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Mastering Object-Oriented Python

You're reading from   Mastering Object-Oriented Python Build powerful applications with reusable code using OOP design patterns and Python 3.7

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781789531367
Length 770 pages
Edition 2nd Edition
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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 (25) Chapters Close

Preface 1. Section 1: Tighter Integration Via Special Methods FREE CHAPTER
2. Preliminaries, Tools, and Techniques 3. The __init__() Method 4. Integrating Seamlessly - Basic Special Methods 5. Attribute Access, Properties, and Descriptors 6. The ABCs of Consistent Design 7. Using Callables and Contexts 8. Creating Containers and Collections 9. Creating Numbers 10. Decorators and Mixins - Cross-Cutting Aspects 11. Section 2: Object Serialization and Persistence
12. Serializing and Saving - JSON, YAML, Pickle, CSV, and XML 13. Storing and Retrieving Objects via Shelve 14. Storing and Retrieving Objects via SQLite 15. Transmitting and Sharing Objects 16. Configuration Files and Persistence 17. Section 3: Object-Oriented Testing and Debugging
18. Design Principles and Patterns 19. The Logging and Warning Modules 20. Designing for Testability 21. Coping with the Command Line 22. Module and Package Design 23. Quality and Documentation 24. Other Books You May Enjoy

Design considerations and tradeoffs

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 of existing class definitions. In many cases, a list of tuple objects or a dict of lists provides the needed features.
  4. Consider extending one of the earlier mentioned classes to provide additional methods or attributes.
  5. Consider wrapping an existing structure as another way to provide additional methods or attributes.
  6. Finally, consider a novel data structure. Generally, there is a lot of careful analysis available. Start with Wikipedia articles such as this one: http://en.wikipedia.org/wiki/List_of_data_structures.

Once the design alternatives have been identified, there...

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