2012-02-22 09:52:39 +00:00
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RQ (_Redis Queue_) is a simple Python library for queueing jobs and processing
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them in the background with workers. It is backed by Redis and it is designed
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2012-03-28 08:57:01 +00:00
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to have a low barrier to entry. It should be integrated in your web stack
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easily.
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2011-11-15 23:37:59 +00:00
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2015-03-09 08:21:40 +00:00
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RQ requires Redis >= 2.7.0.
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2014-09-08 11:25:35 +00:00
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2014-07-23 11:10:12 +00:00
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[![Build status](https://travis-ci.org/nvie/rq.svg?branch=master)](https://secure.travis-ci.org/nvie/rq)
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2014-07-25 10:41:18 +00:00
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[![Downloads](https://pypip.in/d/rq/badge.svg)](https://pypi.python.org/pypi/rq)
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2014-07-23 11:08:24 +00:00
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[![Can I Use Python 3?](https://caniusepython3.com/project/rq.svg)](https://caniusepython3.com/project/rq)
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2014-07-24 21:27:32 +00:00
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[![Coverage Status](https://img.shields.io/coveralls/nvie/rq.svg)](https://coveralls.io/r/nvie/rq)
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2014-07-23 11:08:24 +00:00
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2011-11-14 14:15:05 +00:00
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2011-11-26 08:31:59 +00:00
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## Getting started
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2011-11-14 14:15:05 +00:00
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2011-11-26 08:31:59 +00:00
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First, run a Redis server, of course:
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2011-11-14 14:15:05 +00:00
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2012-08-03 13:04:18 +00:00
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```console
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$ redis-server
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```
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2011-11-14 14:15:05 +00:00
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2011-11-26 08:31:59 +00:00
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To put jobs on queues, you don't have to do anything special, just define
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your typically lengthy or blocking function:
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2011-11-15 21:45:51 +00:00
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2012-08-03 13:04:18 +00:00
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```python
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import requests
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2011-11-14 14:15:05 +00:00
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2012-08-03 13:04:18 +00:00
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def count_words_at_url(url):
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2012-08-04 07:18:46 +00:00
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"""Just an example function that's called async."""
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2012-08-03 13:04:18 +00:00
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resp = requests.get(url)
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return len(resp.text.split())
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```
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2011-11-14 14:15:05 +00:00
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2012-04-02 06:37:47 +00:00
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You do use the excellent [requests][r] package, don't you?
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2015-02-01 07:37:21 +00:00
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Then, create an RQ queue:
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2011-11-14 14:15:05 +00:00
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2012-08-03 13:04:18 +00:00
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```python
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from rq import Queue, use_connection
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use_connection()
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q = Queue()
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```
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2011-11-14 14:15:05 +00:00
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2011-11-26 08:31:59 +00:00
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And enqueue the function call:
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2011-11-14 14:15:05 +00:00
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2012-08-03 13:04:18 +00:00
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```python
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from my_module import count_words_at_url
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result = q.enqueue(count_words_at_url, 'http://nvie.com')
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```
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2011-11-15 22:00:55 +00:00
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2011-11-26 08:31:59 +00:00
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For a more complete example, refer to the [docs][d]. But this is the essence.
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2011-11-15 22:00:55 +00:00
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2011-11-26 08:31:59 +00:00
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### The worker
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2011-11-15 22:00:55 +00:00
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2011-11-26 08:31:59 +00:00
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To start executing enqueued function calls in the background, start a worker
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from your project's directory:
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2011-11-15 22:00:55 +00:00
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2012-08-03 13:04:18 +00:00
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```console
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$ rqworker
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*** Listening for work on default
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Got count_words_at_url('http://nvie.com') from default
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Job result = 818
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*** Listening for work on default
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```
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2011-11-15 22:00:55 +00:00
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2011-11-26 08:31:59 +00:00
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That's about it.
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2011-11-15 22:00:55 +00:00
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2011-11-26 08:31:59 +00:00
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## Installation
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2011-11-14 11:10:59 +00:00
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Simply use the following command to install the latest released version:
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pip install rq
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If you want the cutting edge version (that may well be broken), use this:
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2011-11-14 17:40:12 +00:00
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pip install -e git+git@github.com:nvie/rq.git@master#egg=rq
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2011-11-14 11:10:59 +00:00
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2011-11-15 23:53:56 +00:00
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2011-11-26 08:31:59 +00:00
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## Project history
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2011-11-15 23:53:56 +00:00
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This project has been inspired by the good parts of [Celery][1], [Resque][2]
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and [this snippet][3], and has been created as a lightweight alternative to the
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heaviness of Celery or other AMQP-based queueing implementations.
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2012-04-02 06:37:47 +00:00
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[r]: http://python-requests.org
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[d]: http://nvie.github.com/rq/docs/
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2011-11-26 08:31:59 +00:00
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[m]: http://pypi.python.org/pypi/mailer
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[p]: http://docs.python.org/library/pickle.html
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2011-11-15 23:53:56 +00:00
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[1]: http://www.celeryproject.org/
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2014-09-17 10:53:30 +00:00
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[2]: https://github.com/resque/resque
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2011-11-15 23:53:56 +00:00
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[3]: http://flask.pocoo.org/snippets/73/
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