2012-02-22 09:52:39 +00:00
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
2012-03-28 08:57:01 +00:00
to have a low barrier to entry. It should be integrated in your web stack
easily.
2011-11-15 23:37:59 +00:00
2018-12-03 00:28:36 +00:00
RQ requires Redis >= 3.0.0.
2014-09-08 11:25:35 +00:00
2020-11-27 00:39:49 +00:00
[![Build status ](https://github.com/rq/rq/workflows/Test%20rq/badge.svg )](https://github.com/rq/rq/actions?query=workflow%3A%22Test+rq%22)
2017-10-21 04:22:26 +00:00
[![PyPI ](https://img.shields.io/pypi/pyversions/rq.svg )](https://pypi.python.org/pypi/rq)
2018-01-17 23:41:45 +00:00
[![Coverage ](https://codecov.io/gh/rq/rq/branch/master/graph/badge.svg )](https://codecov.io/gh/rq/rq)
2023-02-04 00:42:51 +00:00
[![Code style: black ](https://img.shields.io/badge/code%20style-black-000000.svg )](https://github.com/psf/black)
2014-07-23 11:08:24 +00:00
2015-06-29 13:10:53 +00:00
Full documentation can be found [here][d].
2011-11-14 14:15:05 +00:00
2019-06-07 14:19:34 +00:00
## Support RQ
If you find RQ useful, please consider supporting this project via [Tidelift ](https://tidelift.com/subscription/pkg/pypi-rq?utm_source=pypi-rq&utm_medium=referral&utm_campaign=readme ).
2011-11-26 08:31:59 +00:00
## Getting started
2011-11-14 14:15:05 +00:00
2011-11-26 08:31:59 +00:00
First, run a Redis server, of course:
2011-11-14 14:15:05 +00:00
2012-08-03 13:04:18 +00:00
```console
$ redis-server
```
2011-11-14 14:15:05 +00:00
2011-11-26 08:31:59 +00:00
To put jobs on queues, you don't have to do anything special, just define
your typically lengthy or blocking function:
2011-11-15 21:45:51 +00:00
2012-08-03 13:04:18 +00:00
```python
import requests
2011-11-14 14:15:05 +00:00
2012-08-03 13:04:18 +00:00
def count_words_at_url(url):
2012-08-04 07:18:46 +00:00
"""Just an example function that's called async."""
2012-08-03 13:04:18 +00:00
resp = requests.get(url)
return len(resp.text.split())
```
2011-11-14 14:15:05 +00:00
2015-02-01 07:37:21 +00:00
Then, create an RQ queue:
2011-11-14 14:15:05 +00:00
2012-08-03 13:04:18 +00:00
```python
2016-02-04 13:12:06 +00:00
from redis import Redis
from rq import Queue
2020-07-26 10:49:09 +00:00
queue = Queue(connection=Redis())
2012-08-03 13:04:18 +00:00
```
2011-11-14 14:15:05 +00:00
2011-11-26 08:31:59 +00:00
And enqueue the function call:
2011-11-14 14:15:05 +00:00
2012-08-03 13:04:18 +00:00
```python
from my_module import count_words_at_url
2020-07-26 10:49:09 +00:00
job = queue.enqueue(count_words_at_url, 'http://nvie.com')
```
Scheduling jobs are also similarly easy:
```python
# Schedule job to run at 9:15, October 10th
2021-08-20 01:19:31 +00:00
job = queue.enqueue_at(datetime(2019, 10, 10, 9, 15), say_hello)
2020-07-26 10:49:09 +00:00
# Schedule job to run in 10 seconds
job = queue.enqueue_in(timedelta(seconds=10), say_hello)
```
Retrying failed jobs is also supported:
```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]))
2012-08-03 13:04:18 +00:00
```
2011-11-15 22:00:55 +00:00
2011-11-26 08:31:59 +00:00
For a more complete example, refer to the [docs][d]. But this is the essence.
2011-11-15 22:00:55 +00:00
2011-11-26 08:31:59 +00:00
### The worker
2011-11-15 22:00:55 +00:00
2011-11-26 08:31:59 +00:00
To start executing enqueued function calls in the background, start a worker
from your project's directory:
2011-11-15 22:00:55 +00:00
2012-08-03 13:04:18 +00:00
```console
2020-07-26 10:49:09 +00:00
$ rq worker --with-scheduler
2012-08-03 13:04:18 +00:00
*** Listening for work on default
Got count_words_at_url('http://nvie.com') from default
Job result = 818
*** Listening for work on default
```
2011-11-15 22:00:55 +00:00
2011-11-26 08:31:59 +00:00
That's about it.
2011-11-15 22:00:55 +00:00
2011-11-26 08:31:59 +00:00
## Installation
2011-11-14 11:10:59 +00:00
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:
2021-08-21 13:01:51 +00:00
pip install git+https://github.com/rq/rq.git@master#egg=rq
2011-11-14 11:10:59 +00:00
2011-11-15 23:53:56 +00:00
2024-09-16 04:37:00 +00:00
## Docs
To build and run the docs, install [jekyll ](https://jekyllrb.com/docs/ ) and run:
```shell
cd docs
jekyll serve
```
2020-06-28 11:21:16 +00:00
## Related Projects
2023-06-19 23:49:17 +00:00
If you use RQ, Check out these below repos which might be useful in your rq based project.
2020-06-28 11:21:16 +00:00
2023-06-19 23:49:17 +00:00
- [django-rq ](https://github.com/rq/django-rq )
2020-06-28 11:21:16 +00:00
- [rq-dashboard ](https://github.com/Parallels/rq-dashboard )
- [rqmonitor ](https://github.com/pranavgupta1234/rqmonitor )
- [Flask-RQ2 ](https://github.com/rq/Flask-RQ2 )
- [rq-scheduler ](https://github.com/rq/rq-scheduler )
2024-02-13 02:32:27 +00:00
- [rq-dashboard-fastAPI ](https://github.com/Hannes221/rq-dashboard-fast )
2020-06-28 11:21:16 +00:00
2011-11-26 08:31:59 +00:00
## Project history
2011-11-15 23:53:56 +00:00
This project has been inspired by the good parts of [Celery][1], [Resque][2]
and [this snippet][3], and has been created as a lightweight alternative to the
heaviness of Celery or other AMQP-based queueing implementations.
2019-05-30 10:12:31 +00:00
2015-06-29 13:10:53 +00:00
[d]: http://python-rq.org/
2011-11-26 08:31:59 +00:00
[m]: http://pypi.python.org/pypi/mailer
[p]: http://docs.python.org/library/pickle.html
2022-04-02 01:06:42 +00:00
[1]: http://docs.celeryq.dev/
2014-09-17 10:53:30 +00:00
[2]: https://github.com/resque/resque
2020-11-21 06:08:33 +00:00
[3]: https://github.com/fengsp/flask-snippets/blob/1f65833a4291c5b833b195a09c365aa815baea4e/utilities/rq.py