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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

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.

Here's a dataclass version of our Stock example:

>>> from dataclasses import dataclass
>>> @dataclass
... class Stock:
...     symbol: str
...     current: float
...     high: float
...     low: float

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

The dataclass function is applied as a class decorator, using the @ operator. We encountered decorators in Chapter 6, Abstract Base Classes and Operator Overloading. We'll dig into them deeply in Chapter 11, Common Design Patterns. This class definition syntax isn't much less verbose than an ordinary class with __init__(), but it gives us access to several additional dataclass...

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