Book Image

Advanced Python Programming

By : Dr. Gabriele Lanaro, Quan Nguyen, Sakis Kasampalis
Book Image

Advanced Python Programming

By: Dr. Gabriele Lanaro, Quan Nguyen, Sakis Kasampalis

Overview of this book

This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: • Python High Performance - Second Edition by Gabriele Lanaro • Mastering Concurrency in Python by Quan Nguyen • Mastering Python Design Patterns by Sakis Kasampalis
Table of Contents (41 chapters)
Title Page
About Packt

Chapter 27. The Decorator Pattern

As we saw in the previous chapter, using an adapter, a 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 a programmer to add responsibilities to an object dynamically, and in a transparent manner (without affecting other objects).

There is another reason why this pattern is interesting to us, as you will see in a minute.

As Python developers, we can write decorators in a Pythonic way (meaning using the language's features), thanks to the built-in decorator feature ( What exactly is this feature? A Python decorator is a callable (function, method,...