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.
The current method for transforming functions and methods (for instance, declaring them as a class or static method) is awkward and can lead to code that is difficult to understand. Ideally, these transformations should be made at the same point in the code where the declaration itself is made. This PEP introduces new syntax for transformations of a function or method declaration.
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:

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.

Historically, the painter was responsible for the mixing of the paint; keeping a ready supply of pigments, oils, thinners and driers. The painter would use his experience to determine a suitable mixture depending on the nature of the job. In modern times, the painter is primarily responsible for preparation of the surface to be painted, such as patching holes in drywall, using masking tape and other protection on surfaces not to be painted, applying the paint and then cleaning up.[2]
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.
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.
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.
Decorator Abstractions: A decorator abstraction is an abstract class that implements the component interface. Critically, the decorator abstraction must also contain a pointer to some instance of the same interface. Inside the decorator abstraction, each of the component interface behaviors will be delegated to whichever concrete component the pointer indicates.
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.
Tempera, also known as egg tempera, is a permanent, fast-drying painting medium consisting of colored pigment mixed with a water-soluble binder medium (usually a glutinous material such as egg yolk or some other size). Tempera also refers to the paintings done in this medium. Tempera paintings are very long lasting, and examples from the first centuries CE still exist. Egg tempera was a primary method of painting until after 1500 when it was superseded by the invention of oil painting. A paint commonly called tempera (though it is not) consisting of pigment and glue size is commonly used and referred to by some manufacturers in America as poster paint.
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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 @.
Pastel is a painting medium in the form of a stick, consisting of pure powdered pigment and a binder.[19] The pigments used in pastels are the same as those used to produce all colored art media, including oil paints; the binder is of a neutral hue and low saturation. The color effect of pastels is closer to the natural dry pigments than that of any other process.[20] Because the surface of a pastel painting is fragile and easily smudged, its preservation requires protective measures such as framing under glass; it may also be sprayed with a fixative. Nonetheless, when made with permanent pigments and properly cared for, a pastel painting may endure unchanged for centuries. Pastels are not susceptible, as are paintings made with a fluid medium, to the cracking and discoloration that result from changes in the color, opacity, or dimensions of the medium as it dries.
Color, made up of hue, saturation, and value, dispersed over a surface is the essence of painting, just as pitch and rhythm are the essence of music. Color is highly subjective, but has observable psychological effects, although these can differ from one culture to the next. Black is associated with mourning in the West, but in the East, white is. Some painters, theoreticians, writers and scientists, including Goethe,[3] Kandinsky,[4] and Newton,[5] have written their own color theory.