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Database-backed Periodic Tasks

Build status coverage BSD License django-celery-beat can be installed via wheel Supported Python versions. Support Python implementations.

Version:2.2.0
Web:http://django-celery-beat.readthedocs.io/
Download:http://pypi.python.org/pypi/django-celery-beat
Source:http://github.com/celery/django-celery-beat
Keywords:django, celery, beat, periodic task, cron, scheduling

About

This extension enables you to store the periodic task schedule in the database.

The periodic tasks can be managed from the Django Admin interface, where you can create, edit and delete periodic tasks and how often they should run.

Using the Extension

Usage and installation instructions for this extension are available from the Celery documentation.

Important Warning about Time Zones

Warning

If you change the Django TIME_ZONE setting your periodic task schedule will still be based on the old timezone.

To fix that you would have to reset the "last run time" for each periodic task:

>>> from django_celery_beat.models import PeriodicTask, PeriodicTasks
>>> PeriodicTask.objects.all().update(last_run_at=None)
>>> for task in PeriodicTask.objects.all():
>>>     PeriodicTasks.changed(task)

Note

This will reset the state as if the periodic tasks have never run before.

Models

  • django_celery_beat.models.PeriodicTask

This model defines a single periodic task to be run.

It must be associated with a schedule, which defines how often the task should run.

  • django_celery_beat.models.IntervalSchedule

A schedule that runs at a specific interval (e.g. every 5 seconds).

  • django_celery_beat.models.CrontabSchedule

A schedule with fields like entries in cron: minute hour day-of-week day_of_month month_of_year.

  • django_celery_beat.models.PeriodicTasks

This model is only used as an index to keep track of when the schedule has changed.

Whenever you update a PeriodicTask a counter in this table is also incremented, which tells the celery beat service to reload the schedule from the database.

If you update periodic tasks in bulk, you will need to update the counter manually:

>>> from django_celery_beat.models import PeriodicTasks
>>> PeriodicTasks.update_changed()

Example creating interval-based periodic task

To create a periodic task executing at an interval you must first create the interval object:

>>> from django_celery_beat.models import PeriodicTask, IntervalSchedule

# executes every 10 seconds.
>>> schedule, created = IntervalSchedule.objects.get_or_create(
...     every=10,
...     period=IntervalSchedule.SECONDS,
... )

That's all the fields you need: a period type and the frequency.

You can choose between a specific set of periods:

  • IntervalSchedule.DAYS
  • IntervalSchedule.HOURS
  • IntervalSchedule.MINUTES
  • IntervalSchedule.SECONDS
  • IntervalSchedule.MICROSECONDS

Note

If you have multiple periodic tasks executing every 10 seconds, then they should all point to the same schedule object.

There's also a "choices tuple" available should you need to present this to the user:

>>> IntervalSchedule.PERIOD_CHOICES

Now that we have defined the schedule object, we can create the periodic task entry:

>>> PeriodicTask.objects.create(
...     interval=schedule,                  # we created this above.
...     name='Importing contacts',          # simply describes this periodic task.
...     task='proj.tasks.import_contacts',  # name of task.
... )

Note that this is a very basic example, you can also specify the arguments and keyword arguments used to execute the task, the queue to send it to[*], and set an expiry time.

Here's an example specifying the arguments, note how JSON serialization is required:

>>> import json
>>> from datetime import datetime, timedelta

>>> PeriodicTask.objects.create(
...     interval=schedule,                  # we created this above.
...     name='Importing contacts',          # simply describes this periodic task.
...     task='proj.tasks.import_contacts',  # name of task.
...     args=json.dumps(['arg1', 'arg2']),
...     kwargs=json.dumps({
...        'be_careful': True,
...     }),
...     expires=datetime.utcnow() + timedelta(seconds=30)
... )
[*]you can also use low-level AMQP routing using the exchange and routing_key fields.

Example creating crontab-based periodic task

A crontab schedule has the fields: minute, hour, day_of_week, day_of_month and month_of_year, so if you want the equivalent of a 30 * * * * (execute every 30 minutes) crontab entry you specify:

>>> from django_celery_beat.models import CrontabSchedule, PeriodicTask
>>> schedule, _ = CrontabSchedule.objects.get_or_create(
...     minute='30',
...     hour='*',
...     day_of_week='*',
...     day_of_month='*',
...     month_of_year='*',
...     timezone=pytz.timezone('Canada/Pacific')
... )

The crontab schedule is linked to a specific timezone using the 'timezone' input parameter.

Then to create a periodic task using this schedule, use the same approach as the interval-based periodic task earlier in this document, but instead of interval=schedule, specify crontab=schedule:

>>> PeriodicTask.objects.create(
...     crontab=schedule,
...     name='Importing contacts',
...     task='proj.tasks.import_contacts',
... )

Temporarily disable a periodic task

You can use the enabled flag to temporarily disable a periodic task:

>>> periodic_task.enabled = False
>>> periodic_task.save()

Example running periodic tasks

The periodic tasks still need 'workers' to execute them. So make sure the default Celery package is installed. (If not installed, please follow the installation instructions here: https://github.com/celery/celery)

Both the worker and beat services need to be running at the same time.

  1. Start a Celery worker service (specify your Django project name):

    $ celery -A [project-name] worker --loglevel=info
    
  2. As a separate process, start the beat service (specify the Django scheduler):

    $ celery -A [project-name] beat -l info --scheduler django_celery_beat.schedulers:DatabaseScheduler
    

    OR you can use the -S (scheduler flag), for more options see celery beat --help):

    $ celery -A [project-name] beat -l info -S django
    

    Also, as an alternative, you can run the two steps above (worker and beat services) with only one command (recommended for development environment only):

    $ celery -A [project-name] worker --beat --scheduler django --loglevel=info
    
  3. Now you can add and manage your periodic tasks from the Django Admin interface.

Installation

You can install django-celery-beat either via the Python Package Index (PyPI) or from source.

To install using pip:

$ pip install -U django-celery-beat

Downloading and installing from source

Download the latest version of django-celery-beat from http://pypi.python.org/pypi/django-celery-beat

You can install it by doing the following :

$ tar xvfz django-celery-beat-0.0.0.tar.gz
$ cd django-celery-beat-0.0.0
$ python setup.py build
# python setup.py install

The last command must be executed as a privileged user if you are not currently using a virtualenv.

After installation, add django_celery_beat to Django's settings module:

INSTALLED_APPS = [
    ...,
    'django_celery_beat',
]

Run the django_celery_beat migrations using:

$ python manage.py migrate django_celery_beat

Using the development version

With pip

You can install the latest snapshot of django-celery-beat using the following pip command:

$ pip install https://github.com/celery/django-celery-beat/zipball/master#egg=django-celery-beat

Developing django-celery-beat

To spin up a local development copy of django-celery-beat with Django admin at http://127.0.0.1:58000/admin/ run:

$ docker-compose up --build

Log-in as user admin with password admin.

TZ Awareness:

If you have a project that is time zone naive, you can set DJANGO_CELERY_BEAT_TZ_AWARE=False in your settings file.

django-celery-beat as part of the Tidelift Subscription

The maintainers of django-celery-beat and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source dependencies you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact dependencies you use. Learn more.

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Celery Periodic Tasks backed by the Django ORM

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