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)

Summary

In the field of computer science, a process is an instance of a specific computer program or software that is being executed by the operating system. A process contains both the program code and its current activities and interactions with other entities. More than one thread can be implemented within the same process to access and share memory or other resources, while different processes do not interact in this way.

In the context of concurrency and parallelism, multiprocessing refers to the execution of multiple concurrent processes from an operating system, in which each process is executed on a separate CPU, as opposed to a single process being executed at any given time. The multiprocessing module in Python provides a powerful and flexible API to spawn and manage processes for a multiprocessing application. It also allows complex techniques for interprocess communication...