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https://github.com/rq/rq-scheduler

A lightweight library that adds job scheduling capabilities to RQ (Redis Queue)
https://github.com/rq/rq-scheduler

python redis rq scheduled-tasks scheduler task-scheduler

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A lightweight library that adds job scheduling capabilities to RQ (Redis Queue)

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README 

        
============

RQ Scheduler

============



`RQ Scheduler `_ is a small package that

adds job scheduling capabilities to `RQ `_,

a `Redis `_ based Python queuing library.



.. image:: https://travis-ci.org/rq/rq-scheduler.svg?branch=master

    :target: https://travis-ci.org/rq/rq-scheduler



====================

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)



**IMPORTANT**: You should always use UTC datetime when working with `RQ Scheduler`_.



------------------------

Periodic & Repeated Jobs

------------------------



As of version 0.3, `RQ Scheduler`_ also supports creating periodic and repeated jobs.

You can do this via the ``schedule`` method. Note that this feature needs

`RQ`_ >= 0.3.1.



This is how you do it



.. code-block:: python



    scheduler.schedule(

        scheduled_time=datetime.utcnow(), # Time for first execution, in UTC timezone

        func=func,                     # Function to be queued

        args=[arg1, arg2],             # Arguments passed into function when executed

        kwargs={'foo': 'bar'},         # Keyword arguments passed into function when executed

        interval=60,                   # Time before the function is called again, in seconds

        repeat=10,                     # Repeat this number of times (None means repeat forever)

        meta={'foo': 'bar'}            # Arbitrary pickleable data on the job itself

    )



**IMPORTANT NOTE**: If you set up a repeated job, you must make sure that you

either do not set a `result_ttl` value or you set a value larger than the interval.

Otherwise, the entry with the job details will expire and the job will not get re-scheduled.



------------------------

Cron Jobs

------------------------



As of version 0.6.0, `RQ Scheduler`_ also supports creating Cron Jobs, which you can use for

repeated jobs to run periodically at fixed times, dates or intervals, for more info check

https://en.wikipedia.org/wiki/Cron. You can do this via the ``cron`` method.



This is how you do it



.. code-block:: python



    scheduler.cron(

        cron_string,                # A cron string (e.g. "0 0 * * 0")

        func=func,                  # Function to be queued

        args=[arg1, arg2],          # Arguments passed into function when executed

        kwargs={'foo': 'bar'},      # Keyword arguments passed into function when executed

        repeat=10,                  # Repeat this number of times (None means repeat forever)

        result_ttl=300,             # Specify how long (in seconds) successful jobs and their results are kept. Defaults to -1 (forever)

        ttl=200,                    # Specifies the maximum queued time (in seconds) before it's discarded. Defaults to None (infinite TTL).

        queue_name=queue_name,      # In which queue the job should be put in

        meta={'foo': 'bar'},        # Arbitrary pickleable data on the job itself

        use_local_timezone=False    # Interpret hours in the local timezone

    )



-------------------------

Retrieving scheduled jobs

-------------------------



Sometimes you need to know which jobs have already been scheduled. You can get a

list of enqueued jobs with the ``get_jobs`` method



.. code-block:: python



    list_of_job_instances = scheduler.get_jobs()



In it's simplest form (as seen in the above example) this method returns a list

of all job instances that are currently scheduled for execution.



Additionally the method takes two optional keyword arguments ``until`` and

``with_times``. The first one specifies up to which point in time scheduled jobs

should be returned. It can be given as either a datetime / timedelta instance

or an integer denoting the number of seconds since epoch (1970-01-01 00:00:00).

The second argument is a boolean that determines whether the scheduled execution

time should be returned along with the job instances.



