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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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Interprocess communication

While locks are one of the most common synchronization primitives that are used for communication among threads, pipes and queues are the main way of communicating between different processes. Specifically, they provide message-passing options to facilitate communication between processes—pipes for connections between two processes and queues for multiple producers and consumers.

In this section, we will be exploring the usage of queues, specifically the Queue class from the multiprocessing module. The implementation of the Queue class is, in fact, both thread-and process-safe, and we have already seen the use of queues in Chapter 3, Working with Threads in Python. All pickleable objects in Python can be passed through a Queue object; in this section, we will be using queues to pass messages back and forth between processes.

Using a message queue...

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