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)
15
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16
Index

Recall

Here are some of the key points in this chapter:

  • When we have both data and behavior, this is the sweet spot for object-oriented design. We can leverage Python's generic collections and ordinary functions for many things. When it becomes complex enough that we need to be sure that pieces are all defined together, then we need to start using classes.
  • When an attribute value is a reference to another object, the Pythonic approach is to allow direct access to the attribute; we don't write elaborate setter and getter functions. When an attribute value is computed, we have two choices: we can compute it eagerly or lazily. A property lets us be lazy and do the computation just in time.
  • We'll often have cooperating objects; the behavior of the application emerges from the cooperation. This can often lead to manager objects that combine behaviors from component class definitions to create an integrated, working whole.