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A Celery Beat Scheduler that uses MongoDB to store both schedule definitions and status information

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celerybeat-mongo

This is a Celery Beat Scheduler (http://celery.readthedocs.org/en/latest/userguide/periodic-tasks.html) that stores both the schedules themselves and their status information in a backend Mongo database. It can be installed by installing the celerybeat-mongo Python egg:

# pip install celerybeat-mongo 

And specifying the scheduler when running Celery Beat, e.g.:

$ celery beat -S celerybeatmongo.schedulers.MongoScheduler

Settings for the scheduler are defined in your celery configuration file similar to how other aspects of Celery are configured:

CELERY_MONGODB_SCHEDULER_DB = "celery"
CELERY_MONGODB_SCHEDULER_COLLECTION = "schedules"
CELERY_MONGODB_SCHEDULER_URL = "mongodb://userid:password@hostname:port"

If no settings are specified, the library will attempt to use the schedules collection in the local celery database.

Schedules can be manipulated in the Mongo database using the mongoengine models in celerybeatmongo.models or through direct database manipulation. There exist two types of schedules, interval and crontab.

IMPORTANT: because Mongoengine (http://mongoengine-odm.readthedocs.org/) is used to read

the database, objects must have a field _cls set to PeriodicTask. Why? Because Mongoengine allows Document Inheritance (by default: on), which automatically adds extra fields indices (_cls) (http://docs.mongoengine.org/guide/defining-documents.html?highlight=Document%20Inheritance).

Interval:

{
    "_id" : ObjectId("533c5b29b45a2092bffceb13"),
    "_cls": "PeriodicTask",
    "name" : "interval test schedule",
    "task" : "task-name-goes-here",
    "enabled" : true,
    "interval" : {
        "every" : 5,
        "period" : "minutes"
    },
    "args" : [
        "param1",
        "param2"
    ],
    "kwargs" : {
        "max_targets" : 100
    },
    "total_run_count" : 5,
    "last_run_at" : ISODate("2014-04-03T19:19:22.666+17:00")
}

The example from Celery User Guide::Periodic Tasks. :

{
    CELERYBEAT_SCHEDULE = {
        'add-every-30-seconds': {
            'task': 'tasks.add',
            'schedule': timedelta(seconds=30),
            'args': (16, 16)
        },
    }
}

Becomes the following:

{
    "_id" : ObjectId("53a91dfd455d1c1a4345fb59"),
    "_cls": "PeriodicTask",
    "name" : "crontab test schedule",
    "task" : "task-name-goes-here",
    "enabled" : true,
    "crontab" : {
        "minute" : "30",
        "hour" : "2",
        "day_of_week" : "*",
        "day_of_month" : "*",
        "month_of_year" : "*"
    },
    "args" : [
        "param1",
        "param2"
    ],
    "kwargs" : {
        "max_targets" : 100
    },
    "total_run_count" : 5,
    "last_run_at" : ISODate("2014-04-03T19:19:22.666+17:00")
}

The following fields are required: name, task, crontab || interval, enabled when defining new tasks. total_run_count and last_run_at are maintained by the scheduler and should not be externally manipulated.

The example from Celery User Guide::Periodic Tasks. (see: http://docs.celeryproject.org/en/latest/userguide/periodic-tasks.html#crontab-schedules):

{
    CELERYBEAT_SCHEDULE = {
        # Executes every Monday morning at 7:30 A.M
        'add-every-monday-morning': {
            'task': 'tasks.add',
            'schedule': crontab(hour=7, minute=30, day_of_week=1),
            'args': (16, 16),
        },
    }
}

Becomes:

{
    "_id" : ObjectId("53a91dfd455d1c1a4345fb59"),
    "_cls": "PeriodicTask",
    "name" : "add-every-monday-morning",
    "task" : "tasks.add",
    "enabled" : true,
    "crontab" : {
        "minute" : "30",
        "hour" : "7",
        "day_of_week" : "1",
        "day_of_month" : "*",
        "month_of_year" : "*"
    },
    "args" : [ 
        "16", 
        "16"
    ],
    "kwargs" : {},
    "total_run_count" : 1,
    "last_run_at" : ISODate("2014-06-16T07:30:00.752-07:00")
}

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