Python Lambda Functions: Anonymous Functions, Map, Filter & Reduce

In Python, a lambda function is a small, anonymous function defined without a name using the lambda keyword. While standard functions are declared using def with formal function names and multi-line bodies, lambdas are designed for quick, throwaway single-expression operations—especially when passing callback functions to map(), filter(), and sort().

1. Syntax and Basic Comparison: def vs lambda

# Standard def function:
def square(x):
    return x ** 2

# Equivalent lambda function:
square_lambda = lambda x: x ** 2

print("Standard:", square(6))          # 36
print("Lambda:  ", square_lambda(6))   # 36

Lambda with multiple arguments:

multiply = lambda a, b, c: a * b * c
print("Product:", multiply(2, 3, 4))  # 24

2. Sorting with Lambdas (Custom Keys)

The most common real-world use of lambdas is providing custom sorting criteria to sort() and sorted():

students = [
    {"name": "Rohan", "gpa": 8.4},
    {"name": "Ananya", "gpa": 9.8},
    {"name": "Vikram", "gpa": 7.9}
]

# Sort students in descending order of GPA using lambda:
students.sort(key=lambda s: s["gpa"], reverse=True)

for s in students:
    print(f"{s['name']}: {s['gpa']}")

3. Functional Programming Trio: map(), filter(), reduce()

A. map(function, iterable): Transform Each Element

celsius_temps = [0, 20, 35, 100]
# Convert to Fahrenheit: (C * 9/5) + 32
fahrenheit = list(map(lambda c: (c * 9/5) + 32, celsius_temps))
print("Fahrenheit:", fahrenheit)  # [32.0, 68.0, 95.0, 212.0]

B. filter(function, iterable): Extract Matching Elements

numbers = [12, 45, 68, 73, 84, 91, 102]
# Filter out only numbers divisible by 4:
div_by_4 = list(filter(lambda x: x % 4 == 0, numbers))
print("Divisible by 4:", div_by_4)  # [12, 68, 84]

C. functools.reduce(function, iterable): Cumulative Computation

from functools import reduce

# Calculate Factorial / Cumulative Product of [1, 2, 3, 4, 5]:
nums = [1, 2, 3, 4, 5]
product = reduce(lambda acc, item: acc * item, nums)
print("Product of list:", product)  # 120

Frequently Asked Questions (FAQ)