Iterable Functions - 1
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'''
This is a brief first part of a series on Python's built-ins that operate on
iterables. They are very useful in functional programming, as they avoid
mutable and state data.
'''
# filter(function, iterable) takes a function and an iterable. The function
# is called on each item in the iterable, and a new iterable (of the same type
# as the original iterable) is created and returned as a filter object.
a = [1, 2, 3, 4]
def by_two(arg):
return arg * 2
b = list(filter(by_two, a))
print(b)
# map(function, iterable, ...) takes a function an an iterable. Like filter,
# map applies the function to each variable in the iterable, but it returns a
# map object with the results as a list.
def by_three(arg):
return arg * 3
c = list(map(by_three, a))
print(c)
# reduce(function, iterable [, initializer]) takes a functoin and an iterable
# (again). This time, the function is applied to each value in the iterable
# to reduce the iterable to a single value. If the initializer is present, it
# serves as a fallback and is returned when the iterable is empty.
import functools as f
def get_sum(accum, new):
return accum + new
d = f.reduce(get_sum, a)
e = f.reduce(get_sum, a, 10)
print(d)
print(e)
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