feat: Add comprehensive Python testing infrastructure with Poetry

[llbbl]

Add Python Testing Infrastructure

Summary

This PR sets up a complete testing infrastructure for the neural network pruning project using Poetry as the package manager and pytest as the testing framework.

Changes Made

Package Management

• Poetry Setup: Created pyproject.toml with Poetry configuration
• Dependencies: Migrated existing dependencies (torch, torchvision, numpy) to Poetry
• Testing Dependencies: Added pytest, pytest-cov, and pytest-mock as development dependencies

Testing Configuration

• pytest Configuration in pyproject.toml:

  • Test discovery patterns for multiple naming conventions
  • Coverage reporting with HTML and XML outputs
  • Custom markers for test categorization (unit, integration, slow)
  • Strict mode enabled with colored output

• Coverage Configuration:

  • Source directories and exclusion patterns defined
  • Coverage threshold set to 0% for validation phase
  • Multiple reporting formats configured

Directory Structure

tests/
├── __init__.py
├── conftest.py              # Shared pytest fixtures
├── unit/                    # Unit tests directory
│   └── __init__.py
├── integration/             # Integration tests directory
│   └── __init__.py
├── test_setup_validation.py # Infrastructure validation tests
└── README.md               # Testing documentation

Shared Fixtures (conftest.py)

Created comprehensive fixtures for common testing needs:

• General: temp_dir, random_seed, device
• PyTorch Models: mock_model, sample_tensor, sample_batch, mock_dataloader
• Training: mock_optimizer, mock_scheduler, checkpoint_dir, sample_checkpoint
• Utilities: mock_args, capture_stdout, tensor_shapes

Additional Setup

• Updated .gitignore with testing-related entries and .claude directory
• Created validation tests to verify all fixtures work correctly
• Added testing documentation in tests/README.md

How to Use

Running Tests

# Install dependencies
poetry install

# Run all tests
poetry run test
# or
poetry run tests

# Run specific test file
poetry run pytest tests/test_setup_validation.py

# Run tests with markers
poetry run pytest -m unit
poetry run pytest -m integration
poetry run pytest -m "not slow"

Writing Tests

Developers can now immediately start writing tests using the provided fixtures:

import pytest

class TestMyFeature:
    @pytest.mark.unit
    def test_model_forward(self, mock_model, sample_tensor):
        # Test implementation
        pass

Validation Results

All 17 validation tests pass successfully, confirming:

• ✅ All dependencies installed correctly
• ✅ pytest configuration working
• ✅ All fixtures functioning properly
• ✅ Test markers available
• ✅ Coverage reporting configured

Notes

• Poetry lock file (poetry.lock) is included and should be committed
• Coverage threshold is set to 0% initially - should be increased as tests are added
• The infrastructure is ready for immediate test development