Map, Filter, and Reduce in Python

Map

The map function executes some operation on each item in an iterable series. The general syntax for the map function is;

map(<function>, <series>)

def double(number: int) -> int:
    return number * 2

res = map(double, [1, 2])

print(res)
# output: <map object at 0x00000166222BAC50>
for number in res:
    print(number)
# output:
# 2
# 4

or you can use lambda function: `

res = map(lambda x: x * 2, [1, 2])

Filter

The filter is similar to the map function, but, it filters them with a criterion function. If the criterion function returns True, the item is selected.

even = filter(lambda x: x % 2 == 0, [1, 2, 3, 4])

for number in even:
    print(number)
# output:
# 2
# 4

Reduce

The reduce function reduce the items in series into a single value. It is necessary to import reduce function from  the functools module. The general syntax for the reduce function is;

`reduce(, , )

from functools import reduce
  
numbers = [1, 2, 3, 5]
total = reduce(lambda reduced_sum, x: reduced_sum + x, numbers, 0)

print(total)
# output: 11

The reduce function takes three arguments:

• function
• series of items
• initial value

Function

The first argument, function, represents the operation we want to perform on each item.

lambda reduced_sum, x: reduced_sum + x

in which, the reduced_sum is a current reduced value and the x is a item whose turn it is to be processed. In each turn, the lambda function return the sum of current reduced value and item.

This lambda function is equivalent to the normal function below;

def sum_helper(reduced_sum, item):
  return reduced_sum + item
  
numbers = [1, 2, 3, 5]
total = reduce(sum_helper, numbers, 0)

print(total)
# output: 11

Initial value

The third argument, initial value, is optional. If the initial value is left out, reduce takes the first item in the list as the initial value and starts reducing from the second item onwards.