''' lambdas.py
    demonstrates some functional programming features'''

from functools import reduce

''' lambdas are one line anonymous functions ''' 
g = lambda x : x+5

''' filters are functions that return True or False '''
def even(x):
	if x % 2 == 0 :
		return True
	else:
		return False

def cube(x,y):
	return y**x

print(g(8))	# calling the lambda function

mylist = []

''' filters can be applied across a range of values. It returns a list
    of values for which the filter returned true. '''
myfilter = filter(even, range(0,47))

''' Iterate through the list to get the filtered values ''' 
mylist = [x for x in myfilter ] 
print (mylist)

''' map applies a function across a range of values. Similar to filter, except
    maps can apply any function, where filters only take functions that return
    True or False '''
mymap = map(cube, range(0,15), range(0,5))
mylist = [x for x in mymap]
print(mylist)

def mult(x,y):
	return x*y

''' A reduce function applies the function across the range, taking the first 2
    values the first time, and then applies the result of the operation with
    every subsequent value, one at a time. '''
print(reduce(mult, range(2,10)))