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Distributed Computing with Python

You're reading from   Distributed Computing with Python Harness the power of multiple computers using Python through this fast-paced informative guide

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Product type Paperback
Published in Apr 2016
Publisher
ISBN-13 9781785889691
Length 170 pages
Edition 1st Edition
Languages
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Author (1):
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Rasheedh B Rasheedh B
Author Profile Icon Rasheedh B
Rasheedh B
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Table of Contents (10) Chapters Close

Preface 1. An Introduction to Parallel and Distributed Computing 2. Asynchronous Programming FREE CHAPTER 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

Chapter 2. Asynchronous Programming

In this chapter, we are finally going to write some code! The code in this chapter and all the chapters that follow is written for Python 3.5 (the current release at the time of writing). When modules, syntaxes, or language constructs are not available in earlier versions of Python (for example, Python 2.7), these will be pointed out in this chapter. In general, however, the code presented here should work on Python 2.x with some minor modifications.

Let's go back to some of the ideas presented in the previous chapter. We know that we can structure our algorithms and programs so that they can run on a local machine or on one or more computers across a network. Even when our code runs on a single machine, as we saw, we can use multiple threads and/or multiple processes so that its various parts can run at the same time on multiple CPUs.

We will now pause thinking about multiple CPUs and instead look at a single thread/process of execution...

You have been reading a chapter from
Distributed Computing with Python
Published in: Apr 2016
Publisher:
ISBN-13: 9781785889691
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