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Python Object-Oriented Programming

You're reading from   Python Object-Oriented Programming Learn how and when to apply OOP principles to build scalable and maintainable Python applications

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Product type Paperback
Published in Nov 2025
Publisher Packt
ISBN-13 9781836642596
Length 542 pages
Edition 5th Edition
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Authors (2):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Toc

Table of Contents (17) Chapters Close

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

8.2 Dataclasses

Since Python 3.7, dataclasses let us define ordinary objects with a clean syntax for specifying attributes. They look – superficially – very similar to named tuples. This is a pleasant approach that makes it easy to understand how they work. For more details, see Modern Python Cookbook, Chapter 7 for recipes related to dataclasses.

Here’s a dataclass version of our Stock example:

from decimal import Decimal 
from dataclasses import dataclass 
 
 
@dataclass 
class Stock: 
    symbol: str 
    current: Decimal 
    high: Decimal 
    low: Decimal

For this case, the definition is nearly identical to the NamedTuple definition.

The @dataclass decorator transforms the given code into a more complete class. We encountered decorators in  Chapter 6. We’ll dig into them deeply in  Chapter 11.

As with NamedTuple, it’...

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