:Version: 3.1.13 (Cipater) :Web: http://celeryproject.org/ :Download: http://pypi.python.org/pypi/celery/ :Source: http://github.com/celery/celery/ :Keywords: task queue, job queue, asynchronous, async, rabbitmq, amqp, redis, python, webhooks, queue, distributed -- What is a Task Queue? ===================== Task queues are used as a mechanism to distribute work across threads or machines. A task queue's input is a unit of work, called a task, dedicated worker processes then constantly monitor the queue for new work to perform. Celery communicates via messages, usually using a broker to mediate between clients and workers. To initiate a task a client puts a message on the queue, the broker then delivers the message to a worker. A Celery system can consist of multiple workers and brokers, giving way to high availability and horizontal scaling. Celery is a library written in Python, but the protocol can be implemented in any language. So far there's RCelery_ for the Ruby programming language, and a `PHP client`, but language interoperability can also be achieved by using webhooks. .. _RCelery: http://leapfrogdevelopment.github.com/rcelery/ .. _`PHP client`: https://github.com/gjedeer/celery-php .. _`using webhooks`: http://docs.celeryproject.org/en/latest/userguide/remote-tasks.html What do I need? =============== Celery version 3.0 runs on, - Python (2.5, 2.6, 2.7, 3.2, 3.3) - PyPy (1.8, 1.9) - Jython (2.5, 2.7). This is the last version to support Python 2.5, and from Celery 3.1, Python 2.6 or later is required. The last version to support Python 2.4 was Celery series 2.2. *Celery* is usually used with a message broker to send and receive messages. The RabbitMQ, Redis transports are feature complete, but there's also experimental support for a myriad of other solutions, including using SQLite for local development. *Celery* can run on a single machine, on multiple machines, or even across datacenters. Get Started =========== If this is the first time you're trying to use Celery, or you are new to Celery 3.0 coming from previous versions then you should read our getting started tutorials: - `First steps with Celery`_ Tutorial teaching you the bare minimum needed to get started with Celery. - `Next steps`_ A more complete overview, showing more features. .. _`First steps with Celery`: http://docs.celeryproject.org/en/latest/getting-started/first-steps-with-celery.html .. _`Next steps`: http://docs.celeryproject.org/en/latest/getting-started/next-steps.html Celery is… ========== - **Simple** Celery is easy to use and maintain, and does *not need configuration files*. It has an active, friendly community you can talk to for support, including a `mailing-list`_ and and an IRC channel. Here's one of the simplest applications you can make:: from celery import Celery app = Celery('hello', broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' - **Highly Available** Workers and clients will automatically retry in the event of connection loss or failure, and some brokers support HA in way of *Master/Master* or *Master/Slave* replication. - **Fast** A single Celery process can process millions of tasks a minute, with sub-millisecond round-trip latency (using RabbitMQ, py-librabbitmq, and optimized settings). - **Flexible** Almost every part of *Celery* can be extended or used on its own, Custom pool implementations, serializers, compression schemes, logging, schedulers, consumers, producers, autoscalers, broker transports and much more. It supports… ============ - **Message Transports** - RabbitMQ_, Redis_, - MongoDB_ (experimental), Amazon SQS (experimental), - CouchDB_ (experimental), SQLAlchemy_ (experimental), - Django ORM (experimental), `IronMQ`_ - and more… - **Concurrency** - Prefork, Eventlet_, gevent_, threads/single threaded - **Result Stores** - AMQP, Redis - memcached, MongoDB - SQLAlchemy, Django ORM - Apache Cassandra, IronCache - **Serialization** - *pickle*, *json*, *yaml*, *msgpack*. - *zlib*, *bzip2* compression. - Cryptographic message signing. .. _`Eventlet`: http://eventlet.net/ .. _`gevent`: http://gevent.org/ .. _RabbitMQ: http://rabbitmq.com .. _Redis: http://redis.io .. _MongoDB: http://mongodb.org .. _Beanstalk: http://kr.github.com/beanstalkd .. _CouchDB: http://couchdb.apache.org .. _SQLAlchemy: http://sqlalchemy.org .. _`IronMQ`: http://iron.io Framework Integration ===================== Celery is easy to integrate with web frameworks, some of which even have integration packages: +--------------------+------------------------+ | `Django`_ | not needed | +--------------------+------------------------+ | `Pyramid`_ | `pyramid_celery`_ | +--------------------+------------------------+ | `Pylons`_ | `celery-pylons`_ | +--------------------+------------------------+ | `Flask`_ | not needed | +--------------------+------------------------+ | `web2py`_ | `web2py-celery`_ | +--------------------+------------------------+ | `Tornado`_ | `tornado-celery`_ | +--------------------+------------------------+ The integration packages are not strictly necessary, but they can make development easier, and sometimes they add important hooks like closing database connections at ``fork``. .. _`Django`: http://djangoproject.com/ .. _`Pylons`: http://pylonshq.com/ .. _`Flask`: http://flask.pocoo.org/ .. _`web2py`: http://web2py.com/ .. _`Bottle`: http://bottlepy.org/ .. _`Pyramid`: http://docs.pylonsproject.org/en/latest/docs/pyramid.html .. _`pyramid_celery`: http://pypi.python.org/pypi/pyramid_celery/ .. _`django-celery`: http://pypi.python.org/pypi/django-celery .. _`celery-pylons`: http://pypi.python.org/pypi/celery-pylons .. _`web2py-celery`: http://code.google.com/p/web2py-celery/ .. _`Tornado`: http://www.tornadoweb.org/ .. _`tornado-celery`: http://github.com/mher/tornado-celery/ .. _celery-documentation: Documentation ============= The `latest documentation`_ with user guides, tutorials and API reference is hosted at Read The Docs. .. _`latest documentation`: http://docs.celeryproject.org/en/latest/