The .__init__() method must store a reference to the function and can do any other necessary initialization. The .__call__() method will be called instead of the decorated function. It does essentially the same thing as the wrapper() function in our earlier examples. Note that you need to use the functools.update_wrapper() function instead of @functools.wraps.

There have been a number of objections raised to this location -- the primary one is that it's the first real Python case where a line of code has an effect on a following line. The syntax available in 2.4a3 requires one decorator per line (in a2, multiple decorators could be specified on the same line), and the final decision for 2.4 final stayed one decorator per line.
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 @.
Just take a look at the code again. In the if/else clause we are returning greet and welcome, not greet() and welcome(). Why is that? It’s because when you put a pair of parentheses after it, the function gets executed; whereas if you don’t put parenthesis after it, then it can be passed around and can be assigned to other variables without executing it. Did you get it? Let me explain it in a little bit more detail. When we write a = hi(), hi() gets executed and because the name is yasoob by default, the function greet is returned. If we change the statement to a = hi(name = "ali") then the welcome function will be returned. We can also do print hi()() which outputs now you are in the greet() function.

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.


In this snippet we have a class hierarchy with a SimpleMessage at the top. The SimpleMessage class has a constructor that accepts a content string as well as two methods: GetMessage; and, PrintMessage. Down the hierarchy we have three subclasses: ExcitedMessage; QuizzicalMessage; and, ExcitedAndQuizzicalMessage. The only difference in the subclasses is that they override the SimpleMessage constructor to change the content string and append various exclamations. When we instantiate various message objects, using the same content string, and iterate over them, each has their own unique output.
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.
The decorator pattern can be used to extend (decorate) the functionality of a certain object statically, or in some cases at run-time, independently of other instances of the same class, provided some groundwork is done at design time. This is achieved by designing a new Decorator class that wraps the original class. This wrapping could be achieved by the following sequence of steps:
Modern artists have extended the practice of painting considerably to include, as one example, collage, which began with Cubism and is not painting in the strict sense. Some modern painters incorporate different materials such as sand, cement, straw or wood for their texture. Examples of this are the works of Jean Dubuffet and Anselm Kiefer. There is a growing community of artists who use computers to "paint" color onto a digital "canvas" using programs such as Adobe Photoshop, Corel Painter, and many others. These images can be printed onto traditional canvas if required.
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