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Python High Performance, Second Edition

You're reading from   Python High Performance, Second Edition Build high-performing, concurrent, and distributed applications

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787282896
Length 270 pages
Edition 2nd Edition
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Author (1):
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Dr. Gabriele Lanaro Dr. Gabriele Lanaro
Author Profile Icon Dr. Gabriele Lanaro
Dr. Gabriele Lanaro
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Table of Contents (10) Chapters Close

Preface Benchmarking and Profiling FREE CHAPTER Pure Python Optimizations Fast Array Operations with NumPy and Pandas C Performance with Cython Exploring Compilers Implementing Concurrency Parallel Processing Distributed Processing Designing for High Performance

Summary

Asynchronous programming is useful when our code deals with slow and unpredictable resources, such as I/O devices and networks. In this chapter, we explored the fundamental concepts of concurrency and asynchronous programming and how to write concurrent code with the asyncio and RxPy libraries.

asyncio coroutines are an excellent choice when dealing with multiple, interconnected resources as they greatly simplify the code logic by cleverly avoiding callbacks. Reactive programming is also very good in these situations, but it truly shines when dealing with streams of data that are common in real-time applications and user interfaces.

In the next two chapters, we will learn about parallel programming and how to achieve impressive performance gain by taking advantage of multiple cores and multiple machines.

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