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Mastering Python High Performance

You're reading from   Mastering Python High Performance Learn how to optimize your code and Python performance with this vital guide to Python performance profiling and benchmarking

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781783989300
Length 260 pages
Edition 1st Edition
Languages
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Author (1):
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Fernando Donglio Fernando Donglio
Author Profile Icon Fernando Donglio
Fernando Donglio
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Chapter 6. Generic Optimization Options

In the never-ending road to mastering optimization, we started by covering some tips and tricks in Chapter 4, Optimize Everything. In Chapter 5, Multithreading versus Multiprocessing, we went over two major optimization strategies: multithreading and multiprocessing. We saw how they help us and when to use them.

Finally, we will deal with one of the many implementations of the Python language (CPython). This implies that there are other alternatives to CPython. In this chapter, we'll cover two of them:

  • We'll cover PyPy, an alternative to the standard Python interpreter we've been using throughout the book. This one is written in Python and has some benefits over the standard version.
  • We will talk about Cython, an optimizing static compiler, which will allow us to write Python code and tap into the power of C and C++ easily.

Both alternatives will provide developers with the opportunity to run code in a more optimized fashion,...

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