Skip to content
Related Articles

Related Articles

Python Lambda Functions
  • Difficulty Level : Easy
  • Last Updated : 13 Apr, 2021
GeeksforGeeks - Summer Carnival Banner

In Python, an anonymous function means that a function is without a name. As we already know that the def keyword is used to define a normal function in Python. Similarly, the lambda keyword is used to define an anonymous function in Python. It has the following syntax: 

Syntax: lambda arguments: expression
  • This function can have any number of arguments but only one expression, which is evaluated and returned.
  • One is free to use lambda functions wherever function objects are required.
  • You need to keep in your knowledge that lambda functions are syntactically restricted to a single expression.
  • It has various uses in particular fields of programming besides other types of expressions in functions.

Let’s look at this example and try to understand the difference between a normal def defined function and lambda function. This is a program that returns the cube of a given value:  

Python




# Python code to illustrate cube of a number
# showing difference between def() and lambda().
def cube(y):
    return y*y*y
 
lambda_cube = lambda y: y*y*y
 
# using the normally
# defined function
print(cube(5))
 
# using the lambda function
print(lambda_cube(5))

Output:

125
125

As we can see in the above example both the cube() function and lambda_cube() function behave the same and as intended. Let’s analyze the above example a bit more:

  • Without using Lambda: Here, both of them return the cube of a given number. But, while using def, we needed to define a function with a name cube and needed to pass a value to it. After execution, we also needed to return the result from where the function was called using the return keyword.
  • Using Lambda: Lambda definition does not include a “return” statement, it always contains an expression that is returned. We can also put a lambda definition anywhere a function is expected, and we don’t have to assign it to a variable at all. This is the simplicity of lambda functions.

Lambda functions can be used along with built-in functions like filter(), map() and reduce().



Using lambda() Function with filter()

The filter() function in Python takes in a function and a list as arguments. This offers an elegant way to filter out all the elements of a sequence “sequence”, for which the function returns True. Here is a small program that returns the odd numbers from an input list: 
 

Example 1:

Python




# Python code to illustrate
# filter() with lambda()
li = [5, 7, 22, 97, 54, 62, 77, 23, 73, 61]
 
final_list = list(filter(lambda x: (x%2 != 0) , li))
print(final_list)

Output:

[5, 7, 97, 77, 23, 73, 61]

Example 2:

Python3




# Python 3 code to people above 18 yrs
ages = [13, 90, 17, 59, 21, 60, 5]
 
adults = list(filter(lambda age: age>18, ages))
 
print(adults)

Output:

[90, 59, 21, 60]

Using lambda() Function with map()

The map() function in Python takes in a function and a list as an argument. The function is called with a lambda function and a list and a new list is returned which contains all the lambda modified items returned by that function for each item. Example: 
 

Example 1:

Python




# Python code to illustrate
# map() with lambda()
# to get double of a list.
li = [5, 7, 22, 97, 54, 62, 77, 23, 73, 61]
 
final_list = list(map(lambda x: x*2, li))
print(final_list)

Output:



[10, 14, 44, 194, 108, 124, 154, 46, 146, 122]

Example 2:

Python3




# Python program to demonstrate
# use of lambda() function
# with map() function
animals = ['dog', 'cat', 'parrot', 'rabbit']
 
# here we intend to change all animal names
# to upper case and return the same
uppered_animals = list(map(lambda animal: str.upper(animal), animals))
 
print(uppered_animals)

Output:

['DOG', 'CAT', 'PARROT', 'RABBIT']

Using lambda() Function with reduce()

The reduce() function in Python takes in a function and a list as an argument. The function is called with a lambda function and an iterable and a new reduced result is returned. This performs a repetitive operation over the pairs of the iterable. The reduce() function belongs to the  functools module. 

Example 1:

Python




# Python code to illustrate
# reduce() with lambda()
# to get sum of a list
 
from functools import reduce
li = [5, 8, 10, 20, 50, 100]
sum = reduce((lambda x, y: x + y), li)
print (sum)

Output:

193

Here the results of previous two elements are added to the next element and this goes on till the end of the list like (((((5+8)+10)+20)+50)+100).

Example 2:

Python3




# python code to demonstrate working of reduce()
# with a lambda function
 
# importing functools for reduce()
import functools
 
# initializing list
lis = [ 1 , 3, 5, 6, 2, ]
 
# using reduce to compute maximum element from list
print ("The maximum element of the list is : ",end="")
print (functools.reduce(lambda a,b : a if a > b else b,lis))

Output:

The maximum element of the list is : 6

This article is contributed by Chinmoy Lenka. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
 

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

My Personal Notes arrow_drop_up
Recommended Articles
Page :