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Mastering Object-oriented Python

You're reading from   Mastering Object-oriented Python If you want to master object-oriented Python programming this book is a must-have. With 750 code samples and a relaxed tutorial, it's a seamless route to programming Python.

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Product type Paperback
Published in Apr 2014
Publisher Packt
ISBN-13 9781783280971
Length 634 pages
Edition Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (26) Chapters Close

Mastering Object-oriented Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Some Preliminaries
1. The __init__() Method FREE CHAPTER 2. Integrating Seamlessly with Python Basic Special Methods 3. Attribute Access, Properties, and Descriptors 4. The ABCs of Consistent Design 5. Using Callables and Contexts 6. Creating Containers and Collections 7. Creating Numbers 8. Decorators and Mixins – Cross-cutting Aspects 9. Serializing and Saving – JSON, YAML, Pickle, CSV, and XML 10. Storing and Retrieving Objects via Shelve 11. Storing and Retrieving Objects via SQLite 12. Transmitting and Sharing Objects 13. Configuration Files and Persistence 14. The Logging and Warning Modules 15. Designing for Testability 16. Coping With the Command Line 17. The Module and Package Design 18. Quality and Documentation Index

Summary


In this chapter, we looked at a number of built-in class definitions. The built-in collections are the starting place for most design work. We'll often start with tuple, list, dict, or set. We can leverage the extension to tuple, created by namedtuple(), for an application's immutable objects.

Beyond these classes, we have other standard library classes in the collections mode that we can use:

  • deque

  • ChainMap

  • OrderedDict

  • defaultdict

  • Counter

We have three standard design strategies, too. We can wrap any of these existing classes, or we can extend a class.

Finally, we can also invent an entirely new kind of collection. This requires defining a number of method names and special methods.

Design considerations and Trade-offs

When working with containers and collections, we have a multistep design strategy:

  1. Consider the built-in versions of sequence, mapping, and set.

  2. Consider the library extensions in the collection module as well as extras such as heapq, bisect, and array.

  3. Consider a composition...

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