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Python Object-Oriented Programming

Python Object-Oriented Programming - Fifth Edition

By : Steven F. Lott, Dusty Phillips
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Python Object-Oriented Programming

Python Object-Oriented Programming

By: Steven F. Lott, Dusty Phillips

Overview of this book

Learn to write effective, maintainable, and scalable Python applications by mastering object-oriented programming with this updated fifth edition. Whether you’re transitioning from scripting to structured development or refining your OOP skills, this book offers a clear, practical path forward. You’ll explore Python’s approach to OOP, from class creation and inheritance to polymorphism and abstraction, while discovering how to make smarter decisions about when and how to use these tools. You’ll apply what you learn through hands-on examples and exercises. Updated for Python 3.13, this edition simplifies complex topics such as abstract base classes, testing with unittest and pytest, and async programming with asyncio. It introduces a new chapter on Python’s type hinting ecosystem—crucial for modern Python development. Written by long-time Python experts Steven Lott and Dusty Phillips, this edition emphasizes clarity, testability, and professional software engineering practices. It helps you move beyond scripting to building well-structured, production-ready Python systems. By the end of this book, you’ll be confident in applying OOP principles, design patterns, type hints, and concurrency tools to create robust and maintainable Python applications.
Table of Contents (17 chapters)
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16
Index

13.4 Imitating objects using mocks

Isolated problems are easier to diagnose and solve. Figuring out why a gasoline car won’t start can be tricky because there are so many interrelated parts. If a test fails, uncovering all the interrelationships among software components makes diagnosis of the problem difficult. We often want to isolate items by providing simplified imitations. It turns out there are two reasons to replace perfectly good code with imitation (or “mock”) objects:

  • The most common case is to isolate a unit under test. We want to create collaborating classes and functions so we can test one unknown component in an environment of known, trusted test fixtures.

  • Sometimes, we want to test code that requires an object that is either expensive or risky to use. Things such as shared databases, filesystems, and cloud infrastructures can be very expensive to set up and tear down for testing.

    ...
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Python Object-Oriented Programming
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