The container must inject a delegate object to the delegate injection point. The delegate object implements the delegate type and delegates method invocations to remaining uninvoked decorators and eventually to the bean. When the container calls a decorator during business method interception, the decorator may invoke any method of the delegate object.

Just take a look at the code again. In the if/else clause we are returning greet and welcome, not greet() and welcome(). Why is that? It’s because when you put a pair of parentheses after it, the function gets executed; whereas if you don’t put parenthesis after it, then it can be passed around and can be assigned to other variables without executing it. Did you get it? Let me explain it in a little bit more detail. When we write a = hi(), hi() gets executed and because the name is yasoob by default, the function greet is returned. If we change the statement to a = hi(name = "ali") then the welcome function will be returned. We can also do print hi()() which outputs now you are in the greet() function.
When we instantiate a SimpleMessage and then pass it to the various decorators, we now get new behavior. Moreover, since both the concrete component and the concrete decorators all implement / descend from IMessage, they are interchangeable as far as the program is concerned, meaning that we can loop over them together. Further, rather than having to create a new ExcitedAndQuizzicalMessageDecorator class, we were able to achieve the same effect by double wrapping a SimpleMessage object (first in an ExcitedMessageDecorator and then in a QuizzicalMessageDecorator). Finally, note that despite having been passed into various decorators, our simpleMsg object remains unchanged at the end of the program.
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.
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.
If working inside a person’s home, special attention will need to be paid to the different problems that can be encountered, such as those presented by pets and furniture. It is also essential to respect the private space of the client, and to work appropriately within it. If working for a construction firm, dangerous situations can be encountered, such as working at heights and employing the use of safety harnesses and ropes. Working outside brings with it its own hazards and difficulties, and the worker will need to plan for these accordingly through the types of clothing worn and the equipment used. The days can be long, and the hours can vary significantly. If self-employed, planning is essential to fit in as many jobs as is appropriate for the week, in order to avoid long spells of little work, or booking too many jobs into a short period of time. It is also possible that some jobs will require unsociable hours of work, such as working at the weekend. Although the profession is traditionally male dominated, more women are now being encouraged into the trade.

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.


This decorator works by storing the time just before the function starts running (at the line marked # 1) and just after the function finishes (at # 2). The time the function takes is then the difference between the two (at # 3). We use the time.perf_counter() function, which does a good job of measuring time intervals. Here are some examples of timings:
The decorate() proposal was that no new syntax be implemented -- instead a magic function that used introspection to manipulate the following function. Both Jp Calderone and Philip Eby produced implementations of functions that did this. Guido was pretty firmly against this -- with no new syntax, the magicness of a function like this is extremely high:
Historically, the painter was responsible for the mixing of the paint; keeping a ready supply of pigments, oils, thinners and driers. The painter would use his experience to determine a suitable mixture depending on the nature of the job. In modern times, the painter is primarily responsible for preparation of the surface to be painted, such as patching holes in drywall, using masking tape and other protection on surfaces not to be painted, applying the paint and then cleaning up.[2]

Thanks to enhanced support for multi-core processors and CPUs that use AVX2 extensions and extensive code optimizations, this is the fastest version of Painter yet. A huge selection of brushes are noticeably faster — some as much as twice as fast. You can also take advantage of faster document rendering when zooming, panning and rotating — up to 50% faster.
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