django-orchestra-test/orchestra/contrib/tasks
2015-07-21 12:23:40 +00:00
..
management/commands Removed unused imports and patterns 2015-05-19 13:27:04 +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 Fixes on periodic tasks 2015-05-09 18:53:23 +00:00
beat.py Added mailer 2015-05-04 21:52:53 +02:00
decorators.py Removed unused imports and patterns 2015-05-19 13:27:04 +00:00
parser.py Added tasks app 2015-05-03 17:44:46 +00:00
README.md Added mailer README file 2015-05-07 20:04:28 +00:00
schedules.py Added tasks app 2015-05-03 17:44:46 +00:00
settings.py Random fixes 2015-07-21 12:23:40 +00:00
tasks.py Random fixes 2015-07-21 12:23:40 +00:00
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 the traditional way of pushing the task on a queue (rabbitmq) and wait for a Celery worker to run it.

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.