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Introduction to Django-Celery and Supervisor
1.
Introducti on to Celery
2.
What is Celery? “Celery
is an asynchronous task queue based on distributed message passing.” It is a powerful, production-ready asynchronous job queue, which allows you to run time-consuming Python functions in the background.
3.
Why should I
use Celery?
4.
User perspective • Minimize
request/response cycle • Smoother user experience • Difference between pleasant and unpleasant
5.
Developer perspective • Offload
time/cpu intensive processes • Scalability - add workers as needed • Flexibility - many points of customization • Actively developed • Great documentation • Lots of tutorials
6.
OUT OF THE REQUEST/RESPONSE CYCLE •
Example: Sending emails asynchronously.
7.
TASKS IN THE BACKGROUND. •
Example: Computational heavy jobs. • Example: Interacting with external APIs.
8.
PERIODIC JOBS
9.
10.
Celery Architecture
11.
PRODUCER • Produces a
task for the queue.
12.
BROKER • Stores the
task backlog • Answers, what work remains to be done? • RabbitMQ, Redis, SQLAlchemy, Django's ORM, MongoDB
13.
WORKER • Execute and
consumes tasks. • Distributed.
14.
RESULTS BACKEND • Stores
the results from our tasks.
15.
EXAMPLE
16.
INTERGRATING WITH DJANGO.
17.
BEWARE OF DJANGO- CELERY
18.
IMPORTANT SETTINGS • BROKER_URL
= 'redis://localhost:6379/0' • CELERY_RESULT_BACKEND = 'redis://localhost:6379/0' • CELERY_TASK_RESULT_EXPIRES = 7*86400 # 7 days • CELERYBEAT_SCHEDULER = "djcelery.schedulers.DatabaseScheduler" • CELERY_ACCEPT_CONTENT = ['application/json'] • CELERY_TASK_SERIALIZER = 'json' • CELERY_RESULT_SERIALIZER = 'json' • BROKER_BACKEND = "redis" • BROKER_CONNECTION_TIMEOUT = 5.0 • CELERY_IMPORTS = ('<your-app-name>.tasks',)
19.
Write code in
celery.py
20.
Intialize celery in
__init__.py
21.
BEST PRACTICES
22.
NEVER PASS OBJECTS
AS ARGUMENTS.
23.
AVOID LAUNCHING SYNCHRONOUS SUBTASKS
24.
25.
PERIODIC TASKS
26.
THINGS GO WRONG
?
27.
RE-TRY!
28.
Thanks!
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