A function in Python offers an optimized implementation to run the logic of any program several times with a hassle-free execution. You may have also heard about the decorators in Python, which also work in a similar concept of the Python functions. This article talks about the decorators in Python in detail.
To get understanding what decorators in Python are, let us first understand functions. You need to know the concept of the function in Python to proceed to know the decorators. The functions in Python are the first-class objects and the inner functions.
In Python, everything is an object which includes the functions as well as the data types. This makes functions a first-class object. The functions thus can be passed around in the form of arguments.
Python allows defining function in a function. This is known as the inner function. It does not matter how the child’s function gets declared. The output is dependent on the execution of the child function. These are scoped locally with the func() and cannot get called individually.
If you call it separately, you will be given an error because the variables are stored in the func(), which can be called when the func gets called.
It is also possible to return a function using some other function.
Decorators are very powerful in Python. The decorators in Python work to modify the behavior of the function without causing any permanent modification. The decorators wrap some other function, and since both the functions can be called, it returns a callable.
A decorator will wrap a function and modify the behavior.
Decorators can also be used with arguments.
When you place a Python function with an argument, then this makes it tricky for the decorator function since there is also a need for arguments in the declaration. The **kwargs and the *args are used in these cases inside the inner wrapper function.
Values can also be returned for the decorated function. It is also possible to return values from a decorated function. You must return the wrapper function with the argument, which will help to avoid any error.
Now that you are aware of how the decorator functions work in Python let us now understand the fancy decorators that find use in Python. These have complex features and are the decorator function in Python.
The class in Python can be decorated in two different ways. In the first method, you can decorate the method in a class. These are the built-in Python class decorator like the @staticmethod, @classmethod, and the @property in python. The @staticmethod and the @classmethod define the class methods that are not connected with any other class instance. @property finds use to customize the setters and the getters in a class attribute. It is also possible to declare the class by decorating the entire class.
Decorating a class is not about how it reflects on the methods. It is the same as writing a decorator of a Python function. The difference lies in the class of the argument instead of a difference in the function.
A singleton class has just a single instance. Python has many singletons like the None, True, etc. When you use ‘is’ in Python, it will return True for the objects that are of the same instance. The difference is that class is used instead of a function here.
It is also possible to use many decorators who can be done by stacking one on top of the other. This is how nested decorators are used. For this to work, you will need to first define function 1 and function 2 with the wrapper function present in each one of them.
It is always beneficial if you pass an argument in the decorator.
The decorators work to alter the functionality of a function dynamically. They can also change the functionality of a class or method without using any subclasses or by changing the source code of the functions that are getting decorated. When you use decorators in Python, you also ensure that the code is DRY or Don’t repeat yourself. There are many use cases of decorators, including logging, authorization in the framework of Python like in Django and Flask, synchronization, and the measuring of the execution time.
Python has an exciting feature called the decorator, which adds functionality to any existing code. This is also referred to as metaprogramming because a part of the program will try to make modifications in another part of the program at the time of compilation. This is the complete guide on how you should use decorators in Python.
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