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Advanced Python Programming

Advanced Python Programming - Second Edition

By : Quan Nguyen
4.6 (14)
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Advanced Python Programming

Advanced Python Programming

4.6 (14)
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)
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1
Section 1: Python-Native and Specialized Optimization
8
Section 2: Concurrency and Parallelism
18
Section 3: Design Patterns in Python

Chapter 20: The Decorator Pattern

As we saw in the previous chapter, using an adapter, the first structural design pattern, you can adapt an object implementing a given interface to implement another interface. This is called interface adaptation and includes the kinds of patterns that encourage composition over inheritance, and it could bring benefits when you have to maintain a large codebase.

A second interesting structural pattern to learn about is the decorator pattern, which allows us to add responsibilities to an object dynamically and transparently (without affecting other objects); this will be the topic of this chapter. Throughout our discussions, we will learn more about a specific usage of this design pattern: memoization.

We will discuss the following topics:

  • Introducing the decorator pattern
  • Real-world examples
  • Use cases
  • Implementation
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Advanced Python Programming
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