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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

Some additional abstractions


We'll look at some other interesting ABC classes that are less widely extended. It's not that these abstractions are less widely used. It's more that the concrete implementations rarely need extensions or revisions.

We'll look at the iterator, which is defined by collections.abc.Iterator. We'll also look at the unrelated idea of a context manager. This isn't defined with the same formality as other ABC classes. We'll look at this in detail in Chapter 5, Using Callables and Contexts.

The iterator abstraction

Iterators are created implicitly when we use an iterable container with a for statement. We rarely care about the iterator itself. And the few times we do care about the iterator, we rarely want to extend or revise the class definition.

We can expose the implicit iterators that Python uses via the iter() function. We can interact with an iterator in the following way:

>>> x = [ 1, 2, 3 ]
>>> iter(x)
<list_iterator object at 0x1006e3c50>...
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