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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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Chapter 10

What is asynchronous programming? What advantages does it provide?

Asynchronous programming is a model of programming that takes advantage of coordinating computing tasks to overlap the waiting and processing times. If successfully implemented, asynchronous programming provides both responsiveness and an improvement in speed, as compared to synchronous programming.

What are the main elements in an asynchronous program? How do they interact with each other?

There are three main components of an asynchronous program: the event loop, the coroutines, and the futures. The event loop is in charge of scheduling and managing coroutines by using its task queue; the coroutines are computing tasks that are to be executed asynchronously, and each coroutine has to specify, inside its function, exactly where it will give the execution flow back to the event loop (that is, the task...

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