feat: Set up comprehensive Python testing infrastructure

.gitignore

@@ -1 +1,71 @@
-data/preprocessed/
+data/preprocessed/
+
+# Testing
+.pytest_cache/
+.coverage
+htmlcov/
+coverage.xml
+.tox/
+.nox/
+
+# Claude Code settings
+.claude/*
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# PyTorch
+*.pth
+*.pt
+
+# Logs
+*.log

pyproject.toml

@@ -0,0 +1,91 @@
+[tool.poetry]
+name = "gvae-project"
+version = "0.1.0"
+description = "Graph Variational Autoencoder project"
+authors = ["Your Name <your.email@example.com>"]
+readme = "README.md"
+packages = [{include = "."}]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+torch = ">=1.6.0,<3.0.0"
+torch-geometric = ">=1.7.0"
+pandas = "^2.0.0"
+numpy = "^1.20.0"
+tqdm = "^4.60.0"
+deepchem = "^2.7.0"
+
+[tool.poetry.group.test.dependencies]
+pytest = "^7.4.0"
+pytest-cov = "^4.1.0"
+pytest-mock = "^3.11.0"
+
+# Poetry scripts can be used but for simplicity, use: poetry run pytest
+# [tool.poetry.scripts]
+# test = "pytest:main"
+# tests = "pytest:main"
+
+[tool.pytest.ini_options]
+minversion = "7.0"
+addopts = [
+    "-ra",
+    "--strict-markers",
+    "--strict-config",
+    "--cov=.",
+    "--cov-report=term-missing",
+    "--cov-report=html:htmlcov",
+    "--cov-report=xml:coverage.xml",
+    "--cov-fail-under=80",
+]
+testpaths = ["tests"]
+python_files = ["test_*.py", "*_test.py"]
+python_functions = ["test_*"]
+python_classes = ["Test*"]
+markers = [
+    "unit: marks tests as unit tests (fast, isolated)",
+    "integration: marks tests as integration tests (slower, may use external resources)",
+    "slow: marks tests as slow running",
+]
+filterwarnings = [
+    "error",
+    "ignore::UserWarning",
+    "ignore::DeprecationWarning",
+]
+
+[tool.coverage.run]
+source = ["."]
+omit = [
+    "tests/*",
+    ".*/*",
+    "*/site-packages/*",
+    "*/__pycache__/*",
+    "setup.py",
+]
+branch = true
+
+[tool.coverage.report]
+exclude_lines = [
+    "pragma: no cover",
+    "def __repr__",
+    "if self.debug:",
+    "if settings.DEBUG",
+    "raise AssertionError",
+    "raise NotImplementedError",
+    "if 0:",
+    "if __name__ == .__main__.:",
+    "class .*\\bProtocol\\):",
+    "@(abc\\.)?abstractmethod",
+]
+ignore_errors = true
+show_missing = true
+precision = 2
+
+[tool.coverage.html]
+directory = "htmlcov"
+
+[tool.coverage.xml]
+output = "coverage.xml"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

tests/conftest.py

@@ -0,0 +1,147 @@
+"""Shared pytest fixtures for the test suite."""
+
+import tempfile
+import shutil
+from pathlib import Path
+from unittest.mock import Mock, patch
+import pytest
+import torch
+
+
+@pytest.fixture
+def temp_dir():
+    """Create a temporary directory for test files."""
+    temp_dir = tempfile.mkdtemp()
+    yield Path(temp_dir)
+    shutil.rmtree(temp_dir)
+
+
+@pytest.fixture
+def temp_file(temp_dir):
+    """Create a temporary file for testing."""
+    temp_file = temp_dir / "test_file.txt"
+    temp_file.write_text("test content")
+    return temp_file
+
+
+@pytest.fixture
+def sample_config():
+    """Provide a sample configuration dictionary for testing."""
+    return {
+        "model": {
+            "hidden_dim": 128,
+            "latent_dim": 64,
+            "num_layers": 3,
+        },
+        "training": {
+            "learning_rate": 0.001,
+            "batch_size": 32,
+            "num_epochs": 100,
+        },
+        "data": {
+            "dataset_name": "test_dataset",
+            "num_nodes": 1000,
+        }
+    }
+
+
+@pytest.fixture
+def mock_torch_device():
+    """Mock torch device for consistent testing."""
+    with patch('torch.cuda.is_available', return_value=False):
+        yield torch.device('cpu')
+
+
+@pytest.fixture
+def sample_tensor():
+    """Create a sample tensor for testing."""
+    return torch.randn(10, 5)
+
+
+@pytest.fixture
+def sample_graph_data():
+    """Create sample graph data for testing."""
+    # Simple graph with 5 nodes and some edges
+    edge_index = torch.tensor([[0, 1, 1, 2, 2, 3, 3, 4], 
+                               [1, 0, 2, 1, 3, 2, 4, 3]], dtype=torch.long)
+    x = torch.randn(5, 3)  # 5 nodes with 3 features each
+    return {
+        'x': x,
+        'edge_index': edge_index,
+        'num_nodes': 5,
+        'num_edges': edge_index.size(1)
+    }
+
+
+@pytest.fixture
+def mock_model():
+    """Create a mock model for testing."""
+    mock = Mock()
+    mock.forward.return_value = (torch.randn(5, 2), torch.randn(5, 2))  # mean, log_var
+    mock.encode.return_value = torch.randn(5, 2)
+    mock.decode.return_value = torch.randn(5, 3)
+    mock.parameters.return_value = [torch.randn(10, 5, requires_grad=True)]
+    return mock
+
+
+@pytest.fixture
+def mock_optimizer():
+    """Create a mock optimizer for testing."""
+    mock = Mock()
+    mock.step.return_value = None
+    mock.zero_grad.return_value = None
+    return mock
+
+
+@pytest.fixture
+def mock_dataset():
+    """Create a mock dataset for testing."""
+    mock = Mock()
+    mock.__len__.return_value = 100
+    mock.__getitem__.return_value = {
+        'x': torch.randn(10, 3),
+        'edge_index': torch.tensor([[0, 1], [1, 2]], dtype=torch.long).t()
+    }
+    return mock
+
+
+@pytest.fixture(autouse=True)
+def set_random_seeds():
+    """Set random seeds for reproducible testing."""
+    torch.manual_seed(42)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed(42)
+        torch.cuda.manual_seed_all(42)
+
+
+@pytest.fixture
+def capture_logs(caplog):
+    """Fixture to capture and return logs for testing."""
+    return caplog
+
+
+@pytest.fixture
+def mock_file_operations():
+    """Mock file operations for testing without actual I/O."""
+    with patch('builtins.open', mock_open(read_data="test data")):
+        with patch('os.path.exists', return_value=True):
+            with patch('os.makedirs'):
+                yield
+
+
+def mock_open(read_data=""):
+    """Helper function to create a mock open function."""
+    from unittest.mock import mock_open as _mock_open
+    return _mock_open(read_data=read_data)
+
+
+@pytest.fixture
+def isolated_environment(monkeypatch, temp_dir):
+    """Create an isolated environment for testing."""
+    # Change to temporary directory
+    monkeypatch.chdir(temp_dir)
+
+    # Set environment variables
+    monkeypatch.setenv("TEST_MODE", "true")
+
+    yield temp_dir