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)

Advanced Introduction to Concurrent and Parallel Programming

This first chapter of Mastering Concurrency in Python will provide an overview of what concurrent programming is (in contrast to sequential programming). We will briefly discuss the differences between a program that can be made concurrent and one that cannot. We will go over the history of concurrent engineering and programming, and we will provide a number of examples of how concurrent programming is used in the present day. Finally, we will give a brief introduction to the approach that will be taken in this book, including an outline of the chapter structure and detailed instructions for how to download the code and create a working Python environment.

The following topics will be covered in this chapter:

  • The concept of concurrency
  • Why some programs cannot be made concurrent, and how to differentiate them from programs that can
  • The history of concurrency in computer science: how it is used in the industry today, and what can be expected in the future
  • The specific topics that will be covered in each section/chapter of the book
  • How to set up a Python environment, and how to check out/download code from GitHub