Example



.. code-block:: python



    # get all jobs until 2012-11-30 10:00:00

    list_of_job_instances = scheduler.get_jobs(until=datetime(2012, 10, 30, 10))



    # get all jobs for the next hour

    list_of_job_instances = scheduler.get_jobs(until=timedelta(hours=1))



    # get all jobs with execution times

    jobs_and_times = scheduler.get_jobs(with_times=True)

    # returns a list of tuples:

    # [(, datetime.datetime(2012, 11, 25, 12, 30)), ...]



------------------------------

Checking if a job is scheduled

------------------------------



You can check whether a specific job instance or job id is scheduled for

execution using the familiar python ``in`` operator



.. code-block:: python



    if job_instance in scheduler:

        # Do something

    # or

    if job_id in scheduler:

        # Do something



---------------

Canceling a job

---------------



To cancel a job, simply pass a ``Job`` or a job id to ``scheduler.cancel``



.. code-block:: python



    scheduler.cancel(job)



Note that this method returns ``None`` whether the specified job was found or not.



---------------------

Running the scheduler

---------------------



`RQ Scheduler`_ comes with a script ``rqscheduler`` that runs a scheduler

process that polls Redis once every minute and move scheduled jobs to the

relevant queues when they need to be executed



.. code-block:: bash



    # This runs a scheduler process using the default Redis connection

    rqscheduler



If you want to use a different Redis server you could also do



.. code-block:: bash



    rqscheduler --host localhost --port 6379 --db 0



The script accepts these arguments:



* ``-H`` or ``--host``: Redis server to connect to

* ``-p`` or ``--port``: port to connect to

* ``-d`` or ``--db``: Redis db to use

* ``-P`` or ``--password``: password to connect to Redis

* ``-b`` or ``--burst``: runs in burst mode (enqueue scheduled jobs whose execution time is in the past and quit)

* ``-i INTERVAL`` or ``--interval INTERVAL``: How often the scheduler checks for new jobs to add to the queue (in seconds, can be floating-point for more precision).

* ``-j`` or ``--job-class``: specify custom job class for rq to use (python module.Class)

* ``-q`` or ``--queue-class``: specify custom queue class for rq to use (python module.Class)



The arguments pull default values from environment variables with the

same names but with a prefix of ``RQ_REDIS_``.



Running the Scheduler as a Service on Ubuntu

--------------------------------------------



sudo /etc/systemd/system/rqscheduler.service



.. code-block:: bash



    [Unit]

    Description=RQScheduler

    After=network.target



    [Service]

    ExecStart=/home/<>/.virtualenvs/<>/bin/python \

        /home/<>/.virtualenvs/<>/lib/<>/site-packages/rq_scheduler/scripts/rqscheduler.py



    [Install]

    WantedBy=multi-user.target



You will also want to add any command line parameters if your configuration is not localhost or not set in the environment variables.



Start, check Status and Enable the service



.. code-block:: bash



    sudo systemctl start rqscheduler.service

    sudo systemctl status rqscheduler.service

    sudo systemctl enable rqscheduler.service



---------------------------

Running Multiple Schedulers

---------------------------



Multiple instances of the rq-scheduler can be run simultaneously. It allows for



* Reliability (no single point of failure)

* Failover (scheduler instances automatically retry to attain lock and schedule jobs)

* Running scheduler on multiple server instances to make deployment identical and easier



Multiple schedulers can be run in any way you want. Typically you'll only want to run one scheduler per server/instance.



.. code-block:: bash



   rqscheduler -i 5



   # another shell/systemd service or ideally another server

   rqscheduler -i 5



   # different parameters can be provided to different schedulers

   rqscheduler -i 10



**Practical example**:



- ``scheduler_a`` is running on ``ec2_instance_a``

- If ``scheduler_a`` crashes or ``ec2_instance_a`` goes down, then our tasks won't be scheduled at all

- Instead we can simply run 2 schedulers. Another scheduler called ``scheduler_b`` can be run on ``ec2_instance_b``

- Now both ``scheduler_a`` and ``scheduler_b`` will periodically check and schedule the jobs

- If one fails, the other still works



You can read more about multiple schedulers in `#212 `_ and `#195 `_