pytest-testing

Organize pytest tests by placing shared fixtures in a conftest.py file at the root or test directory. This allows you to define fixture scopes for function, module, class, or session levels, making reusable test setup available across your Python project without duplication.

Parametrize tests using the pytest.mark.parametrize decorator to feed multiple data sets into a single test function. This data-driven testing approach eliminates duplication by automatically generating distinct test cases for each input combination you specify.

Mock external dependencies in pytest by using unittest.mock tools like MagicMock and patch, or apply monkeypatch to modify attributes and environment variables. These approaches isolate tests from HTTP, database, and filesystem interactions for reliable execution.

Measure code coverage in pytest by integrating the pytest-cov plugin. Run pytest from your project root to execute tests and generate coverage reports, enforcing code coverage thresholds to ensure your Python project maintains adequate test coverage.

This pytest testing skill does not support framework-specific test types like Django TestCase, FastAPI TestClient, or Flask test client. It focuses on stack-agnostic pytest patterns including fixtures, parametrization, mocks, and coverage measurement.

Test file I/O operations safely in pytest using the tmp_path utility fixture. It creates a unique temporary directory for each test invocation, allowing you to read and write files during testing without modifying the real filesystem.