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Map, Filter and Reduce in Python

 


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Map, Filter, and Reduce in Python

Python provides three powerful functions for functional programming: map(), filter(), and reduce(). These functions allow for efficient and readable data processing operations on iterables.

1. map()

The map() function applies a given function to all items in an input list (or any other iterable) and returns an iterator of the results.

Example:


# Define a function to square a number
def square(x):
    return x**2

numbers = [1, 2, 3, 4, 5]
squared_numbers = map(square, numbers)
print(list(squared_numbers))  # Output: [1, 4, 9, 16, 25]

2. filter()

The filter() function constructs an iterator from elements of an iterable for which a function returns true.

Example:


# Define a function to check if a number is even
def is_even(x):
    return x % 2 == 0

numbers = [1, 2, 3, 4, 5]
even_numbers = filter(is_even, numbers)
print(list(even_numbers))  # Output: [2, 4]

3. reduce()

The reduce() function from the functools module applies a binary function cumulatively to the items of an iterable, from left to right, so as to reduce the iterable to a single value.

Example:


from functools import reduce

# Define a function to multiply two numbers
def multiply(x, y):
    return x * y

numbers = [1, 2, 3, 4, 5]
product = reduce(multiply, numbers)
print(product)  # Output: 120
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