Book Image

Parallel Programming with Python

By : Jan Palach, Jan Palach V Cruz da Silva
Book Image

Parallel Programming with Python

By: Jan Palach, Jan Palach V Cruz da Silva

Overview of this book

Table of Contents (16 chapters)
Parallel Programming with Python
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

Dispatching a simple task


At this point, we have a ready environment. Let's test it by sending a task that will calculate the square root of a value and return a result.

First, we must define our task module tasks.py inside the server. Let's check the description of the tasks.py module. In the following chunk of code, we have imports necessary for our function that will calculate the square root:

from math import sqrt
from celery import Celery

Now, let's create the following instance of Celery, which will represent our client application:

app = Celery('tasks', broker='redis://192.168.25.21:6379/0')

We have created an instance of Celery that will control some aspects of our application. Notice that in its initializer, we informed the name of the module in which definitions of the task are present and we stated the address of the broker as a second argument.

Then, we have to set up our result backend, which will also be in Redis, as follows:

app.config.CELERY_RESULT_BACKEND = 'redis://192.168.25...