest (^7.0.0), pytest-cov (^4.0.0), and pytest-mock (^3.10.0)

Testing Framework Configuration

• pytest Configuration: Comprehensive setup in pyproject.toml with:
  • 80% coverage threshold requirement
  • HTML, XML, and terminal coverage reporting
  • Custom markers for unit, integration, and slow tests
  • Strict configuration options for robust testing
  • Test discovery patterns for automatic test collection

Directory Structure

• tests/ - Main testing directory with proper __init__.py
• tests/unit/ - Unit test subdirectory
• tests/integration/ - Integration test subdirectory
• tests/conftest.py - Comprehensive shared fixtures including:
  • Temporary directory management
  • Mock configurations and models
  • Sample tensor and mesh data
  • Random seed control for reproducible tests
  • CUDA disabling for consistent test environments

Infrastructure Validation

• Validation Tests: Complete test suite in tests/test_infrastructure_validation.py to verify:
  • pytest functionality and marker configuration
  • All fixtures working correctly
  • Torch/ML environment setup
  • Coverage tracking functionality
  • Module imports and dependencies

Development Workflow

• Poetry Scripts: Added poetry run test and poetry run tests commands
• Coverage Reporting: Automatic HTML/XML report generation in htmlcov/ and coverage.xml
• .gitignore Updates: Added Claude Code settings and testing artifacts

How to Run Tests

# Install dependencies (if not already done)
poetry install

# Run all tests
poetry run pytest

# Run with coverage report
poetry run pytest --cov=model --cov=data

# Run specific test categories
poetry run pytest -m unit      # Unit tests only
poetry run pytest -m integration  # Integration tests only
poetry run pytest -m slow      # Slow tests only

# Using Poetry scripts
poetry run test                # Alternative command
poetry run tests               # Alternative command

Coverage Configuration

• Source Coverage: Tracks model/ and data/ directories
• Exclusions: Tests, __init__.py files, and common non-testable patterns
• Threshold: 80% minimum coverage required
• Reporting: HTML reports in htmlcov/, XML in coverage.xml

Dependencies Note

One dependency (open3d) failed to install due to architecture compatibility issues, but this doesn't affect the core testing infrastructure. All pytest functionality and validation tests pass successfully.

Testing Infrastructure Components

✅ Package Management: Poetry with complete dependency migration
✅ Test Framework: pytest with comprehensive configuration
✅ Coverage Reporting: pytest-cov with HTML/XML output
✅ Mocking Support: pytest-mock for test isolation
✅ Directory Structure: Organized test directories with proper imports
✅ Shared Fixtures: Rich fixture library for common testing needs
✅ Configuration: Centralized testing configuration in pyproject.toml
✅ Validation: Infrastructure validation tests ensure everything works
✅ Documentation: Clear instructions for running tests

Next Steps

Developers can now immediately start writing tests using:

• The established directory structure (tests/unit/, tests/integration/)
• Rich fixtures from conftest.py (temp directories, mock models, sample data)
• Standard pytest patterns with coverage tracking
• Poetry commands for easy test execution

The testing infrastructure is complete and ready for development teams to begin writing comprehensive tests for the MeshGPT implementation.