Book Image

Advanced Python Programming - Second Edition

By : Quan Nguyen
Book Image

Advanced Python Programming - Second Edition

By: Quan Nguyen

Overview of this book

Python's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages. In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level. This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models. The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming. You'll also understand the common problems that cause undesirable behavior in concurrent programs. Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable. By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.
Table of Contents (32 chapters)
1
Section 1: Python-Native and Specialized Optimization
8
Section 2: Concurrency and Parallelism
18
Section 3: Design Patterns in Python

Image processing fundamentals

Digital/computational image processing (which we will refer to as image processing from this point forward) has become so popular in the modern era that it exists in numerous aspects of our everyday life. Image processing and manipulation are involved when you take a picture with your camera or phone using different filters, such as when advanced image editing software such as Adobe Photoshop is used, or even when you simply edit images using Microsoft Paint.

Many of the techniques and algorithms that are used in image processing were developed in the early 1960s for various purposes such as medical imaging, satellite image analysis, character recognition, and so on. However, these image processing techniques required significant computing power, and the fact that the available computer equipment at the time was unable to accommodate the need for fast number-crunching slowed down the use of image processing.

Fast-forwarding to the future, when powerful...