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Asynchronous job queues with python-rq

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A short presentation of Redis Queue (python-rq.org) and integrating it with Python/Django.

Watch the presentation here: https://www.youtube.com/watch?v=-WGMgFcnolw

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Asynchronous job queues with python-rq

  1. 1. AsynchronousJobQueueswith PythonRQ AshishAcharya Thoplo.com
  2. 2. Outline ● Asynchronous job queuing ● Redis ● Redis Queue (RQ) ● django-rq
  3. 3. AboutMe ● Computer Engineering graduate from Pulchowk Campus ● Runs a Python shop called Thoplo ● Does a lot of Python/Django ● Uses far too many exec statements ● ashishacharya.com ● Not a designer
  4. 4. WhyAsynchronousJobQueues? ● Some problems take too long to solve within a single process ● Web applications need to provide an immediate response ● Sending emails, processing images, making API calls, etc. can take time ● So background processes and job queues
  5. 5. ToolsforparallelisminPython ● Celery ● IPython.parallel ● Parallel Python ● pymq ● snakeMQ ● Redis Queue
  6. 6. ChallengeswithCelery ● Lots of one-off configuration ● Difficult and time-consuming to set up ● Difficult to get right - lots of moving parts that can fail ● Time consuming to monitor and maintain ● Needs right kind of storage mechanism with the right kind of message queues
  7. 7. MainProblemwithCelery It’s OVERKILL for MOST web projects!
  8. 8. IntroducingRedisQueue ● RQ (Redis Queue) is a simple Python library for queueing jobs and processing them in the background with workers. ● Has a low barrier to entry. ● Has been created as a lightweight alternative to existing queueing frameworks.
  9. 9. WhyRedisQueue? ● Can get it up and running in an afternoon ● No configuration file editing -- or very little ● Don’t have to configure a message broker -- just uses Redis
  10. 10. AboutRedis A server that lets you associate a data structure with a key ● Written in C ● Bindings in most popular languages ● Easy to access from Python ● Used extensively for caching in web applications ● I know almost nothing about it.
  11. 11. AboutRedis import redis connection = redis.Redis(‘localhost’) connection.set(‘key’, ‘value’) print(connection.get(‘key’))
  12. 12. doesRedisQueueuseRedis?Duh! A Python module for treating Redis like a queue ● Pure Python ● Provides a clean, well thought out API for humans
  13. 13. ASimpleExample from redis import Redis from rq import Queue import time q = Queue(connection=Redis()) job = q.enqueue(‘operator.add’, 2, 3) time.sleep(1) print(job.result)
  14. 14. What’sSoCoolAboutRedisQueue?
  15. 15. ...This Monitoring on a web interface: rq-dashboard
  16. 16. ...AlsoThis:django-rq ● Django integration with RQ ● Define queues in settings.py ● Add some urls ● Done! You can start queuing jobs immediately.
  17. 17. Django-rq ● Enqueue jobs like so: import django_rq django_rq.enqueue(func, foo, bar=baz) ● Has a @job decorator like Celery’s @task ● Has management commands for rqworker and rqscheduler python manage.py rqworker high default low python manage.py rqscheduler
  18. 18. Alsohasacooldashboard!
  19. 19. ● Procrastinate digitally...schedule a job for later. ● Send spam daily...and other periodic tasks ...AndThis:rq-scheduler
  20. 20. ...andfinally If you’re already using Redis for caching, you can use the same connection information and reap the benefits of optimization. “Two birds, one Redis.” -- A.A
  21. 21. Twoscoopsapproved
  22. 22. Demo
  23. 23. Tips Break jobs down into atomic packages that don’t do anything else. At a point when this doesn’t work for you anymore, it’s definitely time to upgrade to a more powerful, more complex tool -- Celery. (Or just hire someone to do it for you!)
  24. 24. Questions?

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