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137 lines
3.8 KiB
Markdown
137 lines
3.8 KiB
Markdown
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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to have a low barrier to entry. It should be integrated in your web stack
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easily.
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RQ requires Redis >= 3.0.0.
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[](https://github.com/rq/rq/actions?query=workflow%3A%22Test+rq%22)
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[](https://pypi.python.org/pypi/rq)
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[](https://codecov.io/gh/rq/rq)
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[](https://github.com/psf/black)
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Full documentation can be found [here][d].
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## Support RQ
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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).
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## Getting started
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First, run a Redis server, of course:
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```console
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$ redis-server
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```
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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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```python
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import requests
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def count_words_at_url(url):
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"""Just an example function that's called async."""
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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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You do use the excellent [requests][r] package, don't you?
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Then, create an RQ queue:
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```python
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from redis import Redis
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from rq import Queue
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queue = Queue(connection=Redis())
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```
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And enqueue the function call:
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```python
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from my_module import count_words_at_url
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job = queue.enqueue(count_words_at_url, 'http://nvie.com')
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```
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Scheduling jobs are also similarly easy:
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```python
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# Schedule job to run at 9:15, October 10th
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job = queue.enqueue_at(datetime(2019, 10, 10, 9, 15), say_hello)
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# Schedule job to run in 10 seconds
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job = queue.enqueue_in(timedelta(seconds=10), say_hello)
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```
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Retrying failed jobs is also supported:
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```python
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from rq import Retry
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# Retry up to 3 times, failed job will be requeued immediately
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queue.enqueue(say_hello, retry=Retry(max=3))
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# Retry up to 3 times, with configurable intervals between retries
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queue.enqueue(say_hello, retry=Retry(max=3, interval=[10, 30, 60]))
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```
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For a more complete example, refer to the [docs][d]. But this is the essence.
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### The worker
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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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```console
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$ rq worker --with-scheduler
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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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That's about it.
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## Installation
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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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pip install git+https://github.com/rq/rq.git@master#egg=rq
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## Related Projects
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Check out these below repos which might be useful in your rq based project.
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- [rq-dashboard](https://github.com/Parallels/rq-dashboard)
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- [rqmonitor](https://github.com/pranavgupta1234/rqmonitor)
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- [django-rq](https://github.com/rq/django-rq)
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- [Flask-RQ2](https://github.com/rq/Flask-RQ2)
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- [rq-scheduler](https://github.com/rq/rq-scheduler)
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## Project history
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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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[r]: http://python-requests.org
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[d]: http://python-rq.org/
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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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[1]: http://docs.celeryq.dev/
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[2]: https://github.com/resque/resque
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[3]: https://github.com/fengsp/flask-snippets/blob/1f65833a4291c5b833b195a09c365aa815baea4e/utilities/rq.py
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