Book Image

Mastering Concurrency in Python

By : Quan Nguyen
Book Image

Mastering Concurrency in Python

By: Quan Nguyen

Overview of this book

Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming. Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples. By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language
Table of Contents (22 chapters)

Preface

Concurrency can be notoriously difficult to get right, but fortunately, the Python programming language makes working with concurrency tractable and easy. This book shows how Python can be used to program high-performance, robust, concurrent programs with its unique form of programming.

Designed for any curious developer with an interest in building fast, non-blocking, and resource-thrifty systems applications, this book will cover the best practices and patterns to help you incorporate concurrency into your systems. Additionally, emerging topics in Python concurrent programming will be discussed, including the new AsyncIO syntax, the widely accepted view that "locks don't lock anything," the use of atomic message queues, concurrent application architecture, and best practices.

We will tackle complex concurrency concepts and models via hands-on and engaging code examples. Having read this book, you will have gained a deep understanding of the principal components in the Python concurrency ecosystem, as well as a practical appreciation of different approaches to a real-life concurrency problem.