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Elliot Forbes - Learning Concurrency in Python

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Elliot Forbes Learning Concurrency in Python
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Key Features
  • Build highly efficient, robust, and concurrent applications
  • Work through practical examples that will help you address the challenges of writing concurrent code
  • Improve the overall speed of execution in multiprocessor and multicore systems and keep them highly available
Book Description

Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create.

This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. Well cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python.

The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. Well cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems.

By the end of the book, youll have learned the techniques to write incredibly efficient concurrent systems that follow best practices.

What you will learn
  • Explore the concept of threading and multiprocessing in Python
  • Understand concurrency with threads
  • Manage exceptions in child threads
  • Handle the hardest part in a concurrent system shared resources
  • Build concurrent systems with Communicating Sequential Processes (CSP)
  • Maintain all concurrent systems and master them
  • Apply reactive programming to build concurrent systems
  • Use GPU to solve specific problems
About the Author

Elliot Forbes has worked as a full-time software engineer at a leading financial firm for the last two years. He graduated from the University of Strathclyde in Scotland in the spring of 2015 and worked as a freelancer developing web solutions while studying there.

He has worked on numerous different technologies such as GoLang and NodeJS and plain old Java, and he has spent years working on concurrent enterprise systems. It is with this experience that he was able to write this book.

Elliot has even worked at Barclays Investment Bank for a summer internship in London and has maintained a couple of software development websites for the last three years.

Table of Contents
  1. Speed It Up!
  2. How About Parallel It?
  3. Life of Thread
  4. Synchronization Between Threads
  5. Communication Between Threads
  6. Debug and Benchmark Threads
  7. Executors and Pools
  8. Multiprocessing
  9. Event-driven Programming
  10. Reactive Programming
  11. Using GPU
  12. Choosing a Solution

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Learning Concurrency in Python
Speed up your Python code with clean, readable, and advanced concurrency techniques
Elliot Forbes

BIRMINGHAM - MUMBAI Learning Concurrency in Python Copyright 2017 Packt - photo 1
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Learning Concurrency in Python

Copyright 2017 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: August 2017

Production reference: 1140817

Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.

ISBN 978-1-78728-537-8

www.packtpub.com

Credits

Author

Elliot Forbes

Copy Editor

Sonia Mathur

Reviewer

Nikolaus Gradwohl

Project Coordinator

Vaidehi Sawant

Commissioning Editor

Merint Mathew

Proofreader

Safis Editing

Acquisition Editor

Chaitanya Nair

Indexer

Francy Puthiry

Content Development Editor

Rohit Kumar Singh

Graphics

Abhinash Sahu

Technical Editors

Ketan Kamble

Production Coordinator

Nilesh Mohite

About the Author

Elliot Forbes has worked as a full-time software engineer at JPMorgan Chase for the last 2 years. He graduated from the University of Strathclyde in Scotland in the spring of 2015 and worked as a freelancer developing web solutions while studying there.

He has worked on numerous different technologies such as GoLang and NodeJS and plain old Java, and he has spent years working on concurrent enterprise systems. It is with this experience that he was able to write this book.

Elliot has even worked at Barclays Investment Bank for a summer internship in London and has maintained a couple of software development websites for the last 3 years.

About the Reviewer

Nikolaus Gradwohl was born 1976 in Vienna, Austria and always wanted to become an inventor like Gyro Gearloose. When he got his first Atari, he figured out that being a computer programmer is the closest he could get to that dream. For a living, he wrote programs for nearly anything that can be programmed, ranging from an 8-bit microcontroller to mainframes. In his free time, he likes to master on programming languages and operating systems.

Nikolaus authored the Processing 2: Creative Coding Hotshot book, and you can see some of his work on his blog at http://www.local-guru.net/.

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Table of Contents
Preface

Python is a very high-level, general-purpose language that features a large number of powerful high-level and low-level libraries and frameworks that complement its delightful syntax. This easy-to-follow guide teaches you new practices and techniques to optimize your code and then moves on to more advanced ways to effectively write efficient Python code. Small and simple practical examples will help you test the concepts introduced, and you will be able to easily adapt them to any application.

Throughout this book, you will learn to build highly efficient, robust, and concurrent applications. You will work through practical examples that will help you address the challenges of writing concurrent code, and also you will learn to improve the overall speed of execution in multiprocessor and multicore systems and keep them highly available.

What this book covers

, Speed It Up!, helps you get to grips with threads and processes, and you'll also learn about some of the limitations and challenges of Python when it comes to implementing your own concurrent applications.

, Parallelize It, covers a multitude of topics including the differences between concurrency and parallelism. We will look at how they both leverage the CPU in different ways, and we also branch off into the topic of computer system design and how it relates to concurrent and parallel programming.

, Life of a Thread, delves deeply into the workings of Python's native threading library. We'll look at the numerous different thread types. We'll also look in detail at various concepts such as the multithreading model and the numerous ways in which we can make user threads to their lower-level siblings, the kernel threads.

, Synchronization between Threads, covers the various key issues that can impact our concurrent Python applications. We will delve into the topic of deadlocks and the famous "dining philosophers" problem and see how this can impact our own software.

, Communication between Threads, discusses quite a number of different mechanisms that we can employ to implement communication in our multithreaded systems. We delve into the thread-safe queue primitives that Python features natively.

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