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Learning Concurrency in Python

You're reading from   Learning Concurrency in Python Build highly efficient, robust, and concurrent applications

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787285378
Length 360 pages
Edition 1st Edition
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Author (1):
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Elliot Forbes Elliot Forbes
Author Profile Icon Elliot Forbes
Elliot Forbes
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Table of Contents (13) Chapters Close

Preface 1. Speed It Up! FREE CHAPTER 2. Parallelize It 3. Life of a Thread 4. Synchronization between Threads 5. Communication between Threads 6. Debug and Benchmark 7. Executors and Pools 8. Multiprocessing 9. Event-Driven Programming 10. Reactive Programming 11. Using the GPU 12. Choosing a Solution

Understanding concurrency


Concurrency is, essentially, the practice of doing multiple things at the same time, but not, specifically, in parallel. It can help us to improve the perceived performance of our applications, and it can also improve the speed at which our applications run.

The best way to think of how concurrency works is to imagine one person working on multiple tasks and quickly switching between these tasks. Imagine this one person working concurrently on a program, and, at the same time, dealing with support requests. This person would focus primarily on the writing of their program, and quickly context switch to fixing a bug or dealing with a support issue should there be one. Once they complete the support task, they could switch context again, back to writing their program really quickly.

However, in computing, there are typically two performance bottlenecks that we have to watch out for and guard against when writing our programs. It's important to know the differences between...

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