There are some cases when that's the correct behavior. It mimics
pandas.DataFrame.groupby. For example, what if you have a sequence of (key,
v1, v2) triples? Group by key, then keep the triples intact is the right
choice sometimes.
On Wed, Jul 4, 2018, 6:39 AM David Mertz <me...@gnosis.cx> wrote:
> Steven:
>
> You've misunderstood part of the discussion. There are two different
> signatures being discussed/proposed for a grouping() function.
>
> The one you show we might call grouping_michael(). The alternate API we
> might call grouping_chris(). These two calls will produce the same result
> (the first output you show)
>
> grouping_michael(words, keyfunc=len)
> grouping_chris((len(word), word) for word in words)
>
> I happen to prefer grouping_michael(), but recognize they each make
> slightly different things obvious. Absolutely no one wants the behavior in
> your second output.
>
> On Tue, Jul 3, 2018, 9:32 PM Steven D'Aprano <st...@pearwood.info> wrote:
>
>> Of course you can prepare the sequence any way you like, but these are
>> not equivalent:
>>
>> grouping(words, keyfunc=len)
>> grouping((len(word), word) for word in words)
>>
>> The first groups words by their length; the second groups pairs of
>> (length, word) tuples by equality.
>>
>> py> grouping("a bb ccc d ee fff".split(), keyfunc=len)
>> {1: ['a', 'd'], 2: ['bb', 'ee'], 3: ['ccc', 'fff']}
>>
>> py> grouping((len(w), w) for w in "a bb ccc d ee fff".split())
>> {(3, 'ccc'): [(3, 'ccc')], (1, 'd'): [(1, 'd')], (2, 'ee'): [(2, 'ee')],
>> (3, 'fff'): [(3, 'fff')], (1, 'a'): [(1, 'a')], (2, 'bb'): [(2, '
>>
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