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)

Chapter 1

What is the idea behind concurrency, and why is it useful?

Concurrency is about designing and structuring program commands and instructions so that different sections of the program can be executed in an efficient order, while sharing the same resources.

What are the differences between concurrent programming and sequential programming?

In sequential programming, the commands and instructions are executed one at the time, in a sequential order. In concurrent programming, some sections might be executed in an efficient way for better execution time.

What are the differences between concurrent programming and parallel programming?

In parallel programming, the separate sections of a program are independent of one another; they do not interact with one another, and therefore, they can be executed simultaneously. In concurrent programming, the separate tasks share the same...