Book Image

Mastering Object-Oriented Python - Second Edition

By : Steven F. Lott
Book Image

Mastering Object-Oriented Python - Second Edition

By: Steven F. Lott

Overview of this book

Object-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language's unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you'll be shown how to effectively implement OOP in Python, and even explore Python 3.x. Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design offers the best performance. Next, you'll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you'll discover how essential it is to locate the best algorithms and optimal data structures for developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs. By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python.
Table of Contents (25 chapters)
Free Chapter
1
Section 1: Tighter Integration Via Special Methods
11
Section 2: Object Serialization and Persistence
17
Section 3: Object-Oriented Testing and Debugging

ABCs of collections

The collections.abc module provides a wealth of ABCs that decompose collections into a number of discrete feature sets. A related set of features of a class is called a protocol: the idea is that things such as getting, setting, and deleting items are the protocol for list-like behavior. Similarly, the __iter__() method is part of the protocol for defining an iterable collection. A list often implements both protocols, but some data structures may support fewer protocols. Support for a given protocol is often exploited by mypy algorithms to determine whether an object is being used properly.

We can successfully use the list class without thinking too deeply about the various features and how they relate to the set class or the dict class. Once we start looking at the ABCs, however, we can see that there's a bit of subtlety to these classes. By decomposing...