functional programming

Functional Programming (FP) is a programming paradigm that emphasizes pure functions, immutable data, and function composition.

In Python, functional programming usually means writing functions that avoid changing global state and rely solely on their inputs and return values.

Although Python isn’t purely functional, you can still follow many functional principles using higher-order functions, lambda expressions, and built-in tools like map(), filter() and functools.reduce().

Key Concepts

Pure Functions: Return the same result given the same inputs, without side effects.
Immutability: Data doesn’t change in place; each operation creates new data.
Higher-Order Functions: Functions that take other functions as arguments or return them as results.

Example in Python

Python
      
    
from functools import reduce

numbers = [1, 2, 3, 4, 5]
doubled = map(lambda x: x * 2, numbers)
filtered = filter(lambda x: x % 2 == 0, doubled)
summed = reduce(lambda acc, x: acc + x, filtered, 0)

print(summed)  # 12

Real-world usage often involves processing large data sets or composing pipelines of small, reusable functions, making your code easier to test and maintain.

A smiling person with their hands crossed, looking at a machine that displays the names of the functions map, filter, and reduce

Learning Path