What problem does it solve?
Writing, organizing, and running Python tests can be error-prone and slow to iterate on; this skill provides clear patterns and guidance to author reliable unit, integration, and async tests so you catch regressions early and ship with confidence.
Core Features & Use Cases
- Provides guidance on test discovery, naming conventions, and test structure for predictable test runs.
- Explains fixtures, scopes, and conftest.py usage for reusable setup and teardown in unit and integration tests.
- Covers async testing patterns, mocking strategies for synchronous and asynchronous code, parameterized tests for data-driven cases, and coverage reporting for CI pipelines.
Quick Start
Run the project's test suite with verbose output and coverage by invoking the provided run-tests script or running pytest -v --cov=src against the tests directory.