Python - Higher Order Functions

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Higher-order functions in Python allows you to manipulate functions for increasing the flexibility and re-usability of your code. You can create higher-order functions using nested scopes or callable objects.

Additionally, the functools module provides utilities for working with higher-order functions, making it easier to create decorators and other function-manipulating constructs. This tutorial will explore the concept of higher-order functions in Python and demonstrate how to create them.

What is a Higher-Order Function?

A higher-order function is a function that either, takes one or more functions as arguments or returns a function as its result. Below you can observe the some of the properties of the higher-order function in Python −

• A function can be stored in a variable.
• A function can be passed as a parameter to another function.
• A high order functions can be stored in the form of lists, hash tables, etc.
• Function can be returned from a function.

To create higher-order function in Python you can use nested scopes or callable objects. Below we will discuss about them briefly.

Creating Higher Order Function with Nested Scopes

One way to defining a higher-order function in Python is by using nested scopes. This involves defining a function within another function and returns the inner function.

Example

Let's observe following example for creating a higher order function in Python. In this example, the multiplier function takes one argument, a, and returns another function multiply, which calculates the value a * b

def multiplier(a):  
   # Nested function with second number   
   def multiply(b):
      # Multiplication of two numbers  
      return a * b 
   return multiply   

# Assigning nested multiply function to a variable  
multiply_second_number = multiplier(5)  
# Using variable as high order function  
Result = multiply_second_number(10)  
# Printing result  
print("Multiplication of Two numbers is: ", Result) 

Output

On executing the above program, you will get the following results −

Multiplication of Two numbers is:  50

Creating Higher-Order Functions with Callable Objects

Another approach to create higher-order functions is by using callable objects. This involves defining a class with a __call__ method.

Example

Here is the another approach to creating higher-order functions is using callable objects.

class Multiplier:
   def __init__(self, factor):
      self.factor = factor

   def __call__(self, x):
      return self.factor * x
 
# Create an instance of the Multiplier class
multiply_second_number = Multiplier(2) 

# Call the  Multiplier object to computes factor * x
Result = multiply_second_number(100)  

# Printing result  
print("Multiplication of Two numbers is: ", Result) 

Output

On executing the above program, you will get the following results −

Multiplication of Two numbers is:  200

Higher-order functions with the 'functools' Module

The functools module provides higher-order functions that act on or return other functions. Any callable object can be treated as a function for the purposes of this module.

Working with Higher-order functions using the wraps()

In this example, my_decorator is a higher-order function that modifies the behavior of invite function using the functools.wraps() function.

import functools

def my_decorator(f):
   @functools.wraps(f)
   def wrapper(*args, **kwargs):
      print("Calling", f.__name__)
      return f(*args, **kwargs)
   return wrapper

@my_decorator
def invite(name):
   print(f"Welcome to, {name}!")

invite("Tutorialspoint")

Output

On executing the above program, you will get the following results −

Calling invite
Welcome to, Tutorialspoint!

Working with Higher-order functions using the partial()

The partial() function of the functools module is used to create a callable 'partial' object. This object itself behaves like a function. The partial() function receives another function as argument and freezes some portion of a functions arguments resulting in a new object with a simplified signature.

Example

In following example, a user defined function myfunction() is used as argument to a partial function by setting default value on one of the arguments of original function.

import functools
def myfunction(a,b):
   return a*b

partfunction = functools.partial(myfunction,b = 10)
print(partfunction(10))

Output

On executing the above program, you will get the following results −

100

Working with Higher-order functions using the reduce()

Similar to the above approach the functools module provides the reduce() function, that receives two arguments, a function and an iterable. And, it returns a single value. The argument function is applied cumulatively two arguments in the list from left to right. Result of the function in first call becomes first argument and third item in list becomes second. This is repeated till list is exhausted.

Example

import functools
def mult(x,y):
   return x*y

# Define a number to calculate factorial
n = 4
num = functools.reduce(mult, range(1, n+1))
print (f'Factorial of {n}: ',num)

Output

On executing the above program, you will get the following results −

Factorial of 4:  24