There is general agreement that syntactic support is desirable to the current state of affairs. Guido mentioned syntactic support for decorators [2] in his DevDay keynote presentation at the 10th Python Conference [3], though he later said [5] it was only one of several extensions he proposed there "semi-jokingly". Michael Hudson raised the topic [4] on python-dev shortly after the conference, attributing the initial bracketed syntax to an earlier proposal on comp.lang.python by Gareth McCaughan [6].
To calculate the tenth Fibonacci number, you should really only need to calculate the preceding Fibonacci numbers, but this implementation somehow needs a whopping 177 calculations. It gets worse quickly: 21891 calculations are needed for fibonacci(20) and almost 2.7 million calculations for the 30th number. This is because the code keeps recalculating Fibonacci numbers that are already known.
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.
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.
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.
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Component Interface: The component interface is an abstraction describing the behaviors of the components that you will eventually use in your program. Any objects that will use these components will do so through the interface, meaning that they are principally concerned with the abstraction (not the actual object). This is what allows both objects and wrapped objects to be considered to be the same type.
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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.
With the introduction of Classes in TypeScript and ES6, there now exist certain scenarios that require additional features to support annotating or modifying classes and class members. Decorators provide a way to add both annotations and a meta-programming syntax for class declarations and members. Decorators are a stage 2 proposal for JavaScript and are available as an experimental feature of TypeScript.
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.
Overall unfamiliarity with the concept. For people who have a passing acquaintance with algebra (or even basic arithmetic) or have used at least one other programming language, much of Python is intuitive. Very few people will have had any experience with the decorator concept before encountering it in Python. There's just no strong preexisting meme that captures the concept.
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Water miscible oil paints (also called "water soluble" or "water-mixable") is a modern variety of oil paint engineered to be thinned and cleaned up with water, rather than having to use chemicals such as turpentine. It can be mixed and applied using the same techniques as traditional oil-based paint, but while still wet it can be effectively removed from brushes, palettes, and rags with ordinary soap and water. Its water solubility comes from the use of an oil medium in which one end of the molecule has been altered to bind loosely to water molecules, as in a solution.
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