Decorators are one of the most helpful and powerful tools of Python. These are used to modify the behavior of the function. Decorators provide the flexibility to wrap another function to expand the working of wrapped function, without permanently modifying it.
In Decorators, functions are passed as an argument into another function and then called inside the wrapper function.
It is also called meta programming where a part of the program attempts to change another part of program at compile time.
Before understanding the Decorator, we need to know some important concepts of Python.
What are the functions in Python?
Python has the most interesting feature that everything is treated as an object even classes or any variable we define in Python is also assumed as an object. Functions are first-class objects in the Python because they can reference to, passed to a variable and returned from other functions as well. The example is given below:
Hii, welcome to function Hii, welcome to function
In the above program, when we run the code it give the same output for both functions. The func2referred to function func1 and act as function. We need to understand the following concept of the function:
Python provides the facility to define the function inside another function. These types of functions are called inner functions. Consider the following example:
We are in first function This is first child function This is second child function
In the above program, it doesn't matter how the child functions are declared. The execution of the child function makes effect on the output. These child functions are locally bounded with the func() so they cannot be called separately.
A function that accepts other function as an argument is also called higher order function. Consider the following example:
In the above program, we have passed the sub() function and add() function as argument in operator() function.
A function can return another function. Consider the below example:
In the above program, the hi() function is nested inside the hello() function. It will return each time we call hi().
Decorating functions with parameters
Let's have an example to understand the parameterized decorator function:
In the above program, we have decorated out_div() that is little bit bulky. Instead of using above method, Python allows to use decorator in easy way with @symbol. Sometimes it is called "pie" syntax.
We can reuse the decorator as well by recalling that decorator function. Let's make the decorator to its own module that can be used in many other functions. Creating a file called mod_decorator.py with the following code:
We can import mod_decorator.py in other file.
Hello There Hello There
Python Decorator with Argument
We want to pass some arguments in function. Let's do it in following code:
TypeError: display() missing 1 required positional argument: 'name'
As we can see that, the function didn't accept the argument. Running this code raises an error. We can fix this error by using *args and **kwargsin the inner wrapper function. Modifying the decorator.pyas follows:
Now wrapper_function() can accept any number of argument and pass them on the function.
Hello John Hello John
Returning Values from Decorated Functions
We can control the return type of the decorated function. The example is given below:
We are created greeting We are created greeting
Let's understand the fancy decorators by the following topic:
Python provides two ways to decorate a class. Firstly, we can decorate the method inside a class; there are built-in decorators like @classmethod, @staticmethod and @property in Python. The @classmethod and @staticmethod define methods inside class that is not connected to any other instance of a class. The @property is generally used to modify the getters and setters of a class attributes. Let's understand it by the following example:
@property decorator - By using it, we can use the class function as an attribute. Consider the following code:
Name of the student: John Grade of the student: B John got grade B
@staticmethod decorator- The @staticmethod is used to define a static method in the class. It is called by using the class name as well as instance of the class. Consider the following code:
Hello Peter Hello Peter
A singleton class only has one instance. There are many singletons in Python including True, None, etc.
We can use multiple decorators by using them on top of each other. Let's consider the following example:
In the above code, we have used the nested decorator by stacking them onto one another.
Decorator with Arguments
It is always useful to pass arguments in a decorator. The decorator can be executed several times according to the given value of the argument. Let us consider the following example:
JavatPoint JavatPoint JavatPoint JavatPoint JavatPoint
In the above example, @repeatrefers to a function object that can be called in another function. The @repeat(num = 5)will return a function which acts as a decorator.
The above code may look complex but it is the most commonly used decorator pattern where we have used one additional def that handles the arguments to the decorator.
Note: Decorator with argument is not frequently used in programming, but it provides flexibility. We can use it with or without argument.
Stateful decorators are used to keep track of the decorator state. Let us consider the example where we are creating a decorator that counts how many times the function has been called.
Call 1 of 'say_hello' Say Hello Call 2 of 'say_hello' Say Hello
In the above program, the state represented the number of calls of the function stored in .num_callson the wrapper function. When we call say_hello()it will display the number of the call of the function.
Classes as Decorators
The classes are the best way to maintain state. In this section, we will learn how to use a class as a decorator. Here we will create a class that contains __init__() and take func as an argument. The class needs to be callable so that it can stand in for the decorated function.
To making a class callable, we implement the special __call__() method.
Call 1 of 'say_hello' Say Hello Call 2 of 'say_hello' Say Hello Call 3 of 'say_hello' Say Hello
The __init__() method stores a reference to the function and can do any other required initialization.
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