feat: Set up comprehensive Python testing infrastructure with Poetry

.gitignore

@@ -48,6 +48,7 @@ nosetests.xml
 coverage.xml
 *.cover
 .hypothesis/
+.pytest_cache/
 
 # Translations
 *.mo
@@ -101,4 +102,23 @@ ENV/
 /site
 
 # mypy
-.mypy_cache/
+.mypy_cache/
+
+# Poetry - DO NOT ignore lock file
+# poetry.lock is intentionally not ignored
+dist/
+
+# IDE files
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS files
+.DS_Store
+Thumbs.db
+
+# Testing artifacts
+test-results/
+.benchmarks/

pyproject.toml

@@ -0,0 +1,86 @@
+[tool.poetry]
+name = "stn"
+version = "1.0.1"
+description = "Spatial Transformer Networks."
+authors = ["Kevin Zakka <kevinarmandzakka@gmail.com>"]
+license = "MIT"
+readme = "README.md"
+homepage = "https://github.com/kevinzakka/spatial-transformer-network"
+repository = "https://github.com/kevinzakka/spatial-transformer-network"
+keywords = ["ai", "neural networks", "machine learning", "ml", "deep learning", "dl", "spatial transformer networks"]
+packages = [{include = "stn"}]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+numpy = "*"
+
+
+[tool.poetry.group.dev.dependencies]
+pytest = "^7.4.0"
+pytest-cov = "^4.1.0"
+pytest-mock = "^3.11.1"
+
+[tool.poetry.scripts]
+test = "pytest:main"
+tests = "pytest:main"
+
+[tool.pytest.ini_options]
+minversion = "7.0"
+addopts = [
+    "-ra",
+    "--strict-markers",
+    "--strict-config",
+    "--cov=stn",
+    "--cov-branch",
+    "--cov-report=term-missing:skip-covered",
+    "--cov-report=html",
+    "--cov-report=xml",
+    "--cov-fail-under=80",
+]
+testpaths = ["tests"]
+python_files = "test_*.py"
+python_classes = "Test*"
+python_functions = "test_*"
+markers = [
+    "unit: marks tests as unit tests (fast, isolated)",
+    "integration: marks tests as integration tests (slower, may have dependencies)",
+    "slow: marks tests as slow (deselect with '-m \"not slow\"')",
+]
+
+[tool.coverage.run]
+source = ["stn"]
+branch = true
+parallel = true
+omit = [
+    "*/tests/*",
+    "*/test_*.py",
+    "*/__pycache__/*",
+    "*/site-packages/*",
+]
+
+[tool.coverage.report]
+precision = 2
+show_missing = true
+skip_covered = false
+exclude_lines = [
+    "pragma: no cover",
+    "def __repr__",
+    "def __str__",
+    "raise AssertionError",
+    "raise NotImplementedError",
+    "if __name__ == .__main__.:",
+    "if TYPE_CHECKING:",
+    "if typing.TYPE_CHECKING:",
+    "@overload",
+    "@abstractmethod",
+]
+
+[tool.coverage.html]
+directory = "htmlcov"
+
+[tool.coverage.xml]
+output = "coverage.xml"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"

