map, filter and reduce in Python

map() applies a function to every item. filter() keeps only the items where a function returns True. reduce() combines all the items into one value.

The program

from functools import reduce

numbers = [1, 2, 3, 4, 5, 6]

squares = list(map(lambda x: x ** 2, numbers))
evens = list(filter(lambda x: x % 2 == 0, numbers))
product = reduce(lambda a, b: a * b, numbers)

print(squares)
print(evens)
print(product)

[1, 4, 9, 16, 25, 36]
[2, 4, 6]
720

How it works

• map() and filter() return lazy objects, not lists. They produce items only when asked, so list() is needed to see them all at once.
• reduce() takes the first two items, combines them, then combines that result with the next item, and so on: ((((1*2)*3)*4)*5)*6.
• reduce() is in the functools module. map() and filter() are built-ins.
• You can pass a normal function instead of a lambda: list(map(str, numbers)) turns every number into a string.

Another way: comprehensions and built-ins

Most Python code uses a list comprehension instead of map() and filter(), and a built-in such as sum() or math.prod() instead of reduce(). The results are the same:

import math

numbers = [1, 2, 3, 4, 5, 6]

print([x ** 2 for x in numbers])
print([x for x in numbers if x % 2 == 0])
print(math.prod(numbers))

[1, 4, 9, 16, 25, 36]
[2, 4, 6]
720

An empty list

reduce() on an empty list raises a TypeError, because there is no first item to start with. Pass a starting value as the third argument to avoid that:

from functools import reduce

print(reduce(lambda a, b: a * b, [], 1))

1