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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We've explored a variety of built-in Python data structures in this chapter. Python lets us do a great deal of object-oriented programming without the overheads of numerous, potentially confusing, class definitions. We can rely on a number of built-in classes where they fit our problem.

In this chapter, we looked at the following:

  • Tuples and named tuples let us leverage a simple collection of attributes. We can extend the NamedTuple definition to add methods when those are necessary.
  • Dataclasses provide sophisticated collections of attributes. A variety of methods can be provided for us, simplifying the code we need to write.
  • Dictionaries are an essential feature, used widely in Python. There are many places where keys are associated with values. The syntax for using the built-in dictionary class makes it easy to use.
  • Lists and sets are also first-class parts of Python; our applications can make use of these.
  • We also looked at...