Lambda Function in Python with Examples (Full Tutorial)

Python lambda functions are anonymous functions that are declared using the lambda keyword. A lambda function can take any number of arguments, but can only have one expression. It is often used with functions like map(), filter(), and reduce() for efficient one-line logic.

In this Python tutorial, we'll get into functions in Python covering aspects like the syntax of Python Lambda Functions, an example of Python Lambda Function, and the application of Lambda Function in Python.

What is a Lambda Function in Python?

• A kind of anonymous function is called a lambda function.
• Although a lambda function can only have one expression.
• It can have an unlimited number of parameters.

Python Lambda Function Syntax:

lambda arguments : expression

Python Lambda Function Example

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

Output

SCHOLARHAT

Practical Uses of Lambda Function in Python

In this section, we will learn various uses of the Lambda Function in Python

1. Condition Checking Using Python Lambda Function

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

Explanation:

2. List Comprehension using Python Lambda Function

We are generating a new lambda function with a default argument of x (the current item in the iteration) on each iteration within the list comprehension. Afterwards, we use item() to execute the same function object with the default parameter later on in the for loop, obtaining the required value. Consequently, the list of lambda function objects is stored in is_even_list.

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

3. if-else using Python Lambda Function

Max = lambda a, b : a if(a > b) else b
print(Max(4, 10))

Output

10

4. filter() Using lambda() Function

• Python's filter() function accepts two arguments: a list and a function.
• With this, you can effectively filter out any element of a "sequence" that the function returns True.
• This is a little software that takes an input list and returns the odd numbers:
• Use the filter() and lambda functions to eliminate all odd numbers.
• If x is not even, lambda x: (x % 2!= 0) yields True; otherwise, it returns False. All odd numbers that produced False are eliminated since filter() only retains elements where it returns True.

que = [5, 7, 33, 97, 54, 64, 77, 23, 74, 62]
 
final_list = list(filter(lambda x: (x % 2 != 0), que))
print(final_list)

Output

[5, 7, 33, 97, 77, 23]

5. Lambda Function using Multiple Statements

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]

6. map() with Using lambda() Function

1. Python's map() function accepts two arguments: a list and a function.
2. When a lambda function and a list are passed to the function, a new list containing every lambda-modified item that the function returned for each item is returned.
3. For instance:

• Use the lambda and map() functions to multiply each entry in a list by two.
• The lambda function and the "map" function are used in the code to duplicate every element in a list.
• The updated list with the doubled elements is then printed. Each element from the original list is multiplied by two and displayed in the output.

que = [5, 7, 22, 97, 54, 62, 77, 23, 73, 61]
final_list = list(map(lambda x: x*3, que))
print(final_list)

Output

[15, 21, 66, 291, 162, 186, 231, 69, 219, 183]

Convert elements to upper case using lambda and map() function

employess = ['daksh', 'heral', 'manish', 'reva']
uppered_employees = list(map(lambda employee: employee.upper(), employess))
print(uppered_employees)

Output

['DAKSH', 'HERAL', 'MANISH', 'REVA']

Explanation:

from demo import reduce
que = [33, 11, 50, 80, 50, 100]
sum = reduce((lambda a, b: a + b), que)
print(sum)

324

def cube(y):
	return y*y*y
lambda_cube = lambda y: y*y*y
print("Using function defined with `def` keyword, cube:", cube(6))
print("Using lambda function, cube:", lambda_cube(6))

Using function defined with `def` keyword, cube: 216
Using lambda function, cube: 216

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