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============
RQ Scheduler
============
[RQ Scheduler] is a small package that
adds job scheduling capabilities to [RQ],
a [Redis] based Python queuing library.
====================
Support RQ Scheduler
====================
If you find ``rq-scheduler`` useful, please consider supporting its
development via [Tidelift].
============
Requirements
============
* `RQ`_
============
Installation
============
You can install `RQ Scheduler`_ via pip::
pip install rq-scheduler
Or you can download the latest stable package from [PyPI].
=====
Usage
=====
Schedule a job involves doing two different things:
1. Putting a job in the scheduler
2. Running a scheduler that will move scheduled jobs into queues when the
time comes
----------------
Scheduling a Job
----------------
There are two ways you can schedule a job. The first is using RQ
Scheduler's enqueue_at
.. code-block:: python
from redis import Redis
from rq import Queue
from rq_scheduler import Scheduler
from datetime import datetime
scheduler = Scheduler(connection=Redis()) # Get a scheduler for the
"default" queue
scheduler = Scheduler('foo', connection=Redis()) # Get a scheduler for
the "foo" queue
# You can also instantiate a Scheduler using an RQ Queue
queue = Queue('bar', connection=Redis())
scheduler = Scheduler(queue=queue, connection=queue.connection)
# Puts a job into the scheduler. The API is similar to RQ except that
it
# takes a datetime object as first argument. So for example to schedule
a
# job to run on Jan 1st 2020 we do:
scheduler.enqueue_at(datetime(2020, 1, 1), func) # Date time should be
in UTC
# Here's another example scheduling a job to run at a specific date and
time (in UTC),
# complete with args and kwargs.
scheduler.enqueue_at(datetime(2020, 1, 1, 3, 4), func, foo, bar=baz)
# You can choose the queue type where jobs will be enqueued by passing
the name of the type to the scheduler
# used to enqueue
scheduler = Scheduler('foo', queue_class="rq.Queue")
scheduler.enqueue_at(datetime(2020, 1, 1), func) # The job will be
enqueued at the queue named "foo" using the queue type "rq.Queue"
The second way is using enqueue_in. Instead of taking a datetime object,
this method expects a timedelta and schedules the job to run at
X seconds/minutes/hours/days/weeks later. For example, if we want to
monitor how
popular a tweet is a few times during the course of the day, we could do
something like
.. code-block:: python
from datetime import timedelta
# Schedule a job to run 10 minutes, 1 hour and 1 day later
scheduler.enqueue_in(timedelta(minutes=10), count_retweets, tweet_id)
scheduler.enqueue_in(timedelta(hours=1), count_retweets, tweet_id)
scheduler.enqueue_in(timedelta(days=1), count_retweets, tweet_id)
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