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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

Context manager as a factory


We can create a context manager class, which is a factory for an application object. This gives us a pleasant separation of design considerations without cluttering up an application class with context management features.

Let's say we want a deterministic Deck for dealing in blackjack. This isn't as useful as it might sound. For unit testing, we'll need a completely mock deck with specific sequences of cards. This has the advantage that the context manager works with the classes we already saw.

We'll extend the simple context manager shown earlier to create a Deck that can be used within the with statement context.

The following is a class that is a factory for Deck and also tweaks the random module:

class Deterministic_Deck:
    def __init__( self, *args, **kw ):
        self.args= args
        self.kw= kw
    def __enter__( self ):
        self.was= random.getstate()
        random.seed( 0, version=1 )
        return Deck( *self.args, **self.kw )
    def __exit__...
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