Digital painting is a method of creating an art object (painting) digitally and/or a technique for making digital art in the computer. As a method of creating an art object, it adapts traditional painting medium such as acrylic paint, oils, ink, watercolor, etc. and applies the pigment to traditional carriers, such as woven canvas cloth, paper, polyester etc. by means of computer software driving industrial robotic or office machinery (printers). As a technique, it refers to a computer graphics software program that uses a virtual canvas and virtual painting box of brushes, colors and other supplies. The virtual box contains many instruments that do not exist outside the computer, and which give a digital artwork a different look and feel from an artwork that is made the traditional way. Furthermore, digital painting is not 'computer-generated' art as the computer does not automatically create images on the screen using some mathematical calculations. On the other hand, the artist uses his own painting technique to create the particular piece of work on the computer.
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.
Oil painting is the process of painting with pigments that are bound with a medium of drying oil, such as linseed oil, which was widely used in early modern Europe. Often the oil was boiled with a resin such as pine resin or even frankincense; these were called 'varnishes' and were prized for their body and gloss. Oil paint eventually became the principal medium used for creating artworks as its advantages became widely known. The transition began with Early Netherlandish painting in northern Europe, and by the height of the Renaissance oil painting techniques had almost completely replaced tempera paints in the majority of Europe.
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.
Now we have our logit decorator in production, but when some parts of our application are considered critical, failure might be something that needs more immediate attention. Let’s say sometimes you want to just log to a file. Other times you want an email sent, so the problem is brought to your attention, and still keep a log for your own records. This is a case for using inheritence, but so far we’ve only seen functions being used to build decorators.
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.
Two decorators (classmethod() and staticmethod()) have been available in Python since version 2.2. It's been assumed since approximately that time that some syntactic support for them would eventually be added to the language. Given this assumption, one might wonder why it's been so difficult to arrive at a consensus. Discussions have raged off-and-on at times in both comp.lang.python and the python-dev mailing list about how best to implement function decorators. There is no one clear reason why this should be so, but a few problems seem to be most divisive.
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