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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
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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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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

Dictionaries


Dictionaries are incredibly useful containers that allow us to map objects directly to other objects. An empty object with attributes to it is a sort of dictionary; the names of the properties map to the property values. This is actually closer to the truth than it sounds; internally, objects normally represent attributes as a dictionary, where the values are properties or methods on the objects (see the __dict__ attribute if you don't believe me). Even the attributes on a module are stored, internally, in a dictionary.

Dictionaries are extremely efficient at looking up a value, given a specific key object that maps to that value. They should always be used when you want to find one object based on some other object. The object that is being stored is called the value; the object that is being used as an index is called the key. We've already seen dictionary syntax in some of our previous examples.

Dictionaries can be created either using the dict() constructor or using the {...

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