Lambda Function

A lambda function in Python is a small anonymous function defined using the lambda keyword.

• It is used to create quick, single-expression functions without needing to formally define them using def.

Syntax:

lambda arguments: expression

• lambda is the keyword.
• arguments are input parameters (can be more than one).
• expression is the operation or result (only one expression, no statements).

Advantages of Lambda Functions:

• Useful for short, quick functions.
• Helps reduce code clutter when passing functions as arguments.
• Ideal for functional programming use cases.

Limitations of Lambda Functions:

• Only one expression is allowed.
• Cannot contain multiple statements or annotations.
• Less readable for complex logic.

1.) Example: Basic Lambda Function:

• Here, square is a lambda function that takes one input x and returns x * x.

square = lambda x: x * x
print(square(4))  # Output: 16

2.) Example: Lambda Function with Multiple Arguments:

• This lambda takes two arguments and returns their sum.

add = lambda a, b: a + b
print(add(3, 5))  # Output: 8

3.) Example: Lambda with Conditional Expression

• A lambda that returns “Even” if the number is even, otherwise “Odd”:

check_even = lambda x: "Even" if x % 2 == 0 else "Odd"
print(check_even(7))  # Output: Odd

Common Use Cases of Lambda Functions:

Lambda functions are often used with functions like map(), filter(), and sorted().

1. Using with map():
   • Applies a lambda to each item in a list.

nums = [1, 2, 3, 4]
squares = list(map(lambda x: x * x, nums))
print(squares)  # Output: [1, 4, 9, 16]

2. Using with filter():
   • Filters items based on a condition.

nums = [1, 2, 3, 4, 5, 6]
evens = list(filter(lambda x: x % 2 = = 0, nums))
print(evens)  # Output: [2, 4, 6]

3. Using with sorted():
   • Sort a list of tuples by the second element.

pairs = [(1, 3), (2, 1), (4, 2)]
sorted_pairs = sorted(pairs, key=lambda x: x[1])
print(sorted_pairs)  # Output: [(2, 1), (4, 2), (1, 3)]