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Python Object-Oriented Programming - Fourth Edition

You're reading from  Python Object-Oriented Programming - Fourth Edition

Product type Book
Published in Jul 2021
Publisher Packt
ISBN-13 9781801077262
Pages 714 pages
Edition 4th Edition
Languages
Authors (2):
Steven F. Lott Steven F. Lott
Profile icon Steven F. Lott
Dusty Phillips Dusty Phillips
Profile icon Dusty Phillips
View More author details

Table of Contents (17) Chapters

Preface 1. Object-Oriented Design 2. Objects in Python 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

Sets

Lists are extremely versatile tools that suit many container object applications. But they are not useful when we want to ensure that objects in a list are unique. For example, a song library may contain many songs by the same artist. If we want to sort through the library and create a list of all the artists, we would have to check the list to see whether we've added the artist already, before we add them again.

This is where sets come in. Sets come from mathematics, where they represent an unordered group of unique items. We can try to add an item to a set five times, but the "is a member of a set" doesn't change after the first time we add it.

In Python, sets can hold any hashable object, not just strings or numbers. Hashable objects implement the __hash__() method; these are the same objects that can be used as keys in dictionaries; so again, mutable lists, sets, and dictionaries are out. Like mathematical sets, they can store only one copy of...

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