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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
Languages
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

Synchronization between Threads

Now that we've taken a look at threads, and how we can work with and create these threads using various mechanisms in the previous chapter, it's time to look at some of the basic synchronization primitives we can leverage within our multi-threads.

It's not enough to simply add multiple threads to your application in order to improve performance. You also have to take into consideration complexities such as race conditions, and ensure that your code is properly guarded against them.

In this chapter, we'll look at some of the following concepts:

  • How we can synchronize our data between threads
  • Race conditions--what are they and how to guard against them
  • Deadlock, and how it can cripple your systems and bring them to their knees
  • An overview of all of the synchronization primitives that Python has to offer

We'll also be introducing...

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