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| title | layout |
|---|---|
| RQ: Simple job queues for Python | default |
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 can be integrated in your web stack easily.
RQ requires Redis >= 3.0.0.
Getting started
First, run a Redis server. You can use an existing one. To put jobs on queues, you don't have to do anything special, just define your typically lengthy or blocking function:
{% highlight python %} import requests
def count_words_at_url(url): resp = requests.get(url) return len(resp.text.split()) {% endhighlight %}
Then, create a RQ queue:
{% highlight python %} from redis import Redis from rq import Queue
q = Queue(connection=Redis()) {% endhighlight %}
And enqueue the function call:
{% highlight python %} from my_module import count_words_at_url result = q.enqueue(count_words_at_url, 'http://nvie.com') {% endhighlight %}
Scheduling jobs are similarly easy:
{% highlight python %}
Schedule job to run at 9:15, October 10th
job = queue.enqueue_at(datetime(2019, 10, 8, 9, 15), say_hello)
Schedule job to be run in 10 seconds
job = queue.enqueue_in(timedelta(seconds=10), say_hello) {% endhighlight %}
You can also ask RQ to retry failed jobs:
{% highlight python %} from rq import Retry
Retry up to 3 times, failed job will be requeued immediately
queue.enqueue(say_hello, retry=Retry(max=3))
Retry up to 3 times, with configurable intervals between retries
queue.enqueue(say_hello, retry=Retry(max=3, interval=[10, 30, 60])) {% endhighlight %}
The worker
To start executing enqueued function calls in the background, start a worker from your project's directory:
{% highlight console %} $ rq worker --with-scheduler *** Listening for work on default Got count_words_at_url('http://nvie.com') from default Job result = 818 *** Listening for work on default {% endhighlight %}
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 git+https://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 existing queueing frameworks, with a low barrier to entry.