More elegant way to avoid this hacky implementation of single line reduce for grouping a collection?
MRAB
python at mrabarnett.plus.com
Fri Jan 25 18:50:27 EST 2019
On 2019-01-25 22:58, Travis Griggs wrote:
> Yesterday, I was pondering how to implement groupby, more in the vein of how Kotlin, Swift, Objc, Smalltalk do it, where order doesn’t matter. For example:
>
> def groupby(iterable, groupfunc):
> result = defaultdict(list)
> for each in iterable:
> result[groupfunc(each)].append(each)
> return result
>
> original = [1, 2, 3, 4, 5, 1, 2, 4, 2]
> groupby(original, lambda x: str(x)) ==> {‘1’: [1, 1], ‘2’: [2, 2, 2], ‘3’: [3], ‘4’: [4, 4], ‘5’: [5]}
>
> Easy enough, but I found myself obsessing about doing it with a reduce. At one point, I lost sight of whether that was even a better idea or not (the above is pretty simple); I just wanted to know if I could do it. My naive attempt didn’t work so well:
>
> grouped = reduce(
> lambda grouper, each: grouper[str(each)].append(each),
> allValues,
> defaultdict(list))
>
> Since the result of the append() function is None, the second reduction fails, because the accumulator ceases to be a dictionary.
>
> I persisted and came up with the following piece of evil, using a tuple to move the dict reference from reduction to reduction, but also force the (ignored) side effect of updating the same dict:
>
> grouped = reduce(
> lambda accum, each: (accum[0], accum[0][str(each)].append(each)),
> allValues,
> (defaultdict(list), None))[0]
>
> My question, only for the sake of learning python3 fu/enlightenment, is there a simpler way to do this with a reduce? I get there’s lots of way to do a groupby. The pursuit here is what’s the simplest/cleverest/sneakiest way to do it with reduce, especially if the quality that gorupfunc (str() in this example) is only called once per item is persevered.
>
How about this:
grouped = lambda iterable, groupfunc: dict(reduce(
lambda accum, each: accum[groupfunc(each)].append(each) or accum,
iterable,
defaultdict(list)))
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