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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

Deciding on a strategy to optimize your software is a complex and delicate task that depends on the application type, target platforms, and business requirements. In this chapter, we provided some guidelines to help you think and choose an appropriate software stack for your own applications.

High-performance numerical applications sometimes require managing installation and deployment of third-party packages that may require handling of external tools and native extensions. In this chapter, we saw how to structure your Python project, including tests, benchmarks, documentation, Cython modules, and C extensions. Also, we introduced the continuous integration service Travis CI, which can be used to enable continuous testing for your projects hosted on GitHub.

Finally, we also learned about virtual environments and docker containers that can be used to test applications in isolation and to greatly simplify...

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