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.
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In Python 2.4a3 (to be released this Thursday), everything remains as currently in CVS. For 2.4b1, I will consider a change of @ to some other single character, even though I think that @ has the advantage of being the same character used by a similar feature in Java. It's been argued that it's not quite the same, since @ in Java is used for attributes that don't change semantics. But Python's dynamic nature makes that its syntactic elements never mean quite the same thing as similar constructs in other languages, and there is definitely significant overlap. Regarding the impact on 3rd party tools: IPython's author doesn't think there's going to be much impact; Leo's author has said that Leo will survive (although it will cause him and his users some transitional pain). I actually expect that picking a character that's already used elsewhere in Python's syntax might be harder for external tools to adapt to, since parsing will have to be more subtle in that case. But I'm frankly undecided, so there's some wiggle room here. I don't want to consider further syntactic alternatives at this point: the buck has to stop at some point, everyone has had their say, and the show must go on.
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The first example of modernism in painting was impressionism, a school of painting that initially focused on work done, not in studios, but outdoors (en plein air). Impressionist paintings demonstrated that human beings do not see objects, but instead see light itself. The school gathered adherents despite internal divisions among its leading practitioners, and became increasingly influential. Initially rejected from the most important commercial show of the time, the government-sponsored Paris Salon, the Impressionists organized yearly group exhibitions in commercial venues during the 1870s and 1880s, timing them to coincide with the official Salon. A significant event of 1863 was the Salon des Refusés, created by Emperor Napoleon III to display all of the paintings rejected by the Paris Salon.
Note that greet_bob(say_hello) refers to two functions, but in different ways: greet_bob() and say_hello. The say_hello function is named without parentheses. This means that only a reference to the function is passed. The function is not executed. The greet_bob() function, on the other hand, is written with parentheses, so it will be called as usual.
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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In general, functions in Python may also have side effects rather than just turning an input into an output. The print() function is a basic example of this: it returns None while having the side effect of outputting something to the console. However, to understand decorators, it is enough to think about functions as something that turns given arguments into a value.
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The discussion continued on and off on python-dev from February 2002 through July 2004. Hundreds and hundreds of posts were made, with people proposing many possible syntax variations. Guido took a list of proposals to EuroPython 2004 [7], where a discussion took place. Subsequent to this, he decided that we'd have the Java-style [10] @decorator syntax, and this appeared for the first time in 2.4a2. Barry Warsaw named this the 'pie-decorator' syntax, in honor of the Pie-thon Parrot shootout which occurred around the same time as the decorator syntax, and because the @ looks a little like a pie. Guido outlined his case [8] on Python-dev, including this piece [9] on some of the (many) rejected forms.
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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.
... the keyword starting the line that heads a block draws a lot of attention to it. This is true for "if", "while", "for", "try", "def" and "class". But the "using" keyword (or any other keyword in its place) doesn't deserve that attention; the emphasis should be on the decorator or decorators inside the suite, since those are the important modifiers to the function definition that follows. ...

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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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Did you get it? We just applied the previously learned principles. This is exactly what the decorators do in Python! They wrap a function and modify its behaviour in one way or the another. Now you might be wondering that we did not use the @ anywhere in our code? That is just a short way of making up a decorated function. Here is how we could have run the previous code sample using @.
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The decorator pattern is a design pattern that allows you to wrap an object such that it will appear to execute a given behavior in many different ways at different points in program execution. This is especially useful when you want an object to have different behaviors at but are unable to mutate the object. The decorator pattern is a useful way to implement dynamic behavior without needing an extended inheritance-based class hierarchy. To use the decorator pattern you need four elements: a component interface; a concrete component; a decorator abstraction; and, a concrete decorator. The interface sets the contract for both component and decorator behavior, the decorator abstraction contains a pointer to some concrete component, and the concrete decorators wrap a concrete component and override behavior if desired.
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.
Decorator Abstractions: Our decorator abstraction takes the form of the abstract MessageDecorator class, which also implements IMessage. The MessageDecorator class has a constructor that accepts an IMessage object as a parameter and then assigns it to a private variable. For its part, MessageDecorator doesn’t have any special behaviors and simply delegates GetMessage and PrintMessage calls to whichever IMessage object was injected into it.
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