''' 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)