Josh Bohde

Functional Python

Posted by Josh Bohde

It seems to me that Python as a language has a weird relationship to functional programming. Things such as the itertools module and the builtin map, filter, and reduce rely heavily a functional style, yet these approaches are often not idiomatic.

As I explore other languages, I wonder what would Python written in a functional style would look like. An evening spent hacking on it has produces some interesting results. These techniques probably shouldn't be seriously used, but this code is just for fun.

Let's examine a short imperative script

def imperative_style(xs):
results = []
for x in xs:
if x >= 7:
break
if x < 2:
result = 4 * x
results.append(result)
return results
 
assert imperative_style(range(10)) == [0, 4]

Whenever I see code like the above imperative_style, I mentally file it as point of possible complexity and bugs, especially as requirements change and more logic is tacked on.

As a comparison, let's look at a simple functional version. First, we're going to need takewhile from itertools, which will allow us to build something like the break statement

After that, we have the function definition, utilizing two builtins, map and filter, as well as takewhile to break the problem down into logically independent parts. Notice that the conditional in the takewhile is inverted.

from itertools import takewhile
 
def functional_style(xs):
return map(lambda x: 4 * x,
filter(lambda x: x < 2,
takewhile(lambda x: x < 7, xs)))
 
assert functional_style(range(10)) == [0, 4]

There are less moving parts here, but it seems too much like a Christmas tree for me. Can we make it flatter?

For this, we're going to need more tools for working with functions. First is compose, which let's us feed the result of one function as the argument of another. I'm always surprised that Python doesn't have this builtin. In more functional languages this is a basic feature, with Haskell making it one character (.)

def compose_two(g, f):
"""Function composition for two functions, e.g. compose_two(f, g)(x) == f(g(x))"""
return lambda *args, **kwargs: g(f(*args, **kwargs))
 
assert compose_two(lambda x: x * 2,
lambda y: y + 4)(1) == 10
 
def compose(*funcs):
"""Compose an arbitrary number of functions left-to-right passed as args"""
return reduce(compose_two, funcs)

With compose, we need one more function, partial, which can be used to provide only some of a function's arguments.

from functools import partial
composition_style = compose(
partial(map, lambda x: 4 * x),
partial(filter, lambda x: x < 2),
partial(takewhile, lambda x: x < 7))
 
assert composition_style(range(10)) == [0, 4]

There's a quite a bit of boilerplate in this definition. Can we abstract out a reusable pattern?

from itertools import starmap
def composed_partials(*partial_funcs):
return compose(*starmap(partial, partial_funcs))
 
composed_partials_style = composed_partials(
(map, lambda x: 4 * x),
(filter, lambda x: x < 2),
(takewhile, lambda x: x < 7))
 
assert composed_partials_style(range(10)) == [0, 4]

This is less noisy, but it's a bit difficult to read the logic in reverse order. Can we change that?

def pipe(*partial_funcs):
return composed_partials(*reversed(partial_funcs))
 
pipe_style = pipe(
(takewhile, lambda x: x < 7),
(filter, lambda x: x < 2),
(map, lambda x: 4 * x))
 
assert pipe_style(range(10)) == [0, 4]

This definition is more dataflow oriented, much like using pipes in a shell, or Clojure's -> macro. If you look at it just right, this definition looks a bit like a lisp with currying.

This may be too far, but looking at the definition for composed_partials and pipe, they follow a similar structure. Can we extract that out?

def transform_args(func, transformer):
return lambda *args: func(*transformer(args))
 
composed_partials = transform_args(compose, partial(starmap, partial))
pipe = transform_args(composed_partials, reversed)
 
assert composed_partials_style(range(10)) == [0, 4]
assert pipe_style(range(10)) == [0, 4]

With that, our final complete version is the following:

from itertools import takewhile, starmap
from functools import partial
 
def compose_two(g, f):
"""Function composition for two functions, e.g. compose_two(f, g)(x) == f(g(x))"""
return lambda *args, **kwargs: g(f(*args, **kwargs))
 
def compose(*funcs):
"""Compose an arbitrary number of functions left-to-right passed as args"""
return reduce(compose_two, funcs)
 
def transform_args(func, transformer):
return lambda *args: func(*transformer(args))
 
composed_partials = transform_args(compose, partial(starmap, partial))
pipe = transform_args(composed_partials, reversed)
 
pipe_style = pipe(
(takewhile, lambda x: x < 7),
(filter, lambda x: x < 2),
(map, lambda x: 4 * x))

It's a bit longer than the original version, but provides small reusable parts that can be quickly assembled into larger programs.