Python : filter(), map() and reduce()

filter(), map() and reduce() tools are functional programming methods that can be
applied to iterable objects.

filter(<function>, <object>)

Iterates on object and returns the list of elements from <object> for which <function> returned True.
Usually, lambda functions are used for <function>. A lambda function returns True when the condition is met (example : lambda x: x <= 10).

values = range(100)
print filter(lambda x: x < 50, values)
# prints [0, 1, 2, 3, ..., 49]
print filter(lambda x: x > 50, values)
# prints [51, 52, 53, ..., 100]
print filter(lambda x: x%2 == 0)
# prints [0, 2, 4, ..., 100]

map(<function>, <object>)

Applies a function to every element of a list and returns the modified list.

cities = ['paris', 'london', 'berlin']
print map(lambda n: n.upper(), cities)
# prints ['PARIS', 'LONDON', 'BERLIN']

reduce(<function>, <list>)

Recursive process : at each step, passes the current operation result with the next item from the list.
By default, the first item in the list initializes the first operation result.
Note : reduce takes two parameters

print reduce(lambda x,y: x*y, [1,2,3,4])
# prints 24
# 1st cycle : multiplies 1 (first element) with 2
# 2nd cycle : multiplies 2 (result of previous operation) with 3 (next element)
# 3rd cycle : multiplies 6 (result of previous operation) with 4 (next element)

Cem SOYDING

Author & Editor

Senior software engineer with 12 years of experience in both embedded systems and C# .NET