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BUG: can't register cast functions between datetime64 and user dtype · Issue #21365 · numpy/numpy · GitHub

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BUG: can't register cast functions between datetime64 and user dtype #21365

Description

Describe the issue:

I'd like to register (unsafe) cast functions between datetime64 and a custom dtype. Per the docs, I use PyArray_RegisterCastFunc to register these. Essentially this logic:

// ...
PyArray_RegisterDataType(descr);
// ...
npy_datetime = PyArray_DescrFromType(NPY_DATETIME);
PyArray_RegisterCastFunc(npy_datetime, descr->type_num, cast_from_datetime);
PyArray_RegisterCastFunc(descr, NPY_DATETIME, cast_to_datetime);

These return no error state, and in fact PyArray_GetCastFunc returns the functions I set.

My actual code is here and happy to provide additional details about what I'm trying to do.

Until 1.20, this worked as expected (Time is my custom dtype):

>>> np.can_cast(np.dtype("datetime64[ns]"), Time, casting="unsafe")
True
>>> np.can_cast(Time, np.dtype("datetime64[ns]"), casting="unsafe")
True
>>> a
array([ora.Time(2022, 4, 20, 4, 3, 8.82545807, UTC)], dtype=Time)
>>> a.astype("datetime64[ns]")
array(['2022-04-20T04:03:08.825458080'], dtype='datetime64[ns]')

Starting in 1.21,

>>> np.can_cast(np.dtype("datetime64[ns]"), Time, casting="unsafe")
False
>>> np.can_cast(Time, np.dtype("datetime64[ns]"), casting="unsafe")
False
>>> a.astype("datetime64[ns]")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Cannot cast array data from dtype(Time) to dtype('<M8[ns]') according to the rule 'unsafe'

I assume this has something to do with NEP 42, though I don't understand it well enough to understand whether there is now a different mechanism available for adding conversions to/from datetime64.

Reproduce the code example:

import numpy
import ora

numpy.array([ora.now()]).astype("datetime64[ns]")

Error message:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Cannot cast array data from dtype(Time) to dtype('<M8[ns]') according to the rule 'unsafe'

NumPy/Python version information:

>>> print(numpy.__version__, sys.version)
1.21.0 3.8.13 (default, Apr 19 2022, 21:32:23)
[GCC 11.2.0]

Also tested in current main 55aacc7.

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