More recently, professional painters are responsible for all preparation prior to painting. All scraping, sanding, wallpaper removal, caulking, drywall or wood repair, patching, stain removal, filling nail holes or any defects with plaster or putty, cleaning, taping, preparation and priming are considered to be done by the professional contracted painter.
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 @.
This code works for our purposes but it’s not exactly dynamic. If we wanted our initial simpleMsg object to sometimes act excited and sometimes quizzical, we could only do so by instantiating entirely new objects from the relevant subclass. Moreover, the ExcitedAndQuizzicalMessage is really just a combination of ExcitedMessage and QuizzicalMessage and probably shouldn’t have its own class. To fix these problems, let’s now return to the decorator pattern and see how it might help us.

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As with many construction jobs, those who successfully complete apprenticeships best-position themselves for successful painting careers. For painters, apprenticeships can last up to four years. Apprentices must have a high school diploma or its equivalent before they are eligible to complete the requisite 144 hours of technical instruction and 2,000 hours of paid, on-the-job training. Common lessons include aesthetics, such as how to adequately match colors, as well as using and caring for painting tools and equipment, safety practices, application techniques and wood finishing. Prospective painters may also choose to attend two-year technical schools that offer courses linked to union and contractor organization apprenticeships. Credits gained from apprenticeships typically count toward an associate degree.
This difference becomes most important when there are several independent ways of extending functionality. In some object-oriented programming languages, classes cannot be created at runtime, and it is typically not possible to predict, at design time, what combinations of extensions will be needed. This would mean that a new class would have to be made for every possible combination. By contrast, decorators are objects, created at runtime, and can be combined on a per-use basis. The I/O Streams implementations of both Java and the .NET Framework incorporate the decorator pattern.
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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.
None of these alternatives gained much traction. The alternatives which involve square brackets only serve to make it obvious that the decorator construct is not a list. They do nothing to make parsing any easier. The '<...>' alternative presents parsing problems because '<' and '>' already parse as un-paired. They present a further parsing ambiguity because a right angle bracket might be a greater than symbol instead of a closer for the decorators.
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.
Painters deal practically with pigments,[6] so "blue" for a painter can be any of the blues: phthalocyanine blue, Prussian blue, indigo, Cobalt blue, ultramarine, and so on. Psychological and symbolical meanings of color are not, strictly speaking, means of painting. Colors only add to the potential, derived context of meanings, and because of this, the perception of a painting is highly subjective. The analogy with music is quite clear—sound in music (like a C note) is analogous to "light" in painting, "shades" to dynamics, and "coloration" is to painting as the specific timbre of musical instruments is to music. These elements do not necessarily form a melody (in music) of themselves; rather, they can add different contexts to it.
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