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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

How does the operating system handle threads

So now that we've taken a look at the life cycle of a thread, it's important to know how these threads actually work within your machines. Understanding things like the multithreading model and how Python threads map to system threads is important if you are to make the right decisions when designing your high-performance software.

Creating processes versus threads

A process, as we've seen, is a more heavyweight version of a simple thread in the sense that we can do things like spin up multiple threads within a process. They can perform more CPU-bound tasks better than a standard thread would due to the fact that they each feature their own separate GIL instance.

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