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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 delegate injection point must be an injected field, initializer method parameter or bean constructor method parameter. If an injection point that is not an injected field, initializer method parameter or bean constructor method parameter is annotated @Delegate, the container automatically detects the problem and treats it as a definition error.
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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.

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.
In a previous article, we discussed how to use the strategy pattern to dynamically change an object’s behavior at runtime. Classically, polymorphism in object-oriented design is static and achieved through inheritance; however, with the strategy pattern you can accomplish the same goal dynamically. Indeed, this is an excellent way to handle situations when you need an object to exhibit different behavior at different times. However, it’s worth noting that the strategy pattern requires mutation of the object you’re working with. By using the strategy pattern, you are necessarily changing the algorithm that an object uses for a given behavior. In some situations, it may be preferable not to mutate a given object. Or more likely, you won’t even have the option of mutating an object because it may come from a codebase over which you have no control (such as an external library). Such cases are relatively common; however, it’s still possible to enhance an immutable object’s behavior. One effective means to do so is with the decorator pattern.
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.
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