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Mastering Flask

You're reading from   Mastering Flask Gain expertise in Flask to create dynamic and powerful web applications

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Product type Paperback
Published in Sep 2015
Publisher Packt
ISBN-13 9781784393656
Length 288 pages
Edition 1st Edition
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Author (1):
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Jack Stouffer Jack Stouffer
Author Profile Icon Jack Stouffer
Jack Stouffer
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Table of Contents (15) Chapters Close

Preface 1. Getting Started 2. Creating Models with SQLAlchemy FREE CHAPTER 3. Creating Views with Templates 4. Creating Controllers with Blueprints 5. Advanced Application Structure 6. Securing Your App 7. Using NoSQL with Flask 8. Building RESTful APIs 9. Creating Asynchronous Tasks with Celery 10. Useful Flask Extensions 11. Building Your Own Extension 12. Testing Flask Apps 13. Deploying Flask Apps Index

Running Celery tasks


The delay method is a shorthand version of the apply_async method, which is called in this format:

task.apply_async(
    args=[1, 2],
    kwargs={'kwarg1': '1', 'kwarg2': '2'}
)

However, the args keyword can be implicit:

apply_async([1, 2], kwargs={'kwarg1': '1', 'kwarg2': '2'})

Calling apply_async allows you to define some extra functionality in the task call that you cannot specify in the delay method. First, the countdown option specifies the amount of time in seconds the worker should wait to run the task after receiving it:

>>> from webapp.tasks import log
>>> log.apply_async(["Message"], countdown=600)

countdown is not a guarantee that the task will be run after 600 seconds. countdown only says that the task is up for processing after x number of seconds. If all of the worker processes are busy with the other tasks, then it will not be run immediately.

Another keyword argument that apply_async gives is the eta argument. eta is passed through a Python...

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