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Distributed Computing with Python

You're reading from  Distributed Computing with Python

Product type Book
Published in Apr 2016
Publisher
ISBN-13 9781785889691
Pages 170 pages
Edition 1st Edition
Languages
Toc

Table of Contents (15) Chapters close

Distributed Computing with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. An Introduction to Parallel and Distributed Computing 2. Asynchronous Programming 3. Parallelism in Python 4. Distributed Applications – with Celery 5. Python in the Cloud 6. Python on an HPC Cluster 7. Testing and Debugging Distributed Applications 8. The Road Ahead Index

Testing the installation


Let's try a quick example to make sure that our Celery installation is working. We will need four terminal windows on, ideally, three different machines (again, we will call them HOST1, HOST2, HOST3, and HOST4). We will start RabbitMQ in one window on HOST1, as shown in the following command (make sure that you use the correct path to rabbitmq-server):

HOST1 $ sudo /usr/local/sbin/rabbitmq-server

In another terminal window (on HOST2), start Redis (if you did not install it, skip to the next paragraph) as follows (make sure to use the correct path to redis-server):

HOST2 $ sudo /usr/local/bin/redis-server

Finally, in a third window (HOST3), create the following Python script (always remember to activate our virtual environment using workon book) and call it test.py:

import celery

app = celery.Celery('test',
                        broker='amqp://HOST1',
                        backend='redis://HOST2')


@app.task
def echo(message):
    return message

What this code...

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