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

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 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 like shared databases, filesystems, and cloud infrastructures can be very expensive to set up and tear down for testing.

In some cases, this may lead to designing an API to have a testable interface. Designing...