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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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Concepts
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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

Shared resources and data races

One of the major things we need to guard against when implementing concurrency in your applications is race conditions. These race conditions can cripple our applications, and cause bugs that are hard to debug and even harder to fix. In order to prevent these issues, we need to both understand how these race conditions occur and how we can guard against them using the synchronization primitives we'll be covering in this chapter.

Understanding synchronization and the basic primitives that are available to you is vital if you are to create thread-safe, high-performance programs in Python. Thankfully, we have numerous different synchronization primitives available to us in the threading Python module that can help us in a number of different concurrent situations.

In this section, I'll be giving you a brief overview of all of the synchronization...

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