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Timing Functions With Decorators – Python

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Everything in Python is an object. Functions in Python also object. Hence, like any other object they can be referenced by variables, stored in data structures like dictionary or list, passed as an argument to another function, and returned as a value from another function. In this article, we are going to see the timing function with decorators.

Decorator: A decorator is used to supercharge or modify a function. A decorator is a higher-order function that wraps another function and enhances it or changes it. 

Example :

The best way to explain what it is by coding our own decorator. Suppose, you want to print * 10 times before and after the output of some function. It would be very inconvenient to use print statements in every function again and again. We can do this efficiently with the help of a decorator.



def my_decorator(func):
    def wrapper_function(*args, **kwargs):
        func(*args,  **kwargs)
    return wrapper_function
def say_hello():
    print("Hello Geeks!")
def say_bye():
    print("Bye Geeks!")
say_hello = my_decorator(say_hello)



Hello Geeks!
Bye Geeks!

Explanation :

In the above example, my_decorator is a decorator function, which accepts func, a function object as an argument. It defines a wrapper_function which calls func and executes the code that it contains as well. The my_decorator function returns this wrapper_function.

So, what happens when we write @my_decorator before defining any function? Consider the example of the say_hello function above which is not decorated by any decorator at the time of definition. We can still use our decorator for decorating its output by calling the my_decorator function and passing the say_hello function object as a parameter, which will return a wrapper_function with two print statements, calling the say_hello() function in between. If we receive this modified function in the say_hello object itself, whenever we call say_hello() we’ll get the modified output.

Instead of writing this complex syntax, we can simply write @my_decorator before defining the function and leave the rest of the work for python interpreter as shown in the case of say_bye function.

Timer Function using Decorator

The timer function is one of the applications of decorators. In the below example, we have made a timer_func function that accepts a function object func. Inside the timer function, we have defined wrap_func which can take any number of arguments (*args) and any number of keyword arguments (**kwargs) passed to it. We did this to make our timer_func more flexible. 

In the body of wrap_func, we recorded the current time t1 using the time method of the time module, then we have called the function func passing the same parameters (*args, **kwargs) that were received by wrap_func and stored the returned value in the result. Now we have again recorded the current time t2 and printed the difference between the recorded times i.e. { t2 – t1 } with precision up to the 4th decimal place. This {t2 – t1} is the time passed during the execution of the function func. At last, we have returned the result value inside wrap_func function and returned this wrap_func function inside timer_func function.

We have also defined the long_time function using @timer_func decorator, so whenever we call long_time function it will be called like :


The timer_func function when called passing long_time as a parameter returns a wrap_func function and a function object func starts pointing to the long_time function.


Now the wrap_func will execute as explained above and the result is returned.


from time import time
def timer_func(func):
    # This function shows the execution time of 
    # the function object passed
    def wrap_func(*args, **kwargs):
        t1 = time()
        result = func(*args, **kwargs)
        t2 = time()
        print(f'Function {func.__name__!r} executed in {(t2-t1):.4f}s')
        return result
    return wrap_func
def long_time(n):
    for i in range(n):
        for j in range(100000):



Function 'long_time' executed in 0.0219s

Last Updated : 05 Apr, 2021
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