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move scalar-handling logic into possibly_convert_objects
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kmuehlbauer committed Dec 17, 2024
1 parent 86a408d commit 73e17d5
Showing 1 changed file with 10 additions and 12 deletions.
22 changes: 10 additions & 12 deletions xarray/core/variable.py
Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,6 @@
import numbers
import warnings
from collections.abc import Callable, Hashable, Mapping, Sequence
from datetime import timedelta
from functools import partial
from types import EllipsisType
from typing import TYPE_CHECKING, Any, NoReturn, cast
Expand Down Expand Up @@ -232,10 +231,16 @@ def _as_nanosecond_precision(data):

def _possibly_convert_objects(values):
"""Convert arrays of datetime.datetime and datetime.timedelta objects into
datetime64 and timedelta64, according to the pandas convention. For the time
being, convert any non-nanosecond precision DatetimeIndex or TimedeltaIndex
objects to nanosecond precision. While pandas is relaxing this in version
2.0.0, in xarray we will need to make sure we are ready to handle
datetime64 and timedelta64, according to the pandas convention.
* datetime.datetime
* datetime.timedelta
* pd.Timestamp
* pd.Timedelta
For the time being, convert any non-nanosecond precision DatetimeIndex or
TimedeltaIndex objects to nanosecond precision. While pandas is relaxing this
in version 2.0.0, in xarray we will need to make sure we are ready to handle
non-nanosecond precision datetimes or timedeltas in our code before allowing
such values to pass through unchanged. Converting to nanosecond precision
through pandas.Series objects ensures that datetimes and timedeltas are
Expand Down Expand Up @@ -305,13 +310,6 @@ def convert_non_numpy_type(data):
if isinstance(data, tuple):
data = utils.to_0d_object_array(data)

if isinstance(data, pd.Timestamp):
# TODO: convert, handle datetime objects, too
data = np.datetime64(data.value, "ns")

if isinstance(data, timedelta):
data = np.timedelta64(getattr(data, "value", data), "ns")

# we don't want nested self-described arrays
if isinstance(data, pd.Series | pd.DataFrame):
pandas_data = data.values
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