django-orchestra/orchestra/contrib/tasks
2015-05-07 19:50:37 +00:00
..
management/commands Reandom fixes 2015-05-07 19:00:02 +00:00
__init__.py Refactored dashboard icons and menu registration 2015-05-07 14:09:37 +00:00
admin.py Added tasks app 2015-05-03 17:44:46 +00:00
apps.py Refactored dashboard icons and menu registration 2015-05-07 14:09:37 +00:00
beat.py Added mailer 2015-05-04 21:52:53 +02:00
decorators.py Reandom fixes 2015-05-07 19:00:02 +00:00
parser.py Added tasks app 2015-05-03 17:44:46 +00:00
README.md Added README on tasks contrib application0 2015-05-07 19:50:37 +00:00
schedules.py Added tasks app 2015-05-03 17:44:46 +00:00
settings.py Added mailer 2015-05-04 21:52:53 +02:00
utils.py Added mailer 2015-05-04 21:52:53 +02:00

This is a wrapper around djcelery and celery @task and @periodic_task decorators. It provides transparent support for switching between executing a task on a plain Python thread or pushing the task on a queue (rabbitmq) and executing it on a Celery worker.

A queueless threaded execution has the advantage of 0 moving parts instead of the alternative rabbitmq and celery workers. Less dependencies, less memory footprint, less points of failure.

If your application needs to run thousands or milions of tasks a day, use celery as your backend, if tens or hundreds, then probably the default thread backend will be your best choice.