celery-joinup 4.4.7.1

Donations

This project relies on your generous donations.

If you are using Celery to create a commercial product, please consider becoming our backer or our sponsor to ensure Celery’s future.

For enterprise

Available as part of the Tidelift Subscription.

The maintainers of celery and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source dependencies you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact dependencies you use. Learn more.

What’s 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 written in Python, but the protocol can be implemented in any language. In addition to Python there’s node-celery for Node.js, a PHP client, gocelery for golang, and rusty-celery for Rust.

Language interoperability can also be achieved by using webhooks in such a way that the client enqueues an URL to be requested by a worker.

What do I need?

Celery version 4.4.0 runs on,

• Python (2.7, 3.5, 3.6, 3.7, 3.8)

• PyPy2.7 (7.2)

• PyPy3.5 (7.1)

• PyPy3.6 (7.6)

4.x.x is the last version to support Python 2.7, and from the next major version (Celery 5.x) Python 3.6 or newer is required.

If you’re running an older version of Python, you need to be running an older version of Celery:

• Python 2.6: Celery series 3.1 or earlier.

• Python 2.5: Celery series 3.0 or earlier.

• Python 2.4 was Celery series 2.2 or earlier.

Celery is a project with minimal funding, so we don’t support Microsoft Windows. Please don’t open any issues related to that platform.

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’re new to Celery 4.4 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.

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, like at our mailing-list, or the 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 Primary/Primary or Primary/Replica 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, broker transports, and much more.

It supports…

• Message Transports

  • RabbitMQ, Redis, Amazon SQS

• Concurrency

  • Prefork, Eventlet, gevent, single threaded (solo)

• Result Stores

  • AMQP, Redis

  • memcached

  • SQLAlchemy, Django ORM

  • Apache Cassandra, IronCache, Elasticsearch

• 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:

Django	not needed
Pyramid	pyramid_celery
Pylons	celery-pylons
Flask	not needed
web2py	web2py-celery
Tornado	tornado-celery

The integration packages aren’t strictly necessary, but they can make development easier, and sometimes they add important hooks like closing database connections at fork.

Documentation

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

最新的中文文档托管在 https://www.celerycn.io/ 中，包含用户指南、教程、API接口等。

Installation

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

To install using pip:

$ pip install -U Celery

$ pip install "celery[librabbitmq]"

$ pip install "celery[librabbitmq,redis,auth,msgpack]"

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

$ 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
$ pip install https://github.com/celery/vine/zipball/master#egg=vine

Getting Help

Bug tracker

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

Wiki

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

Credits

License

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