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 this chapter, you learned about asynchronous programming, which is a model of programming that takes advantage of coordinating computing tasks to overlap the waiting and processing times. There are three main components to an asynchronous program: the event loop, the coroutines, and the futures. The event loop is in charge of scheduling and managing coroutines using its task queue. Coroutines are computing tasks that are to be executed asynchronously; each coroutine has to specify inside of its function exactly where it will give the execution flow back to the event loop (that is, the task-switching event). Futures are placeholder objects that contain the results obtained from the coroutines.

The asyncio module, together with the Python keywords async and await, provides an easy-to-use API and an intuitive framework to implement asynchronous programs; additionally,...