pytest-flask is a pytest plugin that provides fixtures and helpers for testing Flask applications. It is a library/plugin, not a standalone application. When installed, it registers itself via the `pytest11` entry point and automatically provides fixtures such as `client`, `client_class`, `config`, `live_server`, and `accept_*` headers. It also installs autouse fixtures that push a Flask request context during tests (so `url_for`, `session`, and `request` work without context managers), apply `pytest.mark.options` to the app config, and monkeypatch the app's response class to add JSON-aware comparison helpers. Architecturally, the plugin is a thin layer over pytest's fixture system and Flask's testing utilities. The core entry point is `src/pytest_flask/plugin.py`, which registers CLI options (`--live-server-port`, `--live-server-host`, `--live-server-wait`, `--no-start-live-server`, etc.) and markers. The `live_server` fixture (in `fixtures.py`) uses the `LiveServer` class (in `live_server.py`) to run the Flask app in a separate multiprocessing process, wait for TCP readiness via a socket probe, and shut down cleanly with SIGINT. The plugin depends only on pytest, Flask, and Werkzeug, plus the Python standard library. The codebase is small, well-typed, and thoroughly tested with a test suite that uses pytest's `pytester` to validate plugin behavior in isolated subprocesses. It supports Python 3.8-3.12 and is compatible with Flask 3.x. The project is actively maintained, with recent commits and CI covering multiple OSes and Python versions. It is not a data research repository; it is a developer tool for testing Flask applications.
This repository is a curated list of awesome Python testing resources, organized by category (assertions, BDD, code coverage, fake data, fixtures, mocking, property-based testing, etc.). It is not a software application or data pipeline; it is a reference list of tools, libraries, and resources for Python testing. The repository contains no executable code; its primary content is a README.md file with links and brief descriptions. The CI workflows ensure link validity and spelling. It is a well-maintained, community-driven resource that serves as a comprehensive directory for Python testing tools and practices.