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)

Mutex-free concurrent data structures in Python

The previous subsection concluded our discussion of designing a lock-based concurrent data structure in Python, and the complexities involved therein. We will now move on to one approach to the theoretical design of mutex-free concurrent data structures.

The term mutex-free in concurrent data structures indicates the lack of a locking mechanism to protect the integrity of the data structure. This does not mean that the data structure simply disregards the protection of its data; instead, the data structure has to employ other synchronization mechanisms. In this section, we will analyze one such mechanism, known as read-copy-update, and discuss how to apply it to a Python data structure.

The impossibility of being lock-free in Python

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