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Daniel Arbuckle???s Mastering Python

You're reading from   Daniel Arbuckle???s Mastering Python Build powerful Python applications

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787283695
Length 274 pages
Edition 1st Edition
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Author (1):
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Daniel Arbuckle Daniel Arbuckle
Author Profile Icon Daniel Arbuckle
Daniel Arbuckle
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Table of Contents (13) Chapters Close

Preface 1. Python Primer 2. Setting Up FREE CHAPTER 3. Making a Package 4. Basic Best Practices 5. Making a Command-Line Utility 6. Parallel Processing 7. Coroutines and Asynchronous I/O 8. Metaprogramming 9. Unit Testing 10. Reactive Programming 11. Microservices 12. Extension Modules and Compiled Code

The difference between asynchronous processing and parallel processing

When we worked with the concurrent.futures module in Chapter 6, Parallel Processing, we saw a way to make two or more streams of code run at the same time. For reference, have a look at the code example we used in the previous chapter:

This code helps you create an executor object. Now if you ever wish to run some code in parallel, you could just tell the executor to do it. The executor would give us a future object that we could use later to get the result of the code, and it would then run the code in a separate process. Our original code will keep on running in the original process.

We talked about how this could improve the performance of CPU-bound programs—it divides the code into multiple computer cores. Therefore, it's a technique that would be convenient in a lot of other circumstances...

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