Concrete Decorator: Here we have two concrete decorators, ExcitedMessageDecorator and QuizzicalMessageDecorator, each of which descends from the abstract MessageDecorator class. However, these decorators do have special behavior in that they override the GetMessage and PrintMessage behaviors and enhance them by calling the base version from MessageDecorator (which in turn delegates to the relevant IMessage object) and then appending exclamations.
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Some commonly used decorators that are even built-ins in Python are @classmethod, @staticmethod, and @property. The @classmethod and @staticmethod decorators are used to define methods inside a class namespace that are not connected to a particular instance of that class. The @property decorator is used to customize getters and setters for class attributes. Expand the box below for an example using these decorators.
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Modifying classes in this fashion is also possible, though the benefits are not as immediately apparent. Almost certainly, anything which could be done with class decorators could be done using metaclasses, but using metaclasses is sufficiently obscure that there is some attraction to having an easier way to make simple modifications to classes. For Python 2.4, only function/method decorators are being added.
When we instantiate a SimpleMessage and then pass it to the various decorators, we now get new behavior. Moreover, since both the concrete component and the concrete decorators all implement / descend from IMessage, they are interchangeable as far as the program is concerned, meaning that we can loop over them together. Further, rather than having to create a new ExcitedAndQuizzicalMessageDecorator class, we were able to achieve the same effect by double wrapping a SimpleMessage object (first in an ExcitedMessageDecorator and then in a QuizzicalMessageDecorator). Finally, note that despite having been passed into various decorators, our simpleMsg object remains unchanged at the end of the program.
You saw that, to define a decorator, you typically define a function returning a wrapper function. The wrapper function uses *args and **kwargs to pass on arguments to the decorated function. If you want your decorator to also take arguments, you need to nest the wrapper function inside another function. In this case, you usually end up with three return statements.
Overall unfamiliarity with the concept. For people who have a passing acquaintance with algebra (or even basic arithmetic) or have used at least one other programming language, much of Python is intuitive. Very few people will have had any experience with the decorator concept before encountering it in Python. There's just no strong preexisting meme that captures the concept.
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To calculate the tenth Fibonacci number, you should really only need to calculate the preceding Fibonacci numbers, but this implementation somehow needs a whopping 177 calculations. It gets worse quickly: 21891 calculations are needed for fibonacci(20) and almost 2.7 million calculations for the 30th number. This is because the code keeps recalculating Fibonacci numbers that are already known.
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This wrapper_repeat() function takes arbitrary arguments and returns the value of the decorated function, func(). This wrapper function also contains the loop that calls the decorated function num_times times. This is no different from the earlier wrapper functions you have seen, except that it is using the num_times parameter that must be supplied from the outside.
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