5.6 The lambda function (BT101CO)

The structure of a lambda function is very concise:

lambda arguments : expression

• lambda: The keyword that initiates the function.
• Arguments: One or more inputs (separated by commas).
• Colon (:): Separates the arguments from the logic.
• Expression: The single line of code that is executed and automatically returned.

Let's compare a standard function with a lambda function that calculates the square of a number.

def square(x):
    return x * x

print(square(5)) # 25

square_lambda = lambda x: x * x

print(square_lambda(5)) # 25

• Anonymous: They don't have a name unless you assign them to a variable.
• Single Expression: You cannot have multiple lines, loops, or complex if-else blocks.
• Implicit Return: You don't type the word return; the result of the expression is returned by default.

The true power of lambda functions is revealed when they are used as arguments inside higher-order functions.

A. Using with filter()

filter() keeps only items where the function returns True.

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

B. Using with map()

map() applies the function to every item in a list.

nums = [1, 2, 3, 4]
# Double every number
doubled = list(map(lambda x: x * 2, nums))
print(doubled) # Output: [2, 4, 6, 8]

C. Using with sorted()

You can use a lambda as a "key" to sort complex data structures (like tuples).

students = [("Ashok", 85), ("Amit", 92), ("Suman", 78)]
# Sort by grade (the second element in the tuple)
students.sort(key=lambda x: x[1])
print(students) # Output: [('Suman', 78), ('Ashok', 85), ('Amit', 92)]