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)

Concurrent web requests

In the context of concurrent programming, we can see that the process of making a request to a web server and obtaining the returned response is independent from the same procedure for a different web server. This is to say that we could apply concurrency and parallelism to our ping test application to speed up our execution.

In the concurrent ping test applications that we are designing, multiple HTTP requests will be made to the server simultaneously and corresponding responses will be sent back to our program, as shown in the following figure. As discussed before, concurrency and parallelism have significant applications in web development, and most servers nowadays have the ability to handle a large amount of requests at the same time:

Parallel HTTP requests
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