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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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Lock-based concurrent data structures in Python

In previous chapters that covered the usage of locks, you learned that locks don't lock anything; an insubstantial locking mechanism implemented on a data structure does not actually prevent external programs from accessing the data structure at the same time, by simply bypassing the lock imposed. One solution to this problem is to embed the lock into the data structure, so that it is impossible for the lock to be ignored by external entities.

In the first section of this chapter, we will consider the theories behind the preceding specific use of locks and lock-based data structures. Specifically, we will analyze the process of designing a concurrent counter that can be safely executed by different threads, using locks (or mutex) as the synchronization mechanism.

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