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Design Approaches

When we consider class design, we have often have a built-in or library class which does some of the job we want. For example, we want to be able to accumulate a list of values and then determine the average: this is a very list-like behavior, extended with a new feature.

There are two overall approaches for extending a class: wrapping and inheritance .

  • Wrap an existing class (for example, a tuple, list, set or map) in a new class which adds features. This allows you to redefine the interface to the existing class, which often involves removing features.

  • Inherit from an existing class, adding features as part of the more specialized subclass. This may require you to read more of the original class documentation to see a little of how it works internally.

Both techniques work extremely well; there isn't a profound reason for making a particular choice. When wrapping a collection, you can provide a new, focused interface on the original collection; this allows you to narrow the choices for the user of the class. When subclassing, however, you often have a lot of capabilities in the original class you are extending.

"Duck" Typing. In the section called “Polymorphism”, we mentioned "Duck" Typing. In Python, two classes are practically polymorphic if they have the same inteface methods. They do not have to be subclasses of the same class or interface (which is the rule in Java.)

This principle means that the distinction between wrapping and inheritance is more subtle in Python than in other languages. If you provide all of the appropriate interface methods to a class, it behaves as if it was a proper subclass. It may be a class that is wrapped by another class that provides the same interface.

For example, say we have a class Dice, which models a set of individual Die objects.

class Dice( object ):
    def __init__( self ):
        self.theDice= [ Die(), Die() ]
    def roll( self ):
        for d in self.theDice:
        return self.theDice

In essence, our class is a wrapper around a list of dice, named theDice. However, we don't provide any of the interface methods that are parts of the built-in list class.

Even though this class is a wrapper around a list object, we can add method names based on the built-in list class: append, extend, count, insert, etc. We'll look closely at this in Chapter 24, Creating or Extending Data Types .

class Dice( object ):
    def __init__( self ):
        self.theDice= [ Die(), Die() ]
    def roll( self ):
        for d in self.theDice:
        return self.theDice
    def append( self, aDie ):
        self.theDice.append( aDie )
    def __len__( self ):
        return len( self.theDice )

Once we've defined these list-like functions we have an ambiguous situation.

  • We could have a subclass of list, which initializes itself to two Die objects and has a roll method.

  • We could have a distinct Dice class, which provides a roll method and a number of other methods that make it look like a list.

For people who will read your Python, clarity is the most important feature of the program. In making design decisions, one of your first questions has to be "what is the real thing that I'm modeling?" Since many alternatives will work, your design should reflect something that clarifies the problem you're solving.

  Published under the terms of the Open Publication License Design by Interspire