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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 looked comprehensively at multiprocessing, and how it can be utilized within our systems. We followed the life of a process from its creation all the way through to its timely termination.

We looked at the various intricacies such as cross-process communication and synchronization, and we also looked at how your standard multiprocessing pools differ from the standard ProcessPoolExecutors that we explored in Chapter 7, Executors and Pools.

We then took a brief look at how we can implement things such as communication and synchronization between our various processes without incurring major performance penalties, or becoming the proud owners of systems plagued by race conditions.

In the next chapter, Event-driven programming, we'll be diving deep into the asyncio module, and understand how we can leverage this module in order to develop our own event-based Python programs.

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