pytest

To write reliable Python tests, use pytest to apply composable scoped fixtures for setup and teardown, and multiply test cases using parametrization. This provides reusable test structures and consistent execution across unit and integration scenarios.

Testing asynchronous Python code requires integrating the pytest-asyncio plugin. It allows the test runner to properly execute and await async test functions, preventing common failure modes like execution hangs and ensuring async logic is validated correctly.

Measuring test coverage and running tests in parallel involves using pytest's plugin-based enhancements. Apply the pytest-cov plugin for coverage measurement and utilize parallel execution plugins to speed up test suite runs while maintaining strict reporting.

Fixture scoping issues cause test failures when setup and teardown lifecycles mismatch test isolation needs. Resolve this by adjusting fixture scopes to ensure consistent state across test boundaries and following pytest 9 strict marker and configuration practices.

Yes, you can use unittest.mock or the mocker fixture for mocking in pytest test suites. This enables practical real-world testing by substituting dependencies, validating interaction calls, and isolating the code under test without modifying external systems.