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Python Object-Oriented Programming

You're reading from   Python Object-Oriented Programming Build robust and maintainable object-oriented Python applications and libraries

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781801077262
Length 714 pages
Edition 4th Edition
Languages
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Author (1):
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Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Toc

Table of Contents (17) Chapters Close

Preface 1. Object-Oriented Design 2. Objects in Python FREE CHAPTER 3. When Objects Are Alike 4. Expecting the Unexpected 5. When to Use Object-Oriented Programming 6. Abstract Base Classes and Operator Overloading 7. Python Data Structures 8. The Intersection of Object-Oriented and Functional Programming 9. Strings, Serialization, and File Paths 10. The Iterator Pattern 11. Common Design Patterns 12. Advanced Design Patterns 13. Testing Object-Oriented Programs 14. Concurrency 15. Other Books You May Enjoy
16. Index

Case study

We'll review a piece of the case study we set aside in Chapter 3, When Objects Are Alike. We talked about the various ways to compute distances, but left part of the design to be filled in later. Now that we've seen some of the basic design patterns, we can apply some of them to our evolving case study.

Specifically, we need to put the various kinds of distance computations into the Hyperparameter class definition. In Chapter 3, we introduced the idea that the distance computation is not a single definition. There are over 50 commonly used distance computation alternatives, some simple, some rather complex. In Chapter 3, we showed a few common ones, including Euclidean distance, Manhattan distance, Chebyshev distance, and even a complex-looking Sorensen distance. Each weights the "nearness" of the neighbors slightly differently.

This leads us to look at the Hyperparameter class as containing three important components:

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