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Distributed Task Queue

Project description

3.0.19 (Chiastic Slide)





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 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.

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 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.

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:

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
    celery = Celery('hello', broker='amqp://guest@localhost//')
    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…

  • Brokers

  • Concurrency

  • Result Stores

    • AMQP, Redis

    • memcached, MongoDB

    • SQLAlchemy, Django ORM

    • Apache Cassandra

  • Serialization

    • pickle, json, yaml, msgpack.

    • zlib, bzip2 compression.

    • Cryptographic message signing.

Framework Integration

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








not needed





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.

The following bundles are available:


for using Redis as a broker.


for using MongoDB as a broker.


for Django, and using Redis as a broker.


for Django, and using MongoDB as a broker.

Downloading and installing from source

Download the latest version of Celery from

You can install it by doing the following,:

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

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

Using the development version

You can clone the repository by doing the following:

$ git clone
$ cd celery
$ python develop

The development version will usually also depend on the development version of kombu, the messaging framework Celery uses to send and receive messages, so you should also install that from git:

$ git clone
$ cd kombu
$ python develop

Getting Help

Mailing list

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.

Bug tracker

If you have any suggestions, bug reports or annoyances please report them to our issue tracker at



Development of celery happens at Github:

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.

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