celerybeat-redis

It's modified from celerybeat-mongo (https://github.com/zakird/celerybeat-mongo)

See Changelog in CHANGES.md

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 Redis database.

Features

Full-featured celery-beat scheduler
Dynamically add/remove/modify tasks
Support multiple instance by Active-Standby model

Installation

It can be installed by installing the celerybeat-redis Python egg:

# pip install celerybeat-redis

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

$ celery beat -S celerybeatredis.schedulers.RedisScheduler

Configuration

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

CELERY_REDIS_SCHEDULER_URL = "redis://localhost:6379/1"
CELERY_REDIS_SCHEDULER_KEY_PREFIX = 'tasks:meta:'

You must make sure these two values are configured. CELERY_REDIS_SCHEDULER_URL is used to store tasks. CELERY_REDIS_SCHEDULER_KEY_PREFIX is used to generate keys in redis. The keys will be of the form

tasks:meta:task-name-here
tasks:meta:test-fib-every-3s

There is also an optional setting

CELERY_REDIS_SCHEDULER_LOCK_TTL = 30

This value determines how long the redis scheduler will hold on to it's lock, which prevents multiple beat instances from running at the same time. However, in some cases -- such as a hard crash -- celery beat will not be able to clean up after itself and release the lock. Therefore, the lock is given a configurable time-to-live, after which it will expire and be released, if it is not renewed by the beat instance that acquired it. If said beat instance does die, another instance will be able to pick up the baton, as it were, and run instead.

Quickstart

After installed and configure the needs by above, you can make a try with test, cd to test directory, start a worker by:

$ celery worker -A tasks -l info

then start the beat by:

$ celery beat -S celerybeatredis.schedulers.RedisScheduler

celerybeat-redis will load the entry from celeryconfig.py

Detailed Configuration

There was two ways to add a period task:

Add in celeryconfig.py

Celery provide a CELERYBEAT_SCHEDULE entry in config file, when celerybeat-redis starts with such a config, it will load tasks to redis, create them as a celerybeat-redis task.

It's perfect for quick test

Manaully add to Redis

You can create task by insert specify data to redis, according to following described:

Schedules can be manipulated in the Redis database through direct database manipulation. There exist two types of schedules, interval and crontab.

{
    "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" : {
        "__type__": "datetime",
        "year": 2014,
        "month": 8,
        "day": 30,
        "hour": 8,
        "minute": 10,
        "second": 6,
        "microsecond": 667
    }
}

The example from Celery User Guide::Periodic Tasks.

CELERYBEAT_SCHEDULE = {
    'interval-test-schedule': {
        'task': 'tasks.add',
        'schedule': timedelta(seconds=30),
        'args': (param1, param2)
    }
}

Becomes the following::

{
    "name" : "interval test schedule",
    "task" : "task.add",
    "enabled" : true,
    "interval" : {
        "every" : 30,
        "period" : "seconds",
    },
    "args" : [
        "param1",
        "param2"
    ],
    "kwargs" : {
        "max_targets" : 100
    },
    "total_run_count": 5,
    "last_run_at" : {
        "__type__": "datetime",
        "year": 2014,
        "month": 8,
        "day": 30,
        "hour": 8,
        "minute": 10,
        "second": 6,
        "microsecond": 667
    }
}

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:

{
    "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" : {
        "__type__": "datetime",
        "year": 2014,
        "month": 8,
        "day": 30,
        "hour": 8,
        "minute": 10,
        "second": 6,
        "microsecond": 667
    }
}

Deploy multiple nodes

Original celery beat doesn't support multiple node deployment, multiple beat will send multiple tasks and make worker duplicate execution, celerybeat-redis use a redis lock to deal with it. Only one node running at a time, other nodes keep tick with minimal task interval, if this node down, when other node ticking, it will acquire the lock and continue to run.

WARNING: this is an experiment feature, need more test, not production ready at this time.

leepa/celerybeatredis