Implement Python Testing Patterns

Covers pytest-based Python testing across ten fundamental and advanced patterns, each with runnable code: basic pytest tests using the AAA (Arrange-Act-Assert) structure, fixtures for setup and teardown including database fixtures, parameterized tests via pytest.mark.parametrize and pytest.param for special cases, mocking external calls with unittest.mock (Mock, patch, and MagicMock demonstrating a decorator-style @patch and call-argument assertions against a requests-based APIClient), exception testing with pytest.raises including message matching and exception-info inspection, async code testing, monkeypatch for environment and attribute patching, temporary files and directories via pytest's tmp_path, custom fixtures and shared conftest.py setup including parametrized fixtures, and property-based testing with Hypothesis - @given with strategies like st.text, st.integers, and st.lists to assert properties such as double-reversal returning the original string, addition commutativity, and sorted-list invariants. Documents test-type classification (unit, integration, end-to-end) and isolation principles, a recommended test-directory layout (test_unit/, test_integration/, and test_e2e/ under a shared conftest.py), naming conventions distinguishing good from bad test names, pytest markers for selectively running or skipping slow and integration tests, coverage reporting with threshold enforcement and missing-line reporting, database-model testing, a GitHub Actions CI workflow, and pytest.ini or pyproject.toml configuration.

Use it when writing unit tests for Python functions and classes, setting up fixtures and mocks, parameterizing test cases, testing async code or exceptions, configuring pytest for CI, or adopting property-based testing. Skip it for anything unrelated to Python testing or outside this scope.

Input is the Python code under test and its testing need - a unit test, a fixture, a mock, a parameterized case, or a property; output is the matching pytest test file or configuration, ready to drop into a tests/ directory structured by unit, integration, and end-to-end layers.

Built on pytest with unittest.mock for mocking, Hypothesis for property-based testing, and pytest-cov for coverage reporting with HTML output and a configurable fail-under threshold. CI integration via a GitHub Actions workflow that runs the suite on push. Configuration lives in pytest.ini or pyproject.toml, covering marker registration and coverage settings in one place.

Python engineers building or extending a test suite who need concrete, runnable pytest patterns - from basic fixtures through mocking, parametrization, and property-based testing - rather than pytest documentation alone. Also useful for teams standardizing test organization: the recommended unit/integration/e2e directory split and naming conventions give a shared structure to review new tests against.