Filter Map Reduce in python | python tutorials

 Filter Map Reduce in python | python tutorials

1. Filter

    Python’s filter() is a built-in function that allows you to process an iterable and extract those items that satisfy a given condition. 

        This process is commonly known as a filtering operation. With filter(), you can apply a filtering function to an iterable and produce a new iterable with the items that satisfy the condition at hand. 

def is_even(a):
    return a%2==0
lst = [2,3,4,6,7,3,1,23,76]
n = list(filter(is_even,lst))
print(n)

Output

[2, 4, 6, 76]

Using Lamda function

lst = [2,3,4,6,7,3,1,23,76]
evens = list(filter(lambda n: n%2==0, lst))
print(evens)

Output

[2, 4, 6, 76]

2. Map

    Python’s map() is a built-in function that allows you to process and transform all the items in an iterable without using an explicit for loop, a technique commonly known as mapping. 

    map() is useful when you need to apply a transformation function to each item in an iterable and transform them into a new iterable.

def update(n):
    return n+2
lst = [2,3,4,6,7,3,1,23,76]
# evens = list(filter(lambda n: n%2==0, lst))
doubles = list(map(update,evens))
print(evens)
print(doubles)

Output

[4, 6, 8, 78]

using lamda function

# def update(n):
#     return n+2
lst = [2,3,4,6,7,3,1,23,76]
evens = list(filter(lambda n: n%2==0, lst))
doubles = list(map(lambda n: n +2 ,evens))
print(evens)
print(doubles)

3. Reduce

    Python’s reduce() is a function that implements a mathematical technique called folding or reduction. 

    reduce() is useful when you need to apply a function to an iterable and reduce it to a single cumulative value.

from functools import reduce

# def add_all(a, b):
#     return a+b

lst = [2,3,4,6,7,3,1,23,76]
evens = list(filter(lambda n: n%2==0, lst))
doubles = list(map(lambda n: n +2 ,evens))
sum = reduce(lambda a,b: a+b, evens)
# sum = reduce(add_all,doubles)
print(evens)
print(doubles)
print(sum)

Output

[2, 4, 6, 76]
[4, 6, 8, 78]
88