| Name | rq JSON |
| Version |
1.16.2
JSON |
| download |
| home_page | None |
| Summary | RQ is a simple, lightweight, library for creating background jobs, and processing them. |
| upload_time | 2024-05-01 07:13:14 |
| maintainer | Selwin Ong |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
|
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 >= 3.0.0.
[](https://github.com/rq/rq/actions?query=workflow%3A%22Test+rq%22)
[](https://pypi.python.org/pypi/rq)
[](https://codecov.io/gh/rq/rq)
[](https://github.com/psf/black)
Full documentation can be found [here][d].
## 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).
## Getting started
First, run a Redis server, of course:
```console
$ redis-server
```
To put jobs on queues, you don't have to do anything special, just define
your typically lengthy or blocking function:
```python
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][r] package, don't you?
Then, create an RQ queue:
```python
from redis import Redis
from rq import Queue
queue = Queue(connection=Redis())
```
And enqueue the function call:
```python
from my_module import count_words_at_url
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
job = queue.enqueue_at(datetime(2019, 10, 10, 9, 15), say_hello)
# 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]))
```
For a more complete example, refer to the [docs][d]. But this is the essence.
### The worker
To start executing enqueued function calls in the background, start a worker
from your project's directory:
```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
```
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/rq/rq.git@master#egg=rq
## Related Projects
Check out these below repos which might be useful in your rq based project.
- [rq-dashboard](https://github.com/Parallels/rq-dashboard)
- [rqmonitor](https://github.com/pranavgupta1234/rqmonitor)
- [django-rq](https://github.com/rq/django-rq)
- [Flask-RQ2](https://github.com/rq/Flask-RQ2)
- [rq-scheduler](https://github.com/rq/rq-scheduler)
## Project history
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.
[r]: http://python-requests.org
[d]: http://python-rq.org/
[m]: http://pypi.python.org/pypi/mailer
[p]: http://docs.python.org/library/pickle.html
[1]: http://docs.celeryq.dev/
[2]: https://github.com/resque/resque
[3]: https://github.com/fengsp/flask-snippets/blob/1f65833a4291c5b833b195a09c365aa815baea4e/utilities/rq.py
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"description": "RQ (_Redis Queue_) is a simple Python library for queueing jobs and processing\nthem in the background with workers. It is backed by Redis and it is designed\nto have a low barrier to entry. It should be integrated in your web stack\neasily.\n\nRQ requires Redis >= 3.0.0.\n\n[](https://github.com/rq/rq/actions?query=workflow%3A%22Test+rq%22)\n[](https://pypi.python.org/pypi/rq)\n[](https://codecov.io/gh/rq/rq)\n[](https://github.com/psf/black)\n\n\nFull documentation can be found [here][d].\n\n\n## Support RQ\n\nIf 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).\n\n\n## Getting started\n\nFirst, run a Redis server, of course:\n\n```console\n$ redis-server\n```\n\nTo put jobs on queues, you don't have to do anything special, just define\nyour typically lengthy or blocking function:\n\n```python\nimport requests\n\ndef count_words_at_url(url):\n \"\"\"Just an example function that's called async.\"\"\"\n resp = requests.get(url)\n return len(resp.text.split())\n```\n\nYou do use the excellent [requests][r] package, don't you?\n\nThen, create an RQ queue:\n\n```python\nfrom redis import Redis\nfrom rq import Queue\n\nqueue = Queue(connection=Redis())\n```\n\nAnd enqueue the function call:\n\n```python\nfrom my_module import count_words_at_url\njob = queue.enqueue(count_words_at_url, 'http://nvie.com')\n```\n\nScheduling jobs are also similarly easy:\n\n```python\n# Schedule job to run at 9:15, October 10th\njob = queue.enqueue_at(datetime(2019, 10, 10, 9, 15), say_hello)\n\n# Schedule job to run in 10 seconds\njob = queue.enqueue_in(timedelta(seconds=10), say_hello)\n```\n\nRetrying failed jobs is also supported:\n\n```python\nfrom rq import Retry\n\n# Retry up to 3 times, failed job will be requeued immediately\nqueue.enqueue(say_hello, retry=Retry(max=3))\n\n# Retry up to 3 times, with configurable intervals between retries\nqueue.enqueue(say_hello, retry=Retry(max=3, interval=[10, 30, 60]))\n```\n\nFor a more complete example, refer to the [docs][d]. But this is the essence.\n\n\n### The worker\n\nTo start executing enqueued function calls in the background, start a worker\nfrom your project's directory:\n\n```console\n$ rq worker --with-scheduler\n*** Listening for work on default\nGot count_words_at_url('http://nvie.com') from default\nJob result = 818\n*** Listening for work on default\n```\n\nThat's about it.\n\n\n## Installation\n\nSimply use the following command to install the latest released version:\n\n pip install rq\n\nIf you want the cutting edge version (that may well be broken), use this:\n\n pip install git+https://github.com/rq/rq.git@master#egg=rq\n\n\n## Related Projects\n\nCheck out these below repos which might be useful in your rq based project.\n\n- [rq-dashboard](https://github.com/Parallels/rq-dashboard)\n- [rqmonitor](https://github.com/pranavgupta1234/rqmonitor)\n- [django-rq](https://github.com/rq/django-rq)\n- [Flask-RQ2](https://github.com/rq/Flask-RQ2)\n- [rq-scheduler](https://github.com/rq/rq-scheduler)\n\n\n## Project history\n\nThis project has been inspired by the good parts of [Celery][1], [Resque][2]\nand [this snippet][3], and has been created as a lightweight alternative to the\nheaviness of Celery or other AMQP-based queueing implementations.\n\n\n[r]: http://python-requests.org\n[d]: http://python-rq.org/\n[m]: http://pypi.python.org/pypi/mailer\n[p]: http://docs.python.org/library/pickle.html\n[1]: http://docs.celeryq.dev/\n[2]: https://github.com/resque/resque\n[3]: https://github.com/fengsp/flask-snippets/blob/1f65833a4291c5b833b195a09c365aa815baea4e/utilities/rq.py\n",
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