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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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Chapter 8

What is an image processing task?

Image processing is the task of analyzing and manipulating digital image files to create new versions of the images, or to extract important data from them.

What is the smallest unit of digital imaging? How is it represented in computers?

The smallest unit of digital imaging is a pixel, which typically contains an RGB value: a tuple of integers between 0 and 255.

What is grayscaling? What purpose does the technique serve?

Grayscaling is the process of converting an image to gray colors by considering only the intensity information of each pixel, represented by the amount of light available. It reduces the dimensionality of the image pixel matrix by mapping traditional three-dimensional color data to one-dimensional gray data.

What is thresholding? What purpose does the technique serve?

Thresholding replaces each pixel in an image with...

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