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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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The basics of web requests

The worldwide capacity to generate data is estimated to double in size every two years. Even though there is an interdisciplinary field known as data science that is entirely dedicated to the study of data, almost every programming task in software development also has something to do with collecting and analyzing data. A significant part of this is, of course, data collection. However, the data that we need for our applications is sometimes not stored nicely and cleanly in a database—sometimes, we need to collect the data we need from web pages.

For example, web scraping is a data extraction method that automatically makes requests to web pages and downloads specific information. Web scraping allows us to comb through numerous websites and collect any data we need in a systematic and consistent manner—the collected data can be analyzed...

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