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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Some key points in this chapter:

  • Python has optional type hints to help describe how data objects are related and what the parameters should be for methods and functions.
  • We create Python classes with the class statement. We should initialize the attributes in the special __init__() method.
  • Modules and packages are used as higher-level groupings of classes.
  • We need to plan out the organization of module content. While the general advice is "flat is better than nested," there are a few cases where it can be helpful to have nested packages.
  • Python has no notion of "private" data. We often say "we're all adults here"; we can see the source code, and private declarations aren't very helpful. This doesn't change our design; it simply removes the need for a handful of keywords.
  • We can install third-party packages using PIP tools. We can create a virtual environment, for example, with venv.