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  • Book Overview & Buying Python High Performance, Second Edition
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Python High Performance, Second Edition

Python High Performance, Second Edition - Second Edition

By : Dr. Gabriele Lanaro
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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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Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "To summarize, we will implement a method called ParticleSimulator.evolve_numpy and benchmark it against the pure Python version, renamed as ParticleSimulator.evolve_python"

A block of code is set as follows:

    def square(x):
return x * x

inputs = [0, 1, 2, 3, 4]
outputs = pool.map(square, inputs)

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

    def square(x):
return x * x

inputs = [0, 1, 2, 3, 4]
outputs = pool.map(square, inputs)

Any command-line input or output is written as follows:

$ time python -c 'import pi; pi.pi_serial()' 
real 0m0.734s
user 0m0.731s
sys 0m0.004s

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "On the right, clicking on the tab Callee Map will display a diagram of the function costs."

Warnings or important notes appear in a box like this.
Tips and tricks appear like this.
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Programming languages
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Python High Performance, Second Edition
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