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Mastering Concurrency in Python

Mastering Concurrency in Python

By : Quan Nguyen
1 (1)
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Mastering Concurrency in Python

Mastering Concurrency in Python

1 (1)
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)
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Client-side communication with aiohttp

In previous sections, we covered examples of implementing asynchronous communication channels with the asyncio module, mostly from the perspective of the server side of the communication process. In other words, we have been considering handling and processing requests sent from external systems. This, however, is only one side of the equation, and we also have the client side of communication to explore. In this section, we will discuss applying asynchronous programming to make requests to servers.

As you have most likely guessed, the end goal of this process is to efficiently collect data from external systems by asynchronously making requests to those systems. We will be revisiting the concept of web scraping, which is the process of automating HTTP requests to various websites and extracting specific information from their HTML source...

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