Book Image

Python Object-Oriented Programming - Fourth Edition

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

Python Object-Oriented Programming - Fourth Edition

2 (2)
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

Case study

While object-oriented programming is helpful for encapsulating features, it's not the only way to create flexible, expressive, and succinct application programs. Functional programming emphasizes functional design and function composition over object-oriented design.

In Python, functional design often involves using a few object-oriented techniques. This is one of the beauties of Python: being able to choose an appropriate set of design tools to address the problem effectively.

We often depict object-oriented designs with the classes and their various associations. For functional design, we're interested in functions to transform objects. A functional design can follow mathematical practices closely.

In this part of the case study, we'll revisit a number of features of the classifier as functions mixed with class definitions. We'll step away from a pure object-oriented view and adopt a hybrid view. In particular, we'll look closely at...