huey

http://media.charlesleifer.com/blog/photos/huey2-logo.png

a lightweight alternative.

huey is:

  • a task queue (2019-04-01: version 2.0 released)
  • written in python (2.7+, 3.4+)
  • clean and simple API
  • redis, sqlite, file-system, or in-memory storage
  • example code.

huey supports:

  • multi-process, multi-thread or greenlet task execution models
  • schedule tasks to execute at a given time, or after a given delay
  • schedule recurring tasks, like a crontab
  • automatically retry tasks that fail
  • task prioritization
  • task result storage
  • task expiration
  • task locking
  • task pipelines and chains
http://i.imgur.com/2EpRs.jpg

At a glance

task() and periodic_task() decorators turn functions into tasks executed by the consumer:

from huey import RedisHuey, crontab

huey = RedisHuey('my-app', host='redis.myapp.com')

@huey.task()
def add_numbers(a, b):
    return a + b

@huey.task(retries=2, retry_delay=60)
def flaky_task(url):
    # This task might fail, in which case it will be retried up to 2 times
    # with a delay of 60s between retries.
    return this_might_fail(url)

@huey.periodic_task(crontab(minute='0', hour='3'))
def nightly_backup():
    sync_all_data()

Calling a task-decorated function will enqueue the function call for execution by the consumer. A special result handle is returned immediately, which can be used to fetch the result once the task is finished:

>>> from demo import add_numbers
>>> res = add_numbers(1, 2)
>>> res
<Result: task 6b6f36fc-da0d-4069-b46c-c0d4ccff1df6>

>>> res()
3

Tasks can be scheduled to run in the future:

>>> res = add_numbers.schedule((2, 3), delay=10)  # Will be run in ~10s.
>>> res(blocking=True)  # Will block until task finishes, in ~10s.
5

For much more, check out the Guide or take a look at the example code.

Running the consumer

Run the consumer with four worker processes:

$ huey_consumer.py my_app.huey -k process -w 4

To run the consumer with a single worker thread (default):

$ huey_consumer.py my_app.huey

If your work-loads are mostly IO-bound, you can run the consumer with threads or greenlets instead. Because greenlets are so lightweight, you can run quite a few of them efficiently:

$ huey_consumer.py my_app.huey -k greenlet -w 32

For more information, see the Consuming Tasks document.

Indices and tables