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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 took a comprehensive look at some of the techniques that you can utilize in order to ensure your concurrent Python systems are as free as practically possible from bugs before they plague your production environment. We covered testing strategies that help to ensure the soundness of your code's logic, and provide you with that extra peace of mind when bug fixing.

We then looked at the various ways that you can debug your Python codebase, touching upon the inbuilt Pdb, and how you can interactively use that in the command-line.

Finally, we looked at the various techniques that you can employ in order to benchmark and profile your Python applications, and ensure that they are as efficient as possible.

In the next chapter, we are going to look at Python's Asyncio library, and explain how we can utilize executors and pools in order to improve the performance of our Python applications.

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