How to use Lambda Function in Python?

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Lambda Function in Python

Lamda functions are inline functions, i.e., functions that are written in a single line instead of using multiple lines. These are anonymous functions (functions without a name).

We can define a lambda function using the lambda keyword. These are typically used when we need to return a function from another function or accept a function as a parameter.

We can also use lambda functions with built-in functions like map(), filter(), and sorted(), where we need to perform a small operation quickly without writing a separate full function.

Lamda function is basically a shortcut for writing a function with a return statement in one line. we use these where we don't need to define a function using the def keyword.

Syntax of a Lambda Function

Following is the basic syntax of a lambda function -

lambda arguments: expression

Here,

arguments is the input (can be one or more).
expression is the single line of logic to run and return.

Example: Lambda Function to Add Two Numbers

Let us look at an example where we add two numbers using both a regular function and a lambda function -

# Regular function
def add(x, y):
   return x + y

# Same functionality using lambda
add_lambda = lambda x, y: x + y

print("Regular Function",add(5, 3))        
print("Using Lambda",add_lambda(5, 3))

As you can see, both the regular function and the lambda function return the same result. The lambda function provides a shorter way to achieve the same functionality -

Regular Function 8
Using Lambda 8

Using Lambda with map() Function

The map() function in Python is used to apply a function to each element of an iterable (like a list or tuple) and returns a new iterable with the results. When combined with a lambda function, it becomes a quick way to transform data without defining a separate function using def.

Syntax

Following is the basic syntax of using lambda with the map() function -

map(function, iterable)

Here,

function: It is a function to apply to each item. This can be a lambda function.
iterable: It is the collection of items you want to process (like a list).

Example: Square Each Number in a List

Let us use a lambda function with map() function to square each number in a list -

numbers = [1, 2, 3, 4]

# Using lambda with map to square each number
squared = list(map(lambda x: x ** 2, numbers))

print("Original:", numbers)
print("Squared:", squared)

Following is the output obtained -

Original: [1, 2, 3, 4]
Squared: [1, 4, 9, 16]

Using Lambda with filter() Function

The filter() function in Python is used to filter items from an iterable based on a condition. It returns a new iterable containing only the items for which the provided function returns True.

When combined with a lambda function, it becomes an easy way to write short filtering logic without creating a full function using def.

Syntax

Following is the basic syntax of using lambda with filter() function -

filter(function, iterable)

Here,

function: is a function that returns True or False for each item.
iterable: is the collection of items you want to filter.

Example: Filter Even Numbers

In this example, we use a lambda function with filter() function to filter even numbers from a list -

numbers = [1, 2, 3, 4, 5, 6]

# Filter even numbers using lambda
even_numbers = list(filter(lambda x: x % 2 == 0, numbers))

print("Even Numbers:", even_numbers)

We get the output as shown below -

Even Numbers: [2, 4, 6]

Using Lambda with sorted() Function

The sorted() function in Python is used to return a new sorted list from the elements of any iterable. By default, it sorts in ascending order, but you can customize the sorting using a key parameter.

When combined with a lambda function, it allows us to define custom sorting logic in a single line without creating a separate function using def.

Syntax

Following is the basic syntax of using lambda with sorted() function -

sorted(iterable, key=lambda item: expression)

Here,

iterable: is the collection of items to sort.
key: is a function (often a lambda) that returns the value to sort by.

Example: Sort List of Tuples by Second Element

In the following example, we use a lambda function to sort a list of tuples based on the second element of each tuple -

data = [(1, 3), (4, 1), (2, 2)]

# Sort by second element
sorted_data = sorted(data, key=lambda x: x[1])

print("Sorted by Second Element:", sorted_data)

Following is the output of the above code -

Sorted by Second Element: [(4, 1), (2, 2), (1, 3)]

Assigning Lambda Function to a Variable

You can assign a lambda function to a variable, which allows you to use it just like a regular function defined with def. This is useful when you want to reuse the lambda multiple times in your program or give it a more meaningful name.

Once assigned to a variable, the lambda function behaves exactly like any other function. You can call it with arguments, pass it to other functions, or even use it inside data structures.

Example: Lambda to Multiply Two Numbers

In this example, we assign a lambda function to a variable called multiply. This lambda takes two arguments and returns their product -

# Assigning lambda to a variable
multiply = lambda a, b: a * b

# Using the lambda function
print(multiply(4, 5))

We get the output as shown below -

When to Use Lambda Functions

Lambda functions are best used when -

You need a small function for a short task.
You do not want to reuse the function elsewhere.
You want to pass a function as an argument to another function.

Limitations of Lambda Functions

Although lambda functions are useful, they also have some limitations -

They can only contain one expression.
No multiple statements or complex logic.
They are less readable if overused.

Sarika Singh

Updated on: 2025-04-14T15:39:42+05:30

3K+ Views

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