--

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 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 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.

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 requires a message broker to send and receive messages. The RabbitMQ, Redis and MongoDB broker transports are feature complete, but there's also 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.

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.

• 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:https://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.

• Brokers

  • RabbitMQ, Redis,
  • MongoDB, Beanstalk,
  • CouchDB, SQLAlchemy,
  • Django ORM, Amazon SQS, IronMQ
  • and more...

• Concurrency

  • multiprocessing, 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.

Celery is easy to integrate with web frameworks, some of which even have integration packages:

Django	django-celery
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.

The latest documentation with user guides, tutorials and API reference is hosted at Read The Docs.

You can install Celery either via the Python Package Index (PyPI) or from source.

To install using pip,:

$ pip install -U Celery

To install using easy_install,:

$ easy_install -U Celery

Celery also defines a group of bundles that can be used to install Celery and the dependencies for a given feature.

You can specify these in your requirements or on the pip comand-line by using brackets. Multiple bundles can be specified by separating them by commas.

$ pip install celery[librabbitmq]

$ pip install celery[librabbitmq,redis]

The following bundles are available:

Download the latest version of Celery from https://pypi.python.org/pypi/celery/

You can install it by doing the following,:

$ tar xvfz celery-0.0.0.tar.gz
$ cd celery-0.0.0
$ python setup.py build
# python setup.py install

The last command must be executed as a privileged user if you are not currently using a virtualenv.

The Celery development version also requires the development versions of kombu, amqp and billiard.

You can install the latest snapshot of these using the following pip commands:

$ pip install https://github.com/celery/celery/zipball/master#egg=celery
$ pip install https://github.com/celery/billiard/zipball/master#egg=billiard
$ pip install https://github.com/celery/py-amqp/zipball/master#egg=amqp
$ pip install https://github.com/celery/kombu/zipball/master#egg=kombu

Please the Contributing section.

For discussions about the usage, development, and future of celery, please join the celery-users mailing list.

Come chat with us on IRC. The #celery channel is located at the Freenode network.

If you have any suggestions, bug reports or annoyances please report them to our issue tracker at https://github.com/celery/celery/issues/

https://wiki.github.com/celery/celery/

Development of celery happens at Github: https://github.com/celery/celery

You are highly encouraged to participate in the development of celery. If you don't like Github (for some reason) you're welcome to send regular patches.

Be sure to also read the Contributing to Celery section in the documentation.

This software is licensed under the New BSD License. See the LICENSE file in the top distribution directory for the full license text.