celery-asyncio

Distributed task queue with native asyncio support. An asyncio-native rewrite of Celery, one of the most widely used distributed task systems in the Python ecosystem.

This project is exploratory. It is not affiliated with or endorsed by the Celery project. If you're looking for the official production-ready task queue, use the original Celery.

Features

• Native asyncio worker with hybrid thread pool for mixed async/sync workloads
• async def tasks run directly on the event loop, no thread overhead
• Sync tasks run in a thread pool alongside async tasks in the same worker
• Valkey/Redis and AMQP transports via kombu-asyncio
• Celery Flower works out of the box for monitoring
• Django 6.0 Tasks support via django-tasks-celery
• Targeting Python 3.14t free-threading for true parallelism

Quick Start

from celery import Celery

app = Celery("tasks", broker="redis://localhost:6379/0")

@app.task
async def add(x, y):
    return x + y

@app.task
def multiply(x, y):
    return x * y

celery -A tasks worker --loglevel=info -E

Both add (async) and multiply (sync) run in the same worker.

Documentation

Full documentation at oliverhaas.github.io/celery-asyncio

Requirements

• Python 3.14+
• kombu-asyncio 6.0+
• Valkey 8+ or Redis 7+ or RabbitMQ 4+

Attribution

This project is an asyncio rewrite of Celery by Ask Solem, Asif Saif Uddin & contributors. Much of the utility layer (celery/utils/, celery/loaders/, celery/bin/), scheduling (celery/schedules.py, celery/beat.py), data structures (celery/canvas.py, celery/result.py, celery/states.py), and app framework (celery/app/) are carried over from the original with targeted modifications. The worker event loop (celery/worker/loops.py), asyncio pool (celery/concurrency/aio.py), promise system (celery/utils/promises.py), and timer/hub (celery/utils/scheduling.py) were written from scratch. Files containing substantial original Celery code are marked with a header comment.

License

BSD-3-Clause