tests/conftest.py

@@ -0,0 +1,145 @@
+import os
+import tempfile
+import shutil
+from pathlib import Path
+from typing import Generator, Dict, Any
+
+import pytest
+import numpy as np
+
+
+@pytest.fixture
+def temp_dir() -> Generator[Path, None, None]:
+    """Create a temporary directory for test files."""
+    temp_path = tempfile.mkdtemp()
+    yield Path(temp_path)
+    shutil.rmtree(temp_path)
+
+
+@pytest.fixture
+def mock_config() -> Dict[str, Any]:
+    """Provide a mock configuration dictionary for testing."""
+    return {
+        "batch_size": 32,
+        "learning_rate": 0.001,
+        "epochs": 10,
+        "image_size": (224, 224),
+        "num_classes": 10,
+        "device": "cpu",
+    }
+
+
+@pytest.fixture
+def sample_numpy_array() -> np.ndarray:
+    """Generate a sample numpy array for testing."""
+    np.random.seed(42)
+    return np.random.randn(10, 224, 224, 3).astype(np.float32)
+
+
+@pytest.fixture
+def sample_batch() -> Dict[str, np.ndarray]:
+    """Generate a sample batch of data for testing."""
+    np.random.seed(42)
+    batch_size = 4
+    height, width, channels = 28, 28, 1
+
+    return {
+        "images": np.random.randn(batch_size, height, width, channels).astype(np.float32),
+        "labels": np.random.randint(0, 10, size=(batch_size,)),
+        "theta": np.array([[1, 0, 0, 0, 1, 0]] * batch_size).astype(np.float32),
+    }
+
+
+@pytest.fixture
+def identity_theta() -> np.ndarray:
+    """Return identity transformation parameters."""
+    return np.array([1, 0, 0, 0, 1, 0], dtype=np.float32)
+
+
+@pytest.fixture
+def mock_tensorflow_session():
+    """Mock TensorFlow session for testing without GPU."""
+    try:
+        import tensorflow as tf
+        # Configure TensorFlow to use CPU only for tests
+        os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
+
+        if hasattr(tf, 'config'):
+            # TF 2.x
+            physical_devices = tf.config.list_physical_devices('GPU')
+            for device in physical_devices:
+                tf.config.set_memory_growth(device, True)
+
+        return tf.Session() if hasattr(tf, 'Session') else None
+    except ImportError:
+        pytest.skip("TensorFlow not installed")
+
+
+@pytest.fixture(autouse=True)
+def cleanup_tensorflow():
+    """Clean up TensorFlow resources after each test."""
+    yield
+    try:
+        import tensorflow as tf
+        if hasattr(tf, 'keras'):
+            tf.keras.backend.clear_session()
+        elif hasattr(tf, 'reset_default_graph'):
+            tf.reset_default_graph()
+    except ImportError:
+        pass
+
+
+@pytest.fixture
+def sample_image_path(temp_dir: Path) -> Path:
+    """Create a sample image file for testing."""
+    image_path = temp_dir / "test_image.npy"
+    np.save(image_path, np.random.randn(224, 224, 3))
+    return image_path
+
+
+@pytest.fixture
+def mock_model_weights(temp_dir: Path) -> Path:
+    """Create mock model weights file."""
+    weights_path = temp_dir / "model_weights.npy"
+    weights = {
+        "conv1": np.random.randn(3, 3, 3, 32),
+        "conv2": np.random.randn(3, 3, 32, 64),
+        "fc1": np.random.randn(1024, 256),
+        "fc2": np.random.randn(256, 6),
+    }
+    np.save(weights_path, weights)
+    return weights_path
+
+
+@pytest.fixture(scope="session")
+def test_data_dir() -> Path:
+    """Return the path to test data directory."""
+    return Path(__file__).parent / "test_data"
+
+
+def pytest_configure(config):
+    """Configure pytest with custom settings."""
+    # Add custom markers descriptions
+    config.addinivalue_line(
+        "markers", "unit: mark test as a unit test"
+    )
+    config.addinivalue_line(
+        "markers", "integration: mark test as an integration test"
+    )
+    config.addinivalue_line(
+        "markers", "slow: mark test as slow running"
+    )
+
+
+def pytest_collection_modifyitems(config, items):
+    """Modify test collection to add markers based on test location."""
+    for item in items:
+        # Add markers based on test file location
+        if "unit" in str(item.fspath):
+            item.add_marker(pytest.mark.unit)
+        elif "integration" in str(item.fspath):
+            item.add_marker(pytest.mark.integration)
+
+        # Mark tests that have 'slow' in their name
+        if "slow" in item.nodeid:
+            item.add_marker(pytest.mark.slow)

