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Allows you to prevent multiple execution and queuing of celery tasks.

Project description

Celery Once

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Celery Once allows you to prevent multiple execution and queuing of celery tasks.

Installation

Installing celery_once is simple with pip, just run:

pip install -U celery_once

Requirements

  • Celery. Built to run with Celery 4.0. Older versions may work, but are not officially supported.

Usage

To use celery_once, your tasks need to inherit from an abstract base task called QueueOnce.

Once installed, you’ll need to configure a few options a ONCE key in celery’s conf.

from celery import Celery
from celery_once import QueueOnce
from time import sleep

celery = Celery('tasks', broker='amqp://guest@localhost//')
celery.conf.ONCE = {
  'backend': 'celery_once.backends.Redis',
  'settings': {
    'url': 'redis://localhost:6379/0',
    'default_timeout': 60 * 60
  }
}

@celery.task(base=QueueOnce)
def slow_task():
    sleep(30)
    return "Done!"

The exact configuration, depends on which locking backend you want to use. See Backends.

Behind the scenes, this overrides apply_async and delay. It does not affect calling the tasks directly.

When running the task, celery_once checks that no lock is in place (against a Redis key). If it isn’t, the task will run as normal. Once the task completes (or ends due to an exception) the lock will clear. If an attempt is made to run the task again before it completes an AlreadyQueued exception will be raised.

example.delay(10)
example.delay(10)
Traceback (most recent call last):
    ..
AlreadyQueued()
result = example.apply_async(args=(10))
result = example.apply_async(args=(10))
Traceback (most recent call last):
    ..
AlreadyQueued()

graceful

Optionally, instead of raising an AlreadyQueued exception, the task can return None if once={'graceful': True} is set in the task’s options or when run through apply_async.

from celery_once import AlreadyQueued
# Either catch the exception,
try:
    example.delay(10)
except AlreadyQueued:
    pass
# Or, handle it gracefully at run time.
result = example.apply(args=(10), once={'graceful': True})
# or by default.
@celery.task(base=QueueOnce, once={'graceful': True})
def slow_task():
    sleep(30)
    return "Done!"

keys

By default celery_once creates a lock based on the task’s name and its arguments and values. Take for example, the following task below…

@celery.task(base=QueueOnce)
def slow_add(a, b):
    sleep(30)
    return a + b

Running the task with different arguments will default to checking against different locks.

slow_add(1, 1)
slow_add(1, 2)

If you want to specify locking based on a subset, or no arguments you can adjust the keys celery_once looks at in the task’s options with once={'keys': [..]}

@celery.task(base=QueueOnce, once={'keys': ['a']})
def slow_add(a, b):
    sleep(30)
    return a + b

example.delay(1, 1)
# Checks if any tasks are running with the `a=1`
example.delay(1, 2)
Traceback (most recent call last):
    ..
AlreadyQueued()
example.delay(2, 2)
@celery.task(base=QueueOnce, once={'keys': []})
def slow_add(a, b):
    sleep(30)
    return a + b

# Will enforce only one task can run, no matter what arguments.
example.delay(1, 1)
example.delay(2, 2)
Traceback (most recent call last):
    ..
AlreadyQueued()

timeout

As a fall back, celery_once will clear a lock after 60 minutes. This is set globally in Celery’s configuration with ONCE_DEFAULT_TIMEOUT but can be set for individual tasks using…

@celery.task(base=QueueOnce, once={'timeout': 60 * 60 * 10})
def long_running_task():
    sleep(60 * 60 * 3)

unlock_before_run

By default, the lock is removed after the task has executed (using celery’s after_return). This behaviour can be changed setting the task’s option unlock_before_run. When set to True, the lock will be removed just before executing the task.

Caveats:
  • Any retry of the task won’t re-enable the lock!
  • This can only be set when defining the task, it cannot be passed dynamically to apply_async
@celery.task(base=QueueOnce, once={'unlock_before_run': True})
def slow_task():
    sleep(30)
    return "Done!"

Backends

Redis Backend

Requires:

  • Redis is used as a distributed locking mechanism. Behind the scenes, it use Redlock. This page has more infomation about the locking guarantees.

Configuration:

  • backend - celery_once.backends.Redis
  • settings
  • default_timeout - how many seconds after a lock has been set before it should automatically timeout (defaults to 3600 seconds, or 1 hour).
  • url - should point towards a running Redis instance (defaults to redis://localhost:6379/0). See below for the format options supported
  • blocking (boolean value: default False) - If set to True, scheduling a task (by .delay/.apply_async) will block for X seconds to acquire the lock (see: blocking_timeout below). If no lock could be acquired after X seconds, will raise an AlreadyQueued exception. This is a very specific use-case scenario and by default is disabled.
  • blocking_timeout (int or float value: default 1) - How many seconds the task will block trying to aquire the lock, if blocking is set to True. Setting this to None set’s no timeout (equivalent to infinite seconds).

The URL parser supports two patterns of urls:

  • redis://host:port[/db][?options]: redis over TCP

  • redis+socket:///path/to/redis.sock[?options]: redis over a UNIX socket

    The options query args are mapped to the StrictRedis keyword args. Examples: * redis://localhost:6379/1

    • redis+socket:///var/run/redis/redis.sock?db=1

Example Configuration:

Minimal:

celery.conf.ONCE = {
  'backend': 'celery_once.backends.Redis',
  'settings': {
    'url': 'redis://localhost:6379/0',
    'default_timeout': 60 * 60
  }
}

Advanced: Scheduling tasks blocks up to 30 seconds trying to acquire a lock before raising an exception.

celery.conf.ONCE = {
  'backend': 'celery_once.backends.Redis',
  'settings': {
    'url': 'redis://localhost:6379/0',
    'default_timeout': 60 * 60,
    'blocking': True,
    'blocking_timeout': 30
  }
}

Custom Backend

If you want to implement a custom locking backend, see BACKEND_GUIDE.rst.

Support

  • Tests are run against Python 2.7, 3.4 and 3.5. Other versions may work, but are not officially supported.

Contributing

Contributions are welcome, and they are greatly appreciated! See contributing guide for more details.

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