python-testing-patterns

pytest is a framework for writing and running Python tests. Start by installing pytest, then create test files with functions prefixed by `test_`, use fixtures for setup/teardown, and run `pytest` to execute your suite. Fixtures provide reusable test data and configuration, while the AAA pattern (Arrange, Act, Assert) structures individual tests for clarity and maintainability.

Use `unittest.mock` to isolate units under test by simulating external services and APIs. Mocking replaces real objects with test doubles, letting you verify interactions and handle failure scenarios without calling live endpoints. This ensures tests run fast, stay deterministic, and don't depend on external systems.

Yes. pytest supports async test functions and fixtures through plugins and async/await syntax. You can write coroutine-based tests that properly handle async setup, teardown, and execution, enabling you to test concurrent code and async libraries without blocking or race conditions.

Parameterized tests run the same test logic across different input sets using `pytest.mark.parametrize`. This reduces duplication, improves coverage of edge cases, and makes it easy to add new scenarios without writing separate test functions.

Unit tests verify individual functions in isolation using mocks. Integration tests check how components work together with real or partially mocked dependencies. Functional tests validate end-to-end workflows against actual system behavior. pytest supports all three patterns within a single framework.

Test coverage identifies which lines of code are executed by tests, measured as a percentage. Use coverage tools with pytest to generate reports showing untested code paths. High coverage reduces bugs, but meaningful coverage requires testing actual behavior, not just code execution.