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Python Lambda Functions

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Python Lambda Functions are anonymous functions means that the function is without a name. As we already know 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

Python Lambda Function 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.

Python Lambda Function Example

In the example, we defined a lambda function(upper) to convert a string to its upper case using upper().

This code defines a lambda function named upper that takes a string as its argument and converts it to uppercase using the upper() method. It then applies this lambda function to the string ‘GeeksforGeeks’ and prints the result

Python3




str1 = 'GeeksforGeeks'
 
upper = lambda string: string.upper()
print(upper(str1))


Output:

GEEKSFORGEEKS

Use of Lambda Function in Python

Let’s see some of the practical uses of the Python lambda function.

Condition Checking Using Python lambda function

Here, the ‘format_numric’ calls the lambda function, and the num is passed as a parameter to perform operations.

Python3




format_numeric = lambda num: f"{num:e}" if isinstance(num, int) else f"{num:,.2f}"
 
print("Int formatting:", format_numeric(1000000))
print("float formatting:", format_numeric(999999.789541235))


Output:

Int formatting: 1.000000e+06
float formatting: 999,999.79

Difference Between Lambda functions and def defined function

The code defines a cube function using both the def' keyword and a lambda function. It calculates the cube of a given number (5 in this case) using both approaches and prints the results. The output is 125 for both the def' and lambda functions, demonstrating that they achieve the same cube calculation.

Python3




def cube(y):
    return y*y*y
 
lambda_cube = lambda y: y*y*y
print("Using function defined with `def` keyword, cube:", cube(5))
print("Using lambda function, cube:", lambda_cube(5))


Output:

Using function defined with `def` keyword, cube: 125
Using lambda function, cube: 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:

With lambda function

Without lambda function

Supports single-line sometimes statements that return some value. Supports any number of lines inside a function block
Good for performing short operations/data manipulations. Good for any cases that require multiple lines of code.
Using the lambda function can sometime reduce the readability of code. We can use comments and function descriptions for easy readability.

Practical Uses of Python lambda function

Python Lambda Function with List Comprehension

On each iteration inside the list comprehension, we are creating a new lambda function with a default argument of x (where x is the current item in the iteration). Later, inside the for loop, we are calling the same function object having the default argument using item() and get the desired value. Thus, is_even_list stores the list of lambda function objects.

Python3




is_even_list = [lambda arg=x: arg * 10 for x in range(1, 5)]
for item in is_even_list:
    print(item())


Output:

10
20
30
40

Python Lambda Function with if-else

Here we are using the Max lambda function to find the maximum of two integers.

Python3




Max = lambda a, b : a if(a > b) else b
print(Max(1, 2))


Output:

2

Python Lambda with Multiple Statements

Lambda functions do not allow multiple statements, however, we can create two lambda functions and then call the other lambda function as a parameter to the first function. Let’s try to find the second maximum element using lambda.

The code defines a list of sublists called List'. It uses lambda functions to sort each sublist and find the second-largest element in each sublist. The result is a list of second-largest elements, which is then printed. The output displays the second-largest element from each sublist in the original list.

Python3




List = [[2,3,4],[1, 4, 16, 64],[3, 6, 9, 12]]
 
sortList = lambda x: (sorted(i) for i in x)
secondLargest = lambda x, f : [y[len(y)-2] for y in f(x)]
res = secondLargest(List, sortList)
 
print(res)


Output:

[3, 16, 9]

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: 

Filter out all odd numbers using filter() and lambda function

Here, lambda x: (x % 2 != 0) returns True or False if x is not even. Since filter() only keeps elements where it produces True, thus it removes all odd numbers that generated False.

Python3




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]

Filter all people having age more than 18, using lambda and filter() function

The code filters a list of ages and extracts the ages of adults (ages greater than 18) using a lambda function and the filter' function. It then prints the list of adult ages. The output displays the ages of individuals who are 18 years or older.

Python3




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: 

Multiply all elements of a list by 2 using lambda and map() function

The code doubles each element in a list using a lambda function and the map' function. It then prints the new list with the doubled elements. The output displays each element from the original list, multiplied by 2.

Python3




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]

Transform all elements of a list to upper case using lambda and map() function

The code converts a list of animal names to uppercase using a lambda function and the map' function. It then prints the list with the animal names in uppercase. The output displays the animal names in all uppercase letters.

Python3




animals = ['dog', 'cat', 'parrot', 'rabbit']
uppered_animals = list(map(lambda animal: animal.upper(), 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. 

A sum of all elements in a list using lambda and reduce() function

The code calculates the sum of elements in a list using the reduce' function from the functools' module. It imports reduce', defines a list, applies a lambda function that adds two elements at a time, and prints the sum of all elements in the list. The output displays the computed sum.

Python3




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 the 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).

Find the maximum element in a list using lambda and reduce() function

The code uses the functools' module to find the maximum element in a list (lis') by employing the reduce' function and a lambda function. It then prints the maximum element, which is 6 in this case.

Python3




import functools
lis = [1, 3, 5, 6, 2, ]
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


Last Updated : 17 Nov, 2023
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