Book Image

Mastering Flask

By : Jack Stouffer
Book Image

Mastering Flask

By: Jack Stouffer

Overview of this book

Starting from a simple Flask app, this book will walk through advanced topics while providing practical examples of the lessons learned. After building a simple Flask app, a proper app structure is demonstrated by transforming the app to use a Model-View-Controller (MVC) architecture. With a scalable structure in hand, the next chapters use Flask extensions to provide extra functionality to the app, including user login and registration, NoSQL querying, a REST API, an admin interface, and more. Next, you’ll discover how to use unit testing to take the guesswork away from making sure the code is performing as it should. The book closes with a discussion of the different platforms that are available to deploy a Flask app on, the pros and cons of each one, and how to deploy on each one.
Table of Contents (20 chapters)
Mastering Flask
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
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...