pytest-asyncio
The pytest plugin that lets you write and run async/await test functions and fixtures directly.
Repository Health
Technical Analysis
pytest-asyncio is a pytest plugin that makes it possible to write coroutine test functions and have pytest execute them correctly — no manual event-loop boilerplate required. Marking a test @pytest.mark.asyncio (or enabling the asyncio_mode = auto config option) lets you await code inside the test body just like you would in application code, and pytest-asyncio takes care of driving the event loop and running the coroutine to completion.
Maintained under the pytest-dev organization alongside pytest itself, it’s the de facto standard way to test asyncio-based Python code with pytest, supporting async fixtures with configurable scope (function, module, session), parametrized event loops, and custom loop factories. It explicitly does not support unittest.TestCase subclasses, pointing users instead to unittest.IsolatedAsyncioTestCase or an async-aware test framework for that case.
What You Get
- pytest.mark.asyncio to mark individual coroutine functions as pytest test items
- An asyncio_mode = auto configuration option that treats every async def test/fixture as async automatically, without per-test markers
- Async fixtures with configurable scope (function, class, module, session) via @pytest_asyncio.fixture
- Support for custom event loop factories and parametrized event loop configurations across a test session
- Integration with pytest’s existing fixture, parametrization, and collection machinery so async tests behave like any other pytest test
Common Use Cases
- Unit and integration testing of asyncio-based application code (async web frameworks, async DB clients, async task queues)
- Testing async context managers and async generators used as pytest fixtures with proper setup/teardown scoping
- Running the same async test logic against multiple event loop configurations via parametrization
- Migrating a codebase from manual asyncio.run()-wrapped tests to native async def test functions
Under The Hood
Architecture — The entire plugin lives in a single, focused module, pytest_asyncio/plugin.py (1,140 lines), which hooks into pytest’s collection and fixture machinery to detect async def test functions and fixtures, wrap them in an event loop runner, and manage loop lifecycle/scope so fixtures and tests sharing a scope share the same running loop. __init__.py exposes the small public surface (fixture, marker registration) that users actually import.
Tech Stack — Pure Python with pytest as its only required dependency (plus typing-extensions on older Pythons), designed to work with any asyncio-based code without also depending on a specific async framework (no forced dependency on Tornado, Trio, etc.) — it strictly targets Python’s built-in asyncio.
Code Quality — Exceptionally thorough test suite: 37+ test modules covering markers, fixture scopes (tests/modes/), event loop factories, subprocess handling, doctest support, Hypothesis-based property tests, and even task-cleanup edge cases — unusually deep coverage for a plugin of this size, backed by Codecov reporting and CI across supported Python versions. py.typed is shipped, signaling committed type-hint support for consumers.
API Design — The @pytest.mark.asyncio / asyncio_mode=auto split is a deliberate ergonomics choice: teams can opt into per-test explicitness or blanket-enable async support project-wide once they’ve standardized on it. The README is upfront about a real limitation (no support for unittest.TestCase subclasses) rather than leaving users to discover it via a confusing failure, which meaningfully shortens the debugging loop for newcomers.
Used by 49 apps in this directory
Docs
CMS · File Storage
Open-source collaborative knowledge platform with real-time editing, AI writing tools, and full self-hosting control — built by the French and German governments.
Dragonfly
Databases · Developer Tools · Devops
A modern Redis and Memcached replacement engineered for multi-core servers — delivering 25x more throughput, better cache hit rates, and up to 80% lower memory consumption with full API compatibility.
Fern
Developer Tools
Fern turns a single OpenAPI, AsyncAPI, or Protobuf definition into type-safe SDKs for nine languages and a hosted API documentation site, all from one CLI and one source of truth.
Firecrawl
AI Development · Developer Tools
Turn any website into clean, LLM-ready data with a single API call — no proxy headaches, no scraping complexity.
Flowfile
Data Engineering
Visual ETL that compiles to Polars — build pipelines on a canvas, export as standalone Python, and run anywhere without platform lock-in.
Hatchet
AI Development · Automation · Developer Tools
A Postgres-backed orchestration engine for background tasks, AI agents, and durable workflows that replaces Redis queues and multi-datastore durable execution platforms with a single self-hostable service.
headroom
AI Development · Developer Tools
Compress everything your AI agent reads — tool outputs, logs, RAG chunks, and files — before it reaches the LLM, achieving 60–95% fewer tokens with the same answers.
highlight.io
Analytics · Developer Tools · Monitoring
Open-source full-stack monitoring that unifies session replay, error tracking, logging, and distributed tracing so you can stop context-switching between tools.
Hippo
AI Agents · AI Memory
A biologically-inspired memory layer for AI coding agents — memories decay by default and strengthen through use, modeled on the hippocampus, with zero runtime dependencies and a SQLite backbone.