rq-scheduler-bcfg 0.8.4
Provides job scheduling capabilities to RQ (Redis Queue)
License: MIT

============
RQ Scheduler
============

`RQ Scheduler <https://github.com/rq/rq-scheduler>`_ is a small package that
adds job scheduling capabilities to `RQ <https://github.com/nvie/rq>`_,
a `Redis <http://redis.io/>`_ based Python queuing library.

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

============
Requirements
============

* `RQ`_

============
Installation
============

You can install `RQ Scheduler`_ via pip::

    pip install rq-scheduler

Or you can download the latest stable package from `PyPI <http://pypi.python.org/pypi/rq-scheduler>`_.

=====
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

    # You can also instantiate a Scheduler using an RQ Queue
    queue = Queue('foo', connection=Redis())
    scheduler = Scheduler(queue=queue)

    # 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)


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)
        queue_name=queue_name,      # In which queue the job should be put in
        meta={'foo': 'bar'}         # Arbitrary pickleable data on the job itself
    )

-------------------------
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 boolen 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:
    # [(<rq.job.Job object at 0x123456789>, 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_``.