Higher-Order functions in Python

Higher-Order functions

These are the functions that is having another function as an argument or a function that returns another function as a return in the output.

Examples of Higher-Order functions are : map(), filter(), reduce()

Before looking further into these functions, let's see something known as Lambda Function.

LAMBDA FUNCTION:

• This function can have any number of arguments but only one expression, which is evaluated and returned.

• The lambda function is usually used with higher-order functions.

1. map()

• Map is a function that works like list comprehensions and for loops. It is used when you need to map or implement functions on various elements at the same time.

• SYNTAX: map(function, iterable object)

Let's see an example.

list_numbers = (1,2,3,4)
sample_map = map(lambda x: x*2, list_numbers)
print(list(sample_map))

The output we get is [2, 4, 6, 8].

2. filter()

• Filter is a similar operation, but it requires the function to look for a condition and then returns only those elements that satisfy the condition, from the collection.

• SYNTAX: filter(function, iterable object)

The following code prints the names that only start with an 'A'.

name = ['Harshit','Aman','Mohith','Akash']
sample_name = filter(lambda x : x.startswith("A"), name)
print(list(sample_name))

This prints the following output ['Aman', 'Akash'].

3. reduce()

• Reduce is used to apply a particular function passed in its argument to all of the list elements mentioned in the sequence passed along.

• SYNTAX: reduce(function, iterable object)

• Note: the reduce function needs to be imported from the 'functools' library.

from functools import reduce
list_1 = [7,8,4,6,3]
result = reduce(lambda x,y: x+y ,list_1)
print(result)

The result printed is 28 which is the cumulative sum of the list.

Hope this article was helpful. For further digging, take a look here.

Do share your thoughts in the comment section below. You can reach out to me on Linkedin as well. Happy learning!!