I'm -1 on adding it in stdlib.
But if it happens, I'm -1 on functools and collections. They are used very much. Every Python tool import them regardless how much of their contents are used.
On the other hand, itertools contains random stuff very rarely used.
If you really want to add it in collections, I suggests from collections.groupdict import GroupDict.
Regards,
On Tue, Jul 3, 2018 at 10:23 PM David Mertz mertz@gnosis.cx wrote:
Guido said he has mooted this discussion, so it's probably not reaching him. It took one thousand fewer messages for him to stop following this than with PEP 572, for some reason :-).
But before putting it on auto-archive, the BDFL said (1) NO GO on getting a new builtin; (2) NO OBJECTION to putting it in itertools.
My problem with the second idea is that *I* find it very wrong to have something in itertools that does not return an iterator. It wrecks the combinatorial algebra of the module.
That said, it's easy to fix... and I believe independently useful. Just make grouping() a generator function rather than a plain function. This lets us get an incremental grouping of an iterable. This can be useful if the iterable is slow or infinite, but the partial groupings are useful in themselves.
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from grouping import grouping grouped = grouping('AbBa', key=str.casefold) for dct in grouped: print(dct)
... {'a': ['A']} {'a': ['A'], 'b': ['b']} {'a': ['A'], 'b': ['b', 'B']} {'a': ['A', 'a'], 'b': ['b', 'B']}
This isn't so useful for the concrete sequence, but for this it would be great:
for grouped in grouping(data_over_wire()):
process_partial_groups(grouped)The implementation need not and should not rely on "pre-grouping" with itertools.groupby:
def grouping(iterable, key=None): groups = {} key = key or (lambda x: x) for item in iterable: groups.setdefault(key(item), []).append(item) yield groups
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