@Michael: As the previous author I fully support this proposal! ;) Thank you
for the revival. For reference, since you linked one of the answer of the
original thread, this is my original proposal:
https://mail.python.org/pipermail/python-ideas/2016-April/039836.html
Both suggested implementations are very interesting. If I'm not wrong they have
exactly the same behavior (except for __dict__).
Performance-wise with a quick test I get the following results:
t = (1, 2)
print("sizeof", sys.getsizeof(t)) # 56
print("sizeof type", sys.getsizeof(type(t))) # 408
print(timeit.timeit("(1, 2)")) # ~0.01
nt = namedtuple("nt", ["x", "y"])
print("sizeof", sys.getsizeof(nt(1, 2))) # 56
print("sizeof type", sys.getsizeof(type(nt(1, 2)))) # 896
print(timeit.timeit("nt(1, 2)", setup="from __main__ import nt")) # ~0.2
pt = atuple(x=1, y=2)
print("sizeof", sys.getsizeof(pt)) # 56
print("sizeof type", sys.getsizeof(type(pt))) # 896
print(timeit.timeit("atuple(x=12, y=16)", setup="from __main__ import atuple"))
# ~0.8
point = TupleWithNames(x=1, y=2)
print("sizeof", sys.getsizeof(point)) # 64
print("sizeof type", sys.getsizeof(type(point))) # 1064
print(timeit.timeit("TupleWithNames(x=12, y=16)", setup="from __main__ import
TupleWithNames")) # ~0.8
The timing performance of both solutions is roughly the same given the
measurament variation, but way slower than tuple an namedtuple.
TupleWithNames is a bit more memory hungry than atuple and namedtuple, but
there is only one type so if I understand correctly it would be a win for
multiple instances.
Maybe there is room for optimisation in both cases ?
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