Python Functionals I

Let’s learn some new Python concepts!. Map, Filter, lambda and Reduce are paradigms of functional programming. They allow the programmer (you) to write simpler, shorter code, without neccessarily needing to bother about intricacies like loops and branching.

lambda

Lambda is a single expression anonymous function often used as an inline function. In simple words, it is a function that has only one line in its body. It proves very handy in functional and GUI programming.

sum = lambda a, b, c: a + b + c
print(sum(1, 2, 3))
# prints 6

Map

The map() function executes a specified function for each item in iterables(as many as they are). The item is sent to the function as a parameter.

map(function, iterables)

Let’s say you are given a list of names, and you have to print a list that contains the length of each name.

print (list(map(len, ['Tina', 'Raj', 'Tom'])))  
# prints [4, 3, 3]

Filter

While map() passes each element in the iterable through a function and returns the result of all elements having passed through the function, filter(), first of all, requires the function to return boolean values (true or false) and then passes each element in the iterable through the function, “filtering” away those that are false.

filter(func, iterable)

Let’s see an example.

The following is a list (iterable) of the scores of 10 students in an exam. Let’s filter out those who passed with scores more than 75…using filter.

# Python 3
scores = [66, 90, 68, 59, 76, 60, 88, 74, 81, 65]

def is_A_student(score):
    return score > 75

over_75 = list(filter(is_A_student, scores))

print(over_75)

Reduce

reduce applies a function of two arguments cumulatively to the elements of an iterable, optionally starting with an initial argument.

Reduce is not in the __builtins__ module, so it needs to be imported as it resides in the functools module.

reduce(func, iterable[, initial])

Say you have a list, say [1,2,3] and you have to find its sum.

from functools import reduce
print(reduce(lambda x, y : x + y,[1,2,3]))
# prints 6

You can also define an initial value. If it is specified, the function will assume initial value as the value given, and then reduce. It is equivalent to adding the initial value at the beginning of the list.
For example:

from functools import reduce
print(reduce(lambda x, y : x + y, [1,2,3], -3))
# prints 3

from fractions import gcd
print(reduce(gcd, [2,4,8], 3))
# prints 1

Try the following excerise in the editor below.

In this exercise, you’ll use each of map, filter, and reduce to fix broken code.