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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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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

Dictionaries

Dictionaries are incredibly useful containers that allow us to map objects directly to other objects. Dictionaries are extremely efficient at looking up a value, given a specific key object that maps to that value. The secret of the speed is using a hash of the key to locate the value. Every immutable Python object has a numeric hash code; a relatively simple table is used to map the numeric hashes directly to values. This trick means a dictionary never searches the entire collection for a key; the key is transformed to a hash, which locates the associated value (almost) immediately.

Dictionaries can be created either using the dict() constructor or the {} syntax shortcut. In practice, the latter format is almost always used. We can prepopulate a dictionary by separating the keys from the values using a colon and separating the key-value pairs using a comma.

We can also create dictionaries using keyword parameters. We can use dict(current=1235...

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