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Mastering Concurrency in Python

Mastering Concurrency in Python

By : Quan Nguyen
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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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Testing and concurrency in Python

As mentioned previously, testing is an essential (yet often overlooked) component of software development specifically, and programming in general. The goal of testing is to evoke errors that would indicate the existence of bugs in our programs. This is to be contrasted with the process of debugging, which is used to identify the bugs themselves; we will discuss the topic of debugging in the next section.

In the most general sense, testing is about determining whether specific functions and methods can perform and produce results that we intend them to; this is typically done by comparing the results that are produced. In other words, testing is collecting evidence as to the correctness of our programs.

However, testing cannot ensure that all potential defects and bugs in the program under consideration will be identified. Additionally, the test...

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