They allow you to write clean, concise, and expressive code that focuses on what to do, rather than how to do it.
A higher-order function (HOF) is a function that either takes one or more functions as arguments or returns a function as its result.
Because Python treats functions as first-class citizens, they can be manipulated like any other object, such as integers or strings.
Lambda (Anonymous Functions)
A lambda function is a small, anonymous function — meaning it has no name. It is defined using the lambda keyword and can take any number of arguments, but it can only contain a single expression.Syntax:
lambda arguments: expressionExample:
square = lambda x: x * x
print(square(5)) # Output: 25
Another example:
add = lambda a, b: a + b
print(add(3, 7)) # Output: 10
map()
The map() function applies a given function to each item in an iterable (like a list or tuple) and returns a map object (which can be converted into a list).Syntax:
map(function, iterable)Example:
numbers = [1, 2, 3, 4, 5]
squared = map(lambda x: x**2, numbers)
print(list(squared)) # Output: [1, 4, 9, 16, 25]
filter()
The filter() function filters elements from an iterable based on a condition provided by a function. It returns only those elements for which the function returns True.Syntax:
filter(function, iterable)Example:
numbers = [10, 15, 20, 25, 30]
even_numbers = filter(lambda x: x % 2 == 0, numbers)
print(list(even_numbers)) # Output: [10, 20, 30]
reduce()
The reduce() function (available in the functools module) repeatedly applies a function to the items of a sequence, reducing it to a single cumulative value.Syntax:
from functools import reduce
reduce(function, iterable)
Example:
from functools import reduce
numbers = [1, 2, 3, 4, 5]
product = reduce(lambda x, y: x * y, numbers)
print(product) # Output: 120
Summary
Lambda expressions and higher-order functions such as map(), filter(), and reduce() provide elegant and powerful ways to process data in Python.They reduce boilerplate code, eliminate unnecessary loops, and make data transformations and aggregations more concise, expressive, and easier to read.
| Concept | Description |
|---|---|
| lambda | Creates small, anonymous functions for short, one-line operations. |
| map() | Applies a function to every element in an iterable and returns an iterator. |
| filter() | Returns only the elements that satisfy a specified condition. |
| reduce() | Combines all elements of an iterable into a single result. |
| functools | Provides reduce() along with several other utilities for functional programming. |
