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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

Choosing a suitable strategy

Many packages are available for improving the performance of programs, but how do we determine the best optimization strategy for our program? A variety of factors dictate the decision on which method to use. In this section, we will try to answer this question as comprehensively as possible, based on broad application categories.

The first aspect to take into consideration is the type of application. Python is a language that serves multiple and very diverse communities that span web services, system scripting, games, machine learning, and much more. Those different applications will require optimization efforts for different parts of the program.

For example, a web service can be optimized to have a very short response time. Also, it has to be able to answer as many requests as possible using as little resources as possible (that is, it will try to achieve lower latency), while numerical...

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