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Python 3 Object-Oriented Programming - Second Edition

You're reading from   Python 3 Object-Oriented Programming - Second Edition Building robust and maintainable software with object oriented design patterns in Python

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Product type Paperback
Published in Aug 2015
Publisher Packt
ISBN-13 9781784398781
Length 460 pages
Edition 1st 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 (15) Chapters Close

Preface 1. Object-oriented Design FREE CHAPTER 2. Objects in Python 3. When Objects Are Alike 4. Expecting the Unexpected 5. When to Use Object-oriented Programming 6. Python Data Structures 7. Python Object-oriented Shortcuts 8. Strings and Serialization 9. The Iterator Pattern 10. Python Design Patterns I 11. Python Design Patterns II 12. Testing Object-oriented Programs 13. Concurrency Index

Sets


Lists are extremely versatile tools that suit most container object applications. But they are not useful when we want to ensure objects in the 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 if 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 (usually) unique numbers. We can add a number to a set five times, but it will show up in the set only once.

In Python, sets can hold any hashable object, not just numbers. Hashable objects are the same objects that can be used as keys in dictionaries; so again, lists and dictionaries are out. Like mathematical sets, they can store only one copy of each object. So if we're trying to create a list of song artists, we can create a set of string names and simply add them to the set. This example...

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