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Arnold Krille df22f127eb Test the worker in its own subprocess
- run with an empty queue
- schedule one job (which uses get_current_connection and get_current_job) and
run `rqworker`
- schedule a job that itself schedules `access_self` and run `rqworker`
- Make sure the job didn't fail by assuring the failed queue is still empty
  afterwards.
- Install this package locally when running in travis.
  This actually unifies the behaviour of tox and travis as tox also builds the
  package and then installs it into each test environment.
- fix flake8 (as run by tox)
9 years ago
examples fix print in example 11 years ago
rq Add the workers connection to _connection_stack 9 years ago
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.coveragerc Ignore local.py (it's tested in werkzeug instead). 11 years ago
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.travis.yml Test the worker in its own subprocess 9 years ago
CHANGES.md Updated changelog. 9 years ago
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MANIFEST.in Added a MANIFEST excluding tests from distribution 12 years ago
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README.md

RQ (Redis Queue) is a simple Python library for queueing jobs and processing them in the background with workers. It is backed by Redis and it is designed to have a low barrier to entry. It should be integrated in your web stack easily.

RQ requires Redis >= 2.7.0.

Build status Downloads Can I Use Python 3? Coverage Status

Full documentation can be found here.

Getting started

First, run a Redis server, of course:

$ redis-server

To put jobs on queues, you don't have to do anything special, just define your typically lengthy or blocking function:

import requests

def count_words_at_url(url):
    """Just an example function that's called async."""
    resp = requests.get(url)
    return len(resp.text.split())

You do use the excellent requests package, don't you?

Then, create an RQ queue:

from redis import Redis
from rq import Queue

q = Queue(connection=Redis())

And enqueue the function call:

from my_module import count_words_at_url
result = q.enqueue(count_words_at_url, 'http://nvie.com')

For a more complete example, refer to the docs. But this is the essence.

The worker

To start executing enqueued function calls in the background, start a worker from your project's directory:

$ rq worker
*** Listening for work on default
Got count_words_at_url('http://nvie.com') from default
Job result = 818
*** Listening for work on default

That's about it.

Installation

Simply use the following command to install the latest released version:

pip install rq

If you want the cutting edge version (that may well be broken), use this:

pip install -e git+git@github.com:nvie/rq.git@master#egg=rq

Project history

This project has been inspired by the good parts of Celery, Resque and this snippet, and has been created as a lightweight alternative to the heaviness of Celery or other AMQP-based queueing implementations.