astype with 'datetime64[us, UTC]'

[davetapley]

I'm trying to use astype with datetime64[us, UTC].

If I pass a string (as the docs):

astype('datetime64[us, UTC]')

I get:

error: No overloads for "astype" match the provided arguments (reportCallIssue)

I also tried:

from datetime import UTC
from numpy import datetime64

astype(datetime64['us', UTC])

 error: Expected no type arguments for class "datetime64" (reportInvalidTypeArguments)

numpy/numpy#16545 seems to imply that should work, but I thought I'd open a discussion here before an issue there.

[Dr-Irv]

With respect to doing pd.Series.astype("datetime64[us, UTC]"), that is something that we could handle in the stubs, but it would be a challenge to handle all combinations of precision (the 'us' part) and timezone (the 'UTC' part). We do allow a string such as "datetime64[us]", but don't have all the time zone combinations. We'd need to add a LOT of strings to the definition of TimestampDtypeArg in _typing.pyi in order to handle all possible combinations.

With respect to the second example, I don't think the expression datetime64['us', UTC] is valid. I tried it with python 3.11 and numpy 2.0, and got a runtime error.

[herebebeasties]

Given UTC is massively more common than any other timezone, and that the only alternative here for the user is to add # type: ignore annotations, perhaps we could be pragmatic and add just the UTC types, which would hopefully fix well over half the instances of this particular issue?

[Dr-Irv]

Given UTC is massively more common than any other timezone, and that the only alternative here for the user is to add # type: ignore annotations, perhaps we could be pragmatic and add just the UTC types, which would hopefully fix well over half the instances of this particular issue?

Sure, I'm open to a PR that does that.