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 @.
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The decorator pattern, also known as the wrapper pattern, is when you wrap an object within another object, thus providing a means of enhancing or overriding certain behavior. The wrapper object will delegate any incoming method calls to the original object, unless it defines a new method to enhance or replace the original object’s behavior. By using the decorator pattern, you can dynamically create as many decorated objects as you want, each enhancing the behavior of the original object in a unique way — and all without mutating the original object. In this manner, you can effectively add, remove, or extend behaviors at runtime.
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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.
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