... 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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The primary objection to this form is that it requires "peeking inside" the method body to determine the decorators. In addition, even though the code is inside the method body, it is not executed when the method is run. Guido felt that docstrings were not a good counter-example, and that it was quite possible that a 'docstring' decorator could help move the docstring to outside the function body.
The decorate() proposal was that no new syntax be implemented -- instead a magic function that used introspection to manipulate the following function. Both Jp Calderone and Philip Eby produced implementations of functions that did this. Guido was pretty firmly against this -- with no new syntax, the magicness of a function like this is extremely high:
There is general agreement that syntactic support is desirable to the current state of affairs. Guido mentioned syntactic support for decorators  in his DevDay keynote presentation at the 10th Python Conference , though he later said  it was only one of several extensions he proposed there "semi-jokingly". Michael Hudson raised the topic  on python-dev shortly after the conference, attributing the initial bracketed syntax to an earlier proposal on comp.lang.python by Gareth McCaughan .
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 is some history in Java using @ initially as a marker in Javadoc comments  and later in Java 1.5 for annotations , which are similar to Python decorators. The fact that @ was previously unused as a token in Python also means it's clear there is no possibility of such code being parsed by an earlier version of Python, leading to possibly subtle semantic bugs. It also means that ambiguity of what is a decorator and what isn't is removed. That said, @ is still a fairly arbitrary choice. Some have suggested using | instead.
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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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This decorator works by storing the time just before the function starts running (at the line marked # 1) and just after the function finishes (at # 2). The time the function takes is then the difference between the two (at # 3). We use the time.perf_counter() function, which does a good job of measuring time intervals. Here are some examples of timings:
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In object-oriented programming, the decorator pattern is a design pattern that allows behavior to be added to an individual object, dynamically, without affecting the behavior of other objects from the same class. The decorator pattern is often useful for adhering to the Single Responsibility Principle, as it allows functionality to be divided between classes with unique areas of concern. The decorator pattern is structurally nearly identical to the chain of responsibility pattern, the difference being that in a chain of responsibility, exactly one of the classes handles the request, while for the decorator, all classes handle the request.
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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 @.
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 , where a discussion took place. Subsequent to this, he decided that we'd have the Java-style  @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  on Python-dev, including this piece  on some of the (many) rejected forms.
Watercolor is a painting method in which the paints are made of pigments suspended in a water-soluble vehicle. The traditional and most common support for watercolor paintings is paper; other supports include papyrus, bark papers, plastics, vellum or leather, fabric, wood and canvas. In East Asia, watercolor painting with inks is referred to as brush painting or scroll painting. In Chinese, Korean, and Japanese painting it has been the dominant medium, often in monochrome black or browns. India, Ethiopia and other countries also have long traditions. Finger-painting with watercolor paints originated in China. Watercolor pencils (water-soluble color pencils) may be used either wet or dry.