The hacker with the supernumerary nipple

9 March 2019

Item-at-a-time Reduce Functions in Python

by Gianni Tedesco

If you need to write a Reduce function in python, there’s a number of ways of doing it. I’m going to assume you already know what that is and leap right in. Suffice to say, you can think of that as something like an aggregate function in an SQL query.

Perhaps the most obvious would be to use functools.reduce.

from functools import reduce
from operator import add

reduce(add, range(20))

But in this case you would need the entire iterable to be ready at the time of calling reduce. What if you want to call the reduce one step at a time? This would be particularly important, for example, if you were receiving the items over a network connection or reading them from a huge file.

With Generators

Another way might be to use a generator, but that’s not without it’s problems either:

from operator import add

def genreduce(init_val, func):
    val = init_val
    yield init_val
    while True:
        nxt = yield val
        val = func(val, nxt)

def online_reduce(func, init_val, gen):
    state = genreduce(init_val, func)
    init_val = next(state)
    for item in gen:
        init_val = state.send(item)
    return init_val

So now things have got pretty ponderous. And the two things we want to specify here are quite cumbersome to carry around - the function defining the reduction and it’s initial value.

With Function Attributes

What I’m really after is a concise way to specify the callees - the reduce functions themselves. And an intuitive pythonic protocol for a caller to use them.

Luckily, in Python, we can just add attributes to functions.

def foldsum(prev_val, val):
    return prev_val + val
foldsum.init_val = 0

def online_reduce(func, gen):
    val = func.init_val
    for item in gen:
        val = func(val, item)
    return val

This is nice, it lets us combine the function and the initial-value without resorting to defining some new class, or just using a tuple like (add, 0) which is essentially untyped and can get confusing.

It does make type checking blow up though.

With a Decorator

Lets try again but make this a function decorator. We want to be able to decorate our own functions as well as things like operator.add, so we’ll need an extra level of indirection so we don’t start adding attributes on to members of the operator module!

When it comes to typing, we want the caller to be able to access func.init_val without causing a type error. We can define a custom protocol for that using the typing_extensions module.

But also, our actual decorator needs to not blow up mypy and that gets a little bit tricky. I couldn’t figure out how to avoid using a cast.

With all that said, here’s all the tedious boilerplate for the decorator:

from typing import Callable,Any,cast
from typing_extensions import Protocol
from functools import wraps

class ReduceFunc(Protocol):
    init_val : Any
    def __call__(prev_val, val):
        raise NotImplementedError

def reducer(parm : Any):
    def decorator(func) -> ReduceFunc:
        def wrapper(a, b):
            return func(a, b)
        rf = cast(ReduceFunc, wrapper)
        rf.init_val = parm
        return rf
    return decorator

__all__ = (

And here’s two ways of defining a reduce function. First for a user-defined function, secondly when wrapping a function from somewhere else like the operator module.

def foldsum(prev_val, val):
    return prev_val + val
from operator import add
foldsum = reducer(0)(add)
tags: python - mypy