Book Image

Python Object-Oriented Programming - Fourth Edition

By : Steven F. Lott, Dusty Phillips
2 (1)
Book Image

Python Object-Oriented Programming - Fourth Edition

2 (1)
By: Steven F. Lott, Dusty Phillips

Overview of this book

Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python’s classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python’s exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs.
Table of Contents (17 chapters)
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Here are some of the key points in this chapter:

  • Using abstract base class definitions is a way to create class definitions with placeholders. This is a handy technique, and can be somewhat clearer than using raise NotImplementedError in unimplemented methods.
  • ABCs and type hints provide ways to create class definitions. An ABC is a type hint that can help to clarify the essential features we need from an object. It's common, for example, to use Iterable[X] to emphasize that we need one aspect of a class implementation.
  • The module defines abstract base classes for Python's built-in collections. When we want to make our own unique collect class that can integrate seamlessly with Python, we need to start with the definitions from this module.
  • Creating your own abstract base class leverages the abc module. The abc.ABC class definition is often a perfect starting point for creating an abstract base class.
  • The bulk of...