Python High Performance Programming 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Gabriele Lanaro 作者

Packt Publishing

译者

2013-12-23 出版日期

108 页数

USD 26.99 价格

Paperback

丛书系列

9781783288458 图书编码

Python High Performance Programming 在线电子书图书标签: python 编程 Python performance 软件开发计算机程序设计性能

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发表于2024-12-29

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Python High Performance Programming 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Python High Performance Programming 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Python High Performance Programming 在线电子书用户评价

评分☆☆☆☆☆

篇幅好少，感觉像没写完

评分☆☆☆☆☆

篇幅好少，感觉像没写完

评分☆☆☆☆☆

篇幅有点短, 没有介绍pypy和cython的比较

评分☆☆☆☆☆

篇幅有点短, 没有介绍pypy和cython的比较

评分☆☆☆☆☆

篇幅有点短, 没有介绍pypy和cython的比较

Python High Performance Programming 在线电子书著者简介

Gabriele Lanaro is a PhD student in Chemistry at the University of British Columbia, in the field of Molecular Simulation. He writes high performance Python code to analyze chemical systems in large-scale simulations. He is the creator of Chemlab—a high performance visualization software in Python—and emacs-for-python—a collection of emacs extensions that facilitate working with Python code in the emacs text editor. This book builds on his experience in writing scientific Python code for his research and personal projects.

Python High Performance Programming 在线电子书图书目录

Python High Performance Programming 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Python High Performance Programming 在线电子书图书描述

Python is a programming language with a vibrant community known for its simplicity, code readability, and expressiveness. The massive selection of third party libraries make it suitable for a wide range of applications. This also allows programmers to express concepts in fewer lines of code than would be possible in similar languages. The availability of high quality numerically-focused tools has made Python an excellent choice for high performance computing. The speed of applications comes down to how well the code is written. Poorly written code means poorly performing applications, which means unsatisfied customers.

This book is an example-oriented guide to the techniques used to dramatically improve the performance of your Python programs. It will teach optimization techniques by using pure python tricks, high performance libraries, and the python-C integration. The book will also include a section on how to write and run parallel code.

This book will teach you how to take any program and make it run much faster. You will learn state-of the art techniques by applying them to practical examples. This book will also guide you through different profiling tools which will help you identify performance issues in your program. You will learn how to speed up your numerical code using NumPy and Cython. The book will also introduce you to parallel programming so you can take advantage of modern multi-core processors.

This is the perfect guide to help you achieve the best possible performance in your Python applications.

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