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CHAPTER 7 MORE ABSTRACTION
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Assuming that the network stuff already exists, you ve solved the problem for now. But this still isn t very flexible. What if some clever programmer decides that she ll represent the price as a string with a hex value, stored in a dictionary under the key 'price' No problem you just update your function: # Don't do it like this... def getPrice(object): if isinstance(object, tuple): return object[1] elif isinstance(object, dict): return int(object['price']) else: return magic_network_method(object) Now, surely you must have covered every possibility But let s say someone decides to add a new type of dictionary with the price stored under a different key. What do you do now You could certainly update getPrice again, but for how long could you continue doing that Every time someone wanted to implement some priced object differently, you would need to reimplement your module. But what if you already sold your module and moved on to other, cooler projects what would the client do then Clearly, this is an inflexible and impractical way of coding the different behaviors. So what do you do instead You let the objects handle the operation themselves. It sounds really obvious, but think about how much easier things will get. Every new object type can retrieve or calculate its own price and return it to you all you have to do is ask for it. And this is where polymorphism (and, to some extent, encapsulation) enters the scene.
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Polymorphism and Methods
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You receive an object and have no idea of how it is implemented it may have any one of many shapes. All you know is that you can ask for its price, and that s enough for you. The way you do that should be familiar: >>> object.getPrice() 2.5 Functions that are bound to object attributes like this are called methods. You ve already encountered them in the form of string, list, and dictionary methods. There, too, you saw some polymorphism: >>> 'abc'.count('a') 1 >>> [1, 2, 'a'].count('a') 1 If you had a variable x, you wouldn t need to know whether it was a string or a list to call the count method it would work regardless (as long as you supplied a single character as the argument).
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CHAPTER 7 MORE ABSTRACTION
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Let s do an experiment. The standard library random contains a function called choice that selects a random element from a sequence. Let s use that to give your variable a value: >>> from random import choice >>> x = choice(['Hello, world!', [1, 2, 'e', 'e', 4]]) After performing this, x can either contain the string 'Hello, world!' or the list [1, 2, 'e', 'e', 4] you don t know, and you don t have to worry about it. All you care about is how many times you find 'e' in x, and you can find that out regardless of whether x is a list or a string. By calling the count method as before, you find out just that: >>> x.count('e') 2 In this case, it seems that the list won out. But the point is that you didn t need to check. Your only requirement was that x has a method called count that takes a single character as an argument and returned an integer. If someone else had made his own class of objects that had this method, it wouldn t matter to you you could use his objects just as well as the strings and lists.
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Polymorphism Comes in Many Forms
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Polymorphism is at work every time you can do something to an object without having to know exactly what kind of object it is. This doesn t apply only to methods we ve already used polymorphism a lot in the form of built-in operators and functions. Consider the following: >>> 1+2 3 >>> 'Fish'+'license' 'Fishlicense' Here, the plus operator (+) works fine for both numbers (integers in this case) and strings (as well as other types of sequences). To illustrate the point, let s say you wanted to make a function called add that added two things together. You could simply define it like this (equivalent to, but less efficient than, the add function from the operator module): def add(x, y): return x+y This would also work with many kinds of arguments: >>> add(1, 2) 3 >>> add('Fish', 'license') 'Fishlicense'
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