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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

Summary


In this chapter, we successfully covered everything you need to get started with thread pools, process pools, and future objects. We looked at the various ways you could instantiate your own thread pools and process pools as well the advantages of using thread and process pool executors over the traditional methods.

You should now have a good appreciation of how we can improve the performance of our multi-threaded, multi-processed applications by utilizing this pooled-resource concept.

We also looked at how we could improve the existing implementation of our web crawler and refactor it so that it was easier to follow, and utilized some of the key concepts featured in this chapter. In the next chapter, we'll be looking at how we can utilize multiple processes within our applications, in depth.

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