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Python High Performance, Second Edition

Python High Performance, Second Edition

By : Dr. Gabriele Lanaro
4 (2)
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Python High Performance, Second Edition

Python High Performance, Second Edition

4 (2)
By: Dr. Gabriele Lanaro

Overview of this book

Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language. Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications. The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. By the end of the book, readers will have learned to achieve performance and scale from their Python applications.
Table of Contents (10 chapters)
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Profiling Cython

Cython provides a feature, called annotated view, that helps find which lines are executed in the Python interpreter and which are good candidates for ulterior optimizations. We can turn this feature on by compiling a Cython file with the -a option. In this way, Cython will generate an HTML file containing our code annotated with some useful information. The usage of the -a option is as follows:

$ cython -a cevolve.pyx
$ firefox cevolve.html

The HTML file displayed in the following screenshot shows our Cython file line by line:

Each line in the source code can appear in different shades of yellow. A more intense color corresponds to more interpreter-related calls, while white lines are translated to regular C code. Since interpreter calls substantially slow down execution, the objective is to make the function body as white as possible. By clicking on any of the lines, we can inspect the code...

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