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Raise error when trying to construct time-zone aware timestamps #13830

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Aug 7, 2023
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Raise error when trying to construct time-zone aware timestamps #13830

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8ae8316
Raise error for timze-aware timestamps
galipremsagar Aug 7, 2023
44a733e
Update python/cudf/cudf/core/column/datetime.py
galipremsagar Aug 7, 2023
7235fe7
Apply suggestions from code review
galipremsagar Aug 7, 2023
5d77eb5
Apply suggestions from code review
galipremsagar Aug 7, 2023
ac9933a
handle datetime objects
galipremsagar Aug 7, 2023
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16 changes: 11 additions & 5 deletions python/cudf/cudf/core/column/datetime.py
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Original file line number Diff line number Diff line change
Expand Up @@ -242,14 +242,20 @@ def normalize_binop_value(self, other: DatetimeLikeScalar) -> ScalarLike:
if isinstance(other, (cudf.Scalar, ColumnBase, cudf.DateOffset)):
return other

if isinstance(other, datetime.datetime):
other = np.datetime64(other)
elif isinstance(other, datetime.timedelta):
other = np.timedelta64(other)
elif isinstance(other, pd.Timestamp):
if isinstance(other, pd.Timestamp):
if other.tz is not None:
raise TypeError(
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"Cannot perform binary operation on timezone-naive columns"
" and timezone-aware timestamps. For that, "
"use `tz_localize`."
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)
other = other.to_datetime64()
elif isinstance(other, pd.Timedelta):
other = other.to_timedelta64()
elif isinstance(other, datetime.datetime):
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What about TZ-aware datetime.datetime objects? e.g.

>>> import datetime
>>> datetime.datetime.now(datetime.timezone.utc)
datetime.datetime(2023, 8, 7, 20, 47, 48, 483493, tzinfo=datetime.timezone.utc)

Do those need to error, too? On conversion to np.datetime64, I get a warning. Is that sufficient?

>>> np.datetime64(datetime.datetime(2023, 8, 7, 20, 47, 48, 483493, tzinfo=datetime.timezone.utc))
<stdin>:1: DeprecationWarning: parsing timezone aware datetimes is deprecated; this will raise an error in the future
numpy.datetime64('2023-08-07T20:47:48.483493')

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I think we should raise for it too. Good catch, I thought datetime was tz agnostic.

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@bdice I updated the code to handle datetime.datetime objects aswell.

other = np.datetime64(other)
elif isinstance(other, datetime.timedelta):
other = np.timedelta64(other)

if isinstance(other, np.datetime64):
if np.isnat(other):
Expand Down
14 changes: 11 additions & 3 deletions python/cudf/cudf/core/column/timedelta.py
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Expand Up @@ -213,12 +213,20 @@ def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
def normalize_binop_value(self, other) -> ColumnBinaryOperand:
if isinstance(other, (ColumnBase, cudf.Scalar)):
return other
if isinstance(other, datetime.timedelta):
other = np.timedelta64(other)
elif isinstance(other, pd.Timestamp):

if isinstance(other, pd.Timestamp):
if other.tz is not None:
raise TypeError(
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"Cannot perform binary operation on timezone-naive columns"
" and timezone-aware timestamps. For that, "
"use `tz_localize`."
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)
other = other.to_datetime64()
elif isinstance(other, pd.Timedelta):
other = other.to_timedelta64()
elif isinstance(other, datetime.timedelta):
other = np.timedelta64(other)

if isinstance(other, np.timedelta64):
other_time_unit = cudf.utils.dtypes.get_time_unit(other)
if np.isnat(other):
Expand Down
8 changes: 8 additions & 0 deletions python/cudf/cudf/tests/test_datetime.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2093,3 +2093,11 @@ def test_construction_from_tz_timestamps(data):
_ = cudf.Series(data)
with pytest.raises(NotImplementedError):
_ = cudf.Index(data)


@pytest.mark.parametrize("op", _cmpops)
def test_datetime_binop_tz_timestamp(op):
s = cudf.Series([1, 2, 3], dtype="datetime64[ns]")
pd_tz_timestamp = pd.Timestamp("1970-01-01 00:00:00.000000001", tz="utc")
with pytest.raises(TypeError):
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op(s, pd_tz_timestamp)
8 changes: 7 additions & 1 deletion python/cudf/cudf/tests/test_scalar.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2021-2022, NVIDIA CORPORATION.
# Copyright (c) 2021-2023, NVIDIA CORPORATION.

import datetime
import re
Expand Down Expand Up @@ -450,3 +450,9 @@ def test_scalar_numpy_casting():
s1 = cudf.Scalar(1, dtype=np.int32)
s2 = np.int64(2)
assert s1 < s2


def test_construct_timezone_scalar_error():
pd_scalar = pd.Timestamp("1970-01-01 00:00:00.000000001", tz="utc")
with pytest.raises(TypeError):
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cudf.utils.dtypes.to_cudf_compatible_scalar(pd_scalar)
8 changes: 8 additions & 0 deletions python/cudf/cudf/tests/test_timedelta.py
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Expand Up @@ -1426,3 +1426,11 @@ def test_timedelta_constructor(data, dtype):
actual = cudf.TimedeltaIndex(data=cudf.Series(data), dtype=dtype)

assert_eq(expected, actual)


@pytest.mark.parametrize("op", [operator.add, operator.sub])
def test_timdelta_binop_tz_timestamp(op):
s = cudf.Series([1, 2, 3], dtype="timedelta64[ns]")
pd_tz_timestamp = pd.Timestamp("1970-01-01 00:00:00.000000001", tz="utc")
with pytest.raises(TypeError):
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op(s, pd_tz_timestamp)
16 changes: 11 additions & 5 deletions python/cudf/cudf/utils/dtypes.py
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Expand Up @@ -270,14 +270,20 @@ def to_cudf_compatible_scalar(val, dtype=None):
# the string value directly (cudf.DeviceScalar will DTRT)
return val

if isinstance(val, datetime.datetime):
val = np.datetime64(val)
elif isinstance(val, datetime.timedelta):
val = np.timedelta64(val)
elif isinstance(val, pd.Timestamp):
if isinstance(val, pd.Timestamp):
if val.tz is not None:
raise TypeError(
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"Cannot covert a timezone-aware timestamp to"
" timezone-naive scalar. For that, "
"use `tz_localize`."
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)
val = val.to_datetime64()
elif isinstance(val, pd.Timedelta):
val = val.to_timedelta64()
elif isinstance(val, datetime.datetime):
val = np.datetime64(val)
elif isinstance(val, datetime.timedelta):
val = np.timedelta64(val)

val = _maybe_convert_to_default_type(
cudf.api.types.pandas_dtype(type(val))
Expand Down