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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

Lists

Python's generic list structure is integrated into a number of language features. We don't need to import them and rarely need to use method syntax to access their features. We can visit all the items in a list without explicitly requesting an iterator object, and we can construct a list (as with a dictionary) with very simple-looking syntax. Further, list comprehensions and generator expressions turn them into a veritable Swiss Army knife of computing functionality.

If you don't know how to create or append to a list, how to retrieve items from a list, or what slice notation is, we direct you to the official Python tutorial, posthaste. It can be found online at http://docs.python.org/3/tutorial/. In this section, we'll move beyond the basics to cover when lists should be used, and their nature as objects.

In Python, lists should normally be used when we want to store several instances of the same type of object; lists of strings...

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