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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
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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

Multi-strategy __init__()


We may have objects that are created from a variety of sources. For example, we might need to clone an object as part of creating a memento, or freeze an object so that it can be used as the key of a dictionary or placed into a set; this is the idea behind the set and frozenset built-in classes.

There are several overall design patterns that have multiple ways to build an object. One design pattern is complex __init__() that is called multi-strategy initialization. Also, there are multiple class-level (static) constructor methods.

These are incompatible approaches. They have radically different interfaces.

Tip

Avoid clone methods

A clone method that unnecessarily duplicates an object is rarely needed in Python. Using cloning may be an indication of failure to understand the object-oriented design principles available in Python.

A clone method encapsulates the knowledge of object creation in the wrong place. The source object that's being cloned cannot know about the structure of the target object that was built from the clone. However, the reverse (targets having knowledge about a source) is acceptable if the source provides a reasonably well-encapsulated interface.

The examples we have shown here are effectively cloning because they're so simple. We'll expand on them in the next chapter. However, to show ways in which these fundamental techniques are used to do more than trivial cloning, we'll look at turning a mutable Hand object into a frozen, immutable Hand object.

The following is an example of a Hand object that can be built in either of the two ways:

class Hand3:
    def __init__( self, *args, **kw ):
        if len(args) == 1 and isinstance(args[0],Hand3):
            # Clone an existing hand; often a bad idea
            other= args[0]
            self.dealer_card= other.dealer_card
            self.cards= other.cards
        else:
            # Build a fresh, new hand.
            dealer_card, *cards = args
            self.dealer_card=  dealer_card
            self.cards= list(cards)

In the first case, a Hand3 instance has been built from an existing Hand3 object. In the second case, a Hand3 object has been built from individual Card instances.

This parallels the way a frozenset object can be built from individual items or an existing set object. We look more at creating immutable objects in the next chapter. Creating a new Hand from an existing Hand allows us to create a memento of a Hand object using a construct like the following code snippet:

h = Hand( deck.pop(), deck.pop(), deck.pop() )
memento= Hand( h )

We saved the Hand object in the memento variable. This can be used to compare the final with the original hand that was dealt, or we can freeze it for use in a set or mapping too.

More complex initialization alternatives

In order to write a multi-strategy initialization, we're often forced to give up on specific named parameters. This design has the advantage that it is flexible, but the disadvantage that it has opaque, meaningless parameter names. It requires a great deal of documentation explaining the variant use cases.

We can expand our initialization to also split a Hand object. The result of splitting a Hand object is simply another constructor. The following code snippet shows how the splitting of a Hand object might look:

class Hand4:
    def __init__( self, *args, **kw ):
        if len(args) == 1 and isinstance(args[0],Hand4):
            # Clone an existing handl often a bad idea
            other= args[0]
            self.dealer_card= other.dealer_card
            self.cards= other.cards
        elif len(args) == 2 and isinstance(args[0],Hand4) and 'split' in kw:
            # Split an existing hand
            other, card= args
            self.dealer_card= other.dealer_card
            self.cards= [other.cards[kw['split']], card]
        elif len(args) == 3:
            # Build a fresh, new hand.
            dealer_card, *cards = args
            self.dealer_card=  dealer_card
            self.cards= list(cards)
        else:
            raise TypeError( "Invalid constructor args={0!r} kw={1!r}".format(args, kw) )
    def __str__( self ):
        return ", ".join( map(str, self.cards) )

This design involves getting extra cards to build proper, split hands. When we create one Hand4 object from another Hand4 object, we provide a split keyword argument that uses the index of the Card class from the original Hand4 object.

The following code snippet shows how we'd use this to split a hand:

d = Deck()
h = Hand4( d.pop(), d.pop(), d.pop() )
s1 = Hand4( h, d.pop(), split=0 )
s2 = Hand4( h, d.pop(), split=1 )

We created an initial h instance of Hand4 and split it into two other Hand4 instances, s1 and s2, and dealt an additional Card class into each. The rules of blackjack only allow this when the initial hand has two cards of equal rank.

While this __init__() method is rather complex, it has the advantage that it can parallel the way in which fronzenset is created from an existing set. The disadvantage is that it needs a large docstring to explain all these variations.

Initializing static methods

When we have multiple ways to create an object, it's sometimes more clear to use static methods to create and return instances rather than complex __init__() methods.

It's also possible to use class methods as alternate initializers, but there's little tangible advantage to receiving the class as an argument to the method. In the case of freezing or splitting a Hand object, we might want to create two new static methods to freeze or split a Hand object. Using static methods as surrogate constructors is a tiny syntax change in construction, but it has huge advantages when organizing the code.

The following is a version of Hand with static methods that can be used to build new instances of Hand from an existing Hand instance:

class Hand5:
    def __init__( self, dealer_card, *cards ):
        self.dealer_card= dealer_card
        self.cards = list(cards)
    @staticmethod
    def freeze( other ):
        hand= Hand5( other.dealer_card, *other.cards )
        return hand
    @staticmethod
    def split( other, card0, card1 ):
        hand0= Hand5( other.dealer_card, other.cards[0], card0 )
        hand1= Hand5( other.dealer_card, other.cards[1], card1 )
        return hand0, hand1
    def __str__( self ):
        return ", ".join( map(str, self.cards) )

One method freezes or creates a memento version. The other method splits a Hand5 instance to create two new child instances of Hand5.

This is considerably more readable and preserves the use of the parameter names to explain the interface.

The following code snippet shows how we can split a Hand5 instance with this version of the class:

d = Deck()
h = Hand5( d.pop(), d.pop(), d.pop() )
s1, s2 = Hand5.split( h, d.pop(), d.pop() )

We created an initial h instance of Hand5, split it into two other hands, s1 and s2, and dealt an additional Card class into each. The split() static method is much simpler than the equivalent functionality implemented via __init__(). However, it doesn't follow the pattern of creating a fronzenset object from an existing set object.

You have been reading a chapter from
Mastering Object-oriented Python
Published in: Apr 2014
Publisher: Packt
ISBN-13: 9781783280971
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