Python Parallel Programming Cookbook: Over 70 recipes to solve challenges in multithreading and distributed system with Python 3, 2nd Edition (English Edition)

Python Parallel Programming Cookbook: Over 70 recipes to solve challenges in multithreading and distributed system with Python 3, 2nd Edition (English Edition)

作者
Giancarlo Zaccone
语言
英语
出版社
Packt Publishing 版次:2
出版日期
2019年9月6日
纸书页数
370页
电子书格式
epub,pdf,mobi,azw3,txt,fb2,djvu
文件大小
10833 KB
下载次数
2506
更新日期
2023-06-09
运行环境
PC/Windows/Linux/Mac/IOS/iPhone/iPad/iBooks/Kindle/Android/安卓/平板
内容简介

Implement effective programming techniques in Python to build scalable software that saves time and memory

Key Features

Design distributed computing systems and massive computational tasks coherently

Learn practical recipes with concise explanations that address development pain points encountered while coding parallel programs

Understand how to host your parallelized applications on the cloud

Book Description

Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable.

This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications.

By the end of this book, you will be confident in building concurrent and high-performing applications in Python.

What you will learn

Synchronize multiple threads and processes to manage parallel tasks

Use message passing techniques to establish communication between processes to build parallel applications

Program your own GPU cards to address complex problems

Manage computing entities to execute distributed computational task

Write efficient programs by adopting the event-driven programming model

Explore cloud technology with Django and Google App Engine

Apply parallel programming techniques that can lead to performance improvements

Who this book is for

The Python Parallel Programming Cookbook is for software developers who are well-versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing. Table of Contents

Getting Started with Parallel Computing and Python

Thread-based Parallelism

Process-based Parallelism

Message Passing

Asynchronous Programming

Distributed Python

Cloud Computing

Heterogeneous Computing

Python Debugging and Testing

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