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.
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:
def func1(msg):
print(msg)
func1("Hii")
func2 = func1
func2("Hii")In the above program, when we run the code it give the same output for both functions. The func2 referred 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:
def func():
print("We are in first function")
def func1():
print("This is first child function")
def func2():
print(" This is second child function")
func1()
func2()
func()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:
def add(x):
return x+1
def sub(x):
return x-1
def operator(func, x):
temp = func(x)
return temp
print(operator(sub,10))
print(operator(add,20))In the above program, we have passed the dec() function and inc() function as argument in operator() function.
A function can return another function. Consider the below example:
def hello():
def hi():
print("Hello")
return hi
new = hello()
new()In the above program, the hi() function is nested inside the hello() function. It will return each time we call hi().
Let's have an example to understand the parameterized decorator function.
def divide(x,y):
print(x/y)
def outer_div(func):
def inner(x,y):
if(xIn 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.
def outer_div(func):
def inner(x,y):
if(xWe 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:
def do_twice(func):
def wrapper_do_twice():
func()
func()
return wrapper_do_twiceWe can import mod_decorator.py in other file.
from decorator import do_twice
@do_twice
def say_hello():
print("Hello There")
say_hello()We want to pass some arguments in function. Let's do it in following code:
from decorator import do_twice
@do_twice
def display(name):
print(f"Hello {name}")
display()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 **kwargs in the inner wrapper function. Modifying the decorator.py as follows:
def do_twice(func):
def wrapper_function(*args,**kwargs):
func(*args,**kwargs)
func(*args,**kwargs)
return wrapper_functionNow wrapper_function() can accept any number of argument and pass them on the function.
from decorator import do_twice
@do_twice
def display(name):
print(f"Hello {name}")
display("John")We can control the return type of the decorated function. The example is given below:
from decorator import do_twice
@do_twice
def return_greeting(name):
print("We are created greeting")
return f"Hi {name}"
hi_adam = return_greeting("Adam")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:
Example: 1- @property decorator - By using it, we can use the class function as an attribute. Consider the following code:
class Student:
def __init__(self,name,grade):
self.name = name
self.grade = grade
@property
def display(self):
return self.name + " got grade " + self.grade
stu = Student("John","B")
print("Name:", stu.name)
print("Grade:", stu.grade)
print(stu.display)Example:2 - @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:
class Person:
@staticmethod
def hello():
print("Hello Peter")
per = Person()
per.hello()
Person.hello()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:
@function1
@function2
def function(name):
print(f "{name}")In the above code, we have used the nested decorator by stacking them onto one another.
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:
Import functools
def repeat(num):
#Creating and returning a wrapper function
def decorator_repeat(func):
@functools.wraps(func)
def wrapper(*args,**kwargs):
for _ in range(num):
value = func(*args,**kwargs)
return value
return wrapper
return decorator_repeat
#Here we are passing num as an argument which repeats the print function
@repeat(num=5)
def function1(name):
print(f"{name}")In the above example, @repeat refers 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.
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.
Import functools
def count_function(func):
@functools.wraps(func)
def wrapper_count_calls(*args, **kwargs):
wrapper_count_calls.num_calls += 1
print(f"Call{wrapper_count_calls.num_calls} of {func.__name__!r}")
return func(*args, **kwargs)
wrapper_count_calls.num_calls = 0
return wrapper_count_calls
@count_function
def say_hello():
print("Say Hello")
say_hello()
say_hello()In the above program, the state represented the number of calls of the function stored in .num_calls on the wrapper function. When we call say_hello() it will display the number of the call of the function.
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.
import functools
class Count_Calls:
def __init__(self, func):
functools.update_wrapper(self, func)
self.func = func
self.num_calls = 0
def __call__(self, *args, **kwargs):
self.num_calls += 1
print(f"Call{self.num_calls} of {self.func.__name__!r}")
return self.func(*args, **kwargs)
@Count_Calls
def say_hello():
print("Say Hello")
say_hello()
say_hello()
say_hello()The __init__() method stores a reference to the function and can do any other required initialization.
