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remove np.datetime64 from S1, make adding two TimestampSeries fail #527

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Merged
merged 1 commit into from
Feb 7, 2023
Merged

remove np.datetime64 from S1, make adding two TimestampSeries fail #527

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4 changes: 2 additions & 2 deletions pandas-stubs/_libs/tslibs/timestamps.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -217,15 +217,15 @@ class Timestamp(datetime):
@overload
def __eq__(self, other: Timestamp | datetime | np.datetime64) -> bool: ... # type: ignore[misc] # pyright: ignore[reportOverlappingOverload]
@overload
def __eq__(self, other: TimestampSeries | Series[np.datetime64]) -> Series[bool]: ... # type: ignore[misc]
def __eq__(self, other: TimestampSeries) -> Series[bool]: ... # type: ignore[misc]
@overload
def __eq__(self, other: npt.NDArray[np.datetime64] | Index) -> np_ndarray_bool: ... # type: ignore[misc]
@overload
def __eq__(self, other: object) -> Literal[False]: ...
@overload
def __ne__(self, other: Timestamp | datetime | np.datetime64) -> bool: ... # type: ignore[misc] # pyright: ignore[reportOverlappingOverload]
@overload
def __ne__(self, other: TimestampSeries | Series[np.datetime64]) -> Series[bool]: ... # type: ignore[misc]
def __ne__(self, other: TimestampSeries) -> Series[bool]: ... # type: ignore[misc]
@overload
def __ne__(self, other: npt.NDArray[np.datetime64] | Index) -> np_ndarray_bool: ... # type: ignore[misc]
@overload
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1 change: 0 additions & 1 deletion pandas-stubs/_typing.pyi
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Expand Up @@ -207,7 +207,6 @@ S1 = TypeVar(
complex,
Timestamp,
Timedelta,
np.datetime64,
Period,
Interval[int],
Interval[float],
Expand Down
12 changes: 11 additions & 1 deletion pandas-stubs/core/series.pyi
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Expand Up @@ -178,7 +178,6 @@ class _LocIndexerSeries(_LocIndexer, Generic[S1]):
) -> None: ...

class Series(IndexOpsMixin, NDFrame, Generic[S1]):

_ListLike: TypeAlias = Union[ArrayLike, dict[_str, np.ndarray], list, tuple, Index]
__hash__: ClassVar[None]

Expand All @@ -193,6 +192,16 @@ class Series(IndexOpsMixin, NDFrame, Generic[S1]):
fastpath: bool = ...,
) -> TimestampSeries: ...
@overload
def __new__(
cls,
data: _ListLike,
dtype: Literal["datetime64[ns]"],
index: Axes | None = ...,
name: Hashable | None = ...,
copy: bool = ...,
fastpath: bool = ...,
) -> TimestampSeries: ...
@overload
def __new__(
cls,
data: PeriodIndex,
Expand Down Expand Up @@ -1800,6 +1809,7 @@ class TimestampSeries(Series[Timestamp]):
@property
def dt(self) -> TimestampProperties: ... # type: ignore[override]
def __add__(self, other: TimedeltaSeries | np.timedelta64) -> TimestampSeries: ... # type: ignore[override]
def __radd__(self, other: TimedeltaSeries | np.timedelta64) -> TimestampSeries: ... # type: ignore[override]
def __mul__(self, other: int | float | Series[int] | Series[float] | Sequence[int | float]) -> TimestampSeries: ... # type: ignore[override]
def __truediv__(self, other: int | float | Series[int] | Series[float] | Sequence[int | float]) -> TimestampSeries: ... # type: ignore[override]
def mean( # type: ignore[override]
Expand Down
7 changes: 1 addition & 6 deletions tests/test_scalars.py
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Expand Up @@ -44,7 +44,6 @@

from pandas._typing import np_ndarray_bool
else:

np_ndarray_bool = npt.NDArray[np.bool_]
TimedeltaSeries: TypeAlias = pd.Series
TimestampSeries: TypeAlias = pd.Series
Expand Down Expand Up @@ -386,7 +385,6 @@ def test_interval_cmp():


def test_timedelta_construction() -> None:

check(assert_type(pd.Timedelta(1, "H"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.Timedelta(1, "T"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.Timedelta(1, "S"), pd.Timedelta), pd.Timedelta)
Expand Down Expand Up @@ -1078,7 +1076,6 @@ def test_timedelta_cmp_rhs() -> None:


def test_timestamp_construction() -> None:

check(assert_type(pd.Timestamp("2000-1-1"), pd.Timestamp), pd.Timestamp)
check(
assert_type(pd.Timestamp("2000-1-1", tz="US/Pacific"), pd.Timestamp),
Expand Down Expand Up @@ -1256,9 +1253,7 @@ def test_timestamp_cmp() -> None:
c_dt_datetime = dt.datetime(year=2000, month=1, day=1)
c_datetimeindex = pd.DatetimeIndex(["2000-1-1"])
c_np_ndarray_dt64 = np_dt64_arr
c_series_dt64: pd.Series[np.datetime64] = pd.Series(
[1, 2, 3], dtype="datetime64[ns]"
)
c_series_dt64: TimestampSeries = pd.Series([1, 2, 3], dtype="datetime64[ns]")
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Is it possible to specify dtype=np.datetime64?

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No. This is consistent with numpy.

>>> import pandas as pd
>>> import numpy as np
>>> pd.Series([1,2,3], dtype=np.datetime64)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Anaconda3\envs\pandasstubs\lib\site-packages\pandas\core\series.py", line 470, in __init__
    data = sanitize_array(data, index, dtype, copy)
  File "C:\Anaconda3\envs\pandasstubs\lib\site-packages\pandas\core\construction.py", line 622, in sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
  File "C:\Anaconda3\envs\pandasstubs\lib\site-packages\pandas\core\construction.py", line 827, in _try_cast
    return maybe_cast_to_datetime(arr, dtype)
  File "C:\Anaconda3\envs\pandasstubs\lib\site-packages\pandas\core\dtypes\cast.py", line 1321, in maybe_cast_to_datetime
    dtype = _ensure_nanosecond_dtype(dtype)
  File "C:\Anaconda3\envs\pandasstubs\lib\site-packages\pandas\core\dtypes\cast.py", line 1468, in _ensure_nanosecond_dtype
    raise ValueError(msg)
ValueError: The 'datetime64' dtype has no unit. Please pass in 'datetime64[ns]' instead.

c_series_timestamp = pd.Series(pd.DatetimeIndex(["2000-1-1"]))
check(assert_type(c_series_timestamp, TimestampSeries), pd.Series, pd.Timestamp)
# Use xor to ensure one is True and the other is False
Expand Down
2 changes: 1 addition & 1 deletion tests/test_timefuncs.py
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Expand Up @@ -259,7 +259,7 @@ def test_fail_on_adding_two_timestamps() -> None:
s1 = pd.Series(pd.to_datetime(["2022-05-01", "2022-06-01"]))
s2 = pd.Series(pd.to_datetime(["2022-05-15", "2022-06-15"]))
if TYPE_CHECKING_INVALID_USAGE:
ssum: pd.Series = s1 + s2 # type: ignore[operator]
ssum: pd.Series = s1 + s2 # type: ignore[operator] # pyright: ignore[reportGeneralTypeIssues]
ts = pd.Timestamp("2022-06-30")
tsum: pd.Series = s1 + ts # type: ignore[operator] # pyright: ignore[reportGeneralTypeIssues]

Expand Down