tests/test_setup_validation.py

@@ -0,0 +1,125 @@
+"""Validation tests to ensure the testing infrastructure is properly set up."""
+import sys
+from pathlib import Path
+
+import pytest
+import numpy as np
+
+
+class TestSetupValidation:
+    """Test class to validate the testing infrastructure."""
+
+    @pytest.mark.unit
+    def test_pytest_installed(self):
+        """Verify pytest is installed and importable."""
+        assert pytest.__version__
+
+    @pytest.mark.unit
+    def test_coverage_plugin_available(self):
+        """Verify pytest-cov plugin is available."""
+        import pytest_cov
+        assert pytest_cov
+
+    @pytest.mark.unit
+    def test_mock_plugin_available(self):
+        """Verify pytest-mock plugin is available."""
+        import pytest_mock
+        assert pytest_mock
+
+    @pytest.mark.unit
+    def test_project_importable(self):
+        """Verify the stn package can be imported."""
+        try:
+            import stn
+            assert stn
+        except ImportError as e:
+            if "tensorflow" in str(e):
+                pytest.skip("TensorFlow not installed (optional dependency)")
+            else:
+                raise
+
+    @pytest.mark.unit
+    def test_fixtures_available(self, temp_dir, mock_config, sample_numpy_array):
+        """Verify custom fixtures are available and working."""
+        assert temp_dir.exists()
+        assert isinstance(mock_config, dict)
+        assert isinstance(sample_numpy_array, np.ndarray)
+
+    @pytest.mark.unit
+    def test_markers_configured(self, request):
+        """Verify custom markers are properly configured."""
+        markers = [marker.name for marker in request.node.iter_markers()]
+        assert 'unit' in markers
+
+    @pytest.mark.integration
+    def test_integration_marker(self, request):
+        """Test that integration marker works."""
+        markers = [marker.name for marker in request.node.iter_markers()]
+        assert 'integration' in markers
+
+    @pytest.mark.slow
+    @pytest.mark.unit
+    def test_slow_marker(self, request):
+        """Test that slow marker works."""
+        markers = [marker.name for marker in request.node.iter_markers()]
+        assert 'slow' in markers
+        assert 'unit' in markers
+
+    @pytest.mark.unit
+    def test_temp_dir_fixture(self, temp_dir):
+        """Test temporary directory fixture creates and cleans up properly."""
+        test_file = temp_dir / "test.txt"
+        test_file.write_text("test content")
+        assert test_file.exists()
+        assert test_file.read_text() == "test content"
+
+    @pytest.mark.unit
+    def test_sample_batch_fixture(self, sample_batch):
+        """Test sample batch fixture provides correct data structure."""
+        assert 'images' in sample_batch
+        assert 'labels' in sample_batch
+        assert 'theta' in sample_batch
+
+        assert sample_batch['images'].shape == (4, 28, 28, 1)
+        assert sample_batch['labels'].shape == (4,)
+        assert sample_batch['theta'].shape == (4, 6)
+
+    @pytest.mark.unit
+    def test_identity_theta_fixture(self, identity_theta):
+        """Test identity theta fixture returns correct transformation."""
+        expected = np.array([1, 0, 0, 0, 1, 0], dtype=np.float32)
+        np.testing.assert_array_equal(identity_theta, expected)
+
+    @pytest.mark.unit
+    def test_coverage_configured(self):
+        """Verify coverage is properly configured."""
+        # This test will pass if coverage is running
+        # The actual verification happens when running with coverage
+        assert True
+
+    @pytest.mark.unit
+    @pytest.mark.parametrize("value,expected", [
+        (1, 1),
+        (2, 4),
+        (3, 9),
+    ])
+    def test_parametrize_works(self, value, expected):
+        """Verify pytest parametrize decorator works."""
+        assert value ** 2 == expected
+
+
+@pytest.mark.unit
+def test_module_level_test():
+    """Test that module-level tests work."""
+    assert True
+
+
+def test_poetry_scripts_configured():
+    """Test that poetry run test and poetry run tests commands are configured."""
+    pyproject_path = Path(__file__).parent.parent / "pyproject.toml"
+    assert pyproject_path.exists()
+
+    content = pyproject_path.read_text()
+    assert "[tool.poetry.scripts]" in content
+    assert 'test = "pytest:main"' in content
+    assert 'tests = "pytest:main"' in content