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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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Table of Contents (20) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
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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 Index

Chapter 6. Debug and Benchmark

Programming is never just about crafting a solution to a problem and leaving it once it's reached a somewhat finished state. More often than not, it's also about maintaining the existing solutions so that businesses can continue to run and make money. Maintaining these existing solutions, typically, means doing things like debugging and adding new features, and in order to do these things, it's important to have a working knowledge of some of the tools that exist within the Python ecosystem.

In this chapter, we'll be looking at the various testing strategies we can follow in order to ensure that we can continue to add new features and perform refactoring of our code with minimal risk to the existing features.

We'll also be diving deep into some of the tools available that allow us to gain a better understanding of our Python applications at a far more granular level. To that end, in this chapter, we'll be covering the following topics:

  • Test strategies for your...
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