python-pytest-patterns

Pytest fixtures provide reusable test setup through function-scoped, session-scoped, or module-scoped decorators. Organize fixtures in conftest.py files at project or package levels to share them across tests, enabling dependency injection and reducing duplication while maintaining test isolation.

Pytest parametrize decorator lets you run a single test function across multiple input sets, reducing code duplication and improving coverage. Define parameters inline with @pytest.mark.parametrize or use indirect parametrization with fixtures for complex scenarios.

Pytest-mock integration provides the mocker fixture for patching functions, classes, and modules without manual teardown. Use mocker.patch() to replace dependencies, control return values, and assert calls were made as expected while keeping tests isolated from external systems.

Pytest supports async testing through pytest-asyncio plugin, allowing you to mark async test functions with @pytest.mark.asyncio and use await within tests. This enables testing of async fixtures, coroutines, and event-driven code while maintaining standard pytest patterns.

Pytest integrates with pytest-cov to generate coverage reports during test runs. Export results to JSON or XML formats for CI pipeline consumption, set coverage thresholds to enforce quality gates, and generate reports for unit, integration, and end-to-end test suites.

These patterns are designed for pytest 7.0+ and Python 3.9+, ensuring compatibility with modern async features, fixture improvements, and parametrization enhancements. Verify your environment meets these minimums before applying advanced patterns.