PubMed MCP Server

# PubMed MCP Server Test Suite This directory contains comprehensive unit tests for the PubMed MCP Server. ## Test Structure ``` tests/ ├── __init__.py # Test package marker ├── conftest.py # Pytest fixtures and configuration ├── test_utils.py # Tests for utility functions and rate limiting ├── test_models.py # Tests for data models (Pydantic models) ├── test_pubmed_client.py # Tests for PubMed API client ├── test_tool_handler.py # Tests for MCP tool handling └── README.md # This file ``` ## Running Tests ### Prerequisites Install the test dependencies: ```bash pip install -r requirements.txt ``` This will install pytest and related testing packages. ### Basic Test Execution Run all tests: ```bash python run_tests.py ``` Or use pytest directly: ```bash pytest tests/ ``` ### Advanced Test Options Run specific test files: ```bash python run_tests.py test_utils.py python run_tests.py test_pubmed_client.py ``` Run with coverage reporting: ```bash python run_tests.py --coverage ``` Run only fast tests (skip slow integration tests): ```bash python run_tests.py --markers "not slow" ``` Run in verbose mode: ```bash pytest tests/ -v ``` Run specific test methods: ```bash pytest tests/test_utils.py::TestRateLimiter::test_rate_limiter_initialization ``` ### Test Categories Tests are organized into several categories: 1. **Unit Tests** (`test_*.py`): Test individual components in isolation 2. **Integration Tests**: Test component interactions (marked with `@pytest.mark.integration`) 3. **Slow Tests**: Tests that take longer to run (marked with `@pytest.mark.slow`) ## Test Coverage The test suite aims to cover: - ✅ **Rate Limiting**: Ensures the rate limiting decorator works correctly - ✅ **Caching**: Tests cache functionality and TTL behavior - ✅ **PubMed API Client**: Tests API interactions with mocked responses - ✅ **Data Models**: Tests Pydantic model validation and serialization - ✅ **Tool Handling**: Tests MCP tool request handling - ✅ **Error Handling**: Tests exception handling and error responses - ✅ **Edge Cases**: Tests with invalid inputs, empty results, etc. ## Key Test Fixes This test suite addresses several issues found in the original code: ### 1. Rate Limiting Decorator Issue **Problem**: The `@rate_limited` decorator was being used incorrectly, causing the error: ``` rate_limited.<locals>.decorator() takes 1 positional argument but 3 were given ``` **Solution**: The tests verify that rate limiting is now applied correctly using direct calls to `await self.rate_limiter.acquire()` instead of the problematic decorator usage. ### 2. Comprehensive Mocking The test suite uses comprehensive mocking to: - Avoid actual API calls during testing - Test error scenarios safely - Ensure predictable test results ### 3. Async Testing All async functions are properly tested using `pytest-asyncio` with the `@pytest.mark.asyncio` decorator. ## Test Fixtures Key fixtures provided in `conftest.py`: - `mock_config`: Test configuration - `mock_rate_limiter`: Mocked rate limiter - `mock_cache_manager`: Mocked cache - `mock_pubmed_client`: Mocked PubMed client - `sample_article`: Sample article data - `sample_search_result`: Sample search results - `mock_httpx_response`: Mocked HTTP responses ## Writing New Tests When adding new tests: 1. **Use appropriate fixtures**: Leverage existing fixtures for consistency 2. **Mock external dependencies**: Don't make real API calls 3. **Test both success and error cases**: Include negative test scenarios 4. **Use descriptive test names**: Test names should explain what they test 5. **Add markers for slow tests**: Use `@pytest.mark.slow` for time-consuming tests Example test structure: ```python @pytest.mark.asyncio async def test_new_feature(mock_client, sample_data): """Test description of what this test verifies.""" # Arrange mock_client.some_method.return_value = sample_data # Act result = await function_under_test() # Assert assert result.success is True mock_client.some_method.assert_called_once() ``` ## Continuous Integration These tests are designed to run in CI/CD environments. The `run_tests.py` script provides: - Exit codes for CI systems - Parallel test execution (with `--parallel`) - Coverage reporting - Dependency installation ## Debugging Tests For debugging failing tests: 1. **Run with verbose output**: `pytest -v -s` 2. **Run specific failing test**: `pytest tests/test_file.py::test_function` 3. **Use pytest debugger**: `pytest --pdb` 4. **Check logs**: Tests include logging output for debugging ## Performance Testing Some tests include performance checks: - Rate limiting timing tests - Cache performance tests - API response time validation Run only performance tests: ```bash pytest tests/ -m "performance" ``` ## Common Issues ### Import Errors If you see import errors, ensure you're running tests from the project root: ```bash cd pubmed-mcp python run_tests.py ``` ### Async Event Loop Issues If you encounter event loop issues, ensure `pytest-asyncio` is installed and `asyncio_mode = auto` is set in `pytest.ini`. ### Mock Object Issues If mocks aren't working as expected, check that you're using the correct mock specifications and return values in the test fixtures.