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

In this chapter, we've looked at the following topics:

  • The ways to encode strings into bytes and decode bytes into strings. While some older character encodings (like ASCII) treat bytes and characters alike, this leads to confusion. Python text can be any Unicode character and Python bytes are numbers in the range 0 to 255.
  • String formatting lets us prepare string objects that have template pieces and dynamic pieces. This works for a lot of situations in Python. One is to create readable output for people, but we can use f-strings and the string format() method everywhere we're creating a complex string from pieces.
  • We use regular expressions to decompose complex strings. In effect, a regular expression is the opposite of a fancy string formatter. Regular expressions struggle to separate the characters we're matching from "meta-characters" that provide additional matching rules, like repetition or alternative choices.
  • We...