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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

In this chapter's case study, we'll revisit our design, leveraging Python's @dataclass definitions. This holds some potential for streamlining our design. We'll be looking at some choices and limitations; this will lead us to explore some difficult engineering trade-offs, where there isn't one obvious best approach.

We'll also look at immutable NamedTuple class definitions. These objects have no internal state changes, leading to the possibility of some design simplifications. This will also change our design to make less use of inheritance and more use of composition.

Logical model

Let's review the design we have so far for our model.py module. This shows the hierarchy of Sample class definitions, used to reflect the various ways samples are used:

Figure 7.2: Class diagram so far

The various Sample classes are a very good fit with the dataclass definition. These objects have a number...

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