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GH1327 Add overloead for date_range and timedelta_range #1333

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merged 6 commits into from
Aug 22, 2025
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GH1327 Add overloead for date_range and timedelta_range #1333

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GH1327 Add overloead for date_range and timedelta_range
loicdiridollou Aug 20, 2025
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GH1327 Fix CI
loicdiridollou Aug 20, 2025
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GH1327 PR feedback
loicdiridollou Aug 20, 2025
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Merge branch 'main' into gh1327_date_timedelta_range
loicdiridollou Aug 20, 2025
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GH1327 Revert changes to start clean
loicdiridollou Aug 21, 2025
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45 changes: 41 additions & 4 deletions pandas-stubs/core/indexes/datetimes.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -102,11 +102,48 @@ class DatetimeIndex(
self, periods: int = 1, freq: DateOffset | Timedelta | str | None = None
) -> Self: ...

@overload
def date_range(
start: str | DateAndDatetimeLike | None = None,
end: str | DateAndDatetimeLike | None = None,
periods: int | None = None,
freq: str | timedelta | Timedelta | BaseOffset = "D",
*,
end: str | DateAndDatetimeLike = ...,
periods: int = ...,
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I think this would allow pd.date_range() to be accepted.

The error message is " Of the four parameters: start, end, periods, and freq, exactly three must be specified".

So if you want this to work, you have to have overloads where 3 are required. You can't have = ... on any of them (or default values either), because that means the argument is optional.

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The point where I am a bit unsure is that most of the usage I have seen it just about passing start and end, freq is often left alone so the usage does not reflect the docs.
Should we force the user to use three out of the four or allow only two?

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So I think the docs and error message are a bit misleading.

You'll need to do a test to determine when 2 are allowed. I think the rule is as follows:

  • Whether or not freq is specified, you need at least 2 out of the 3 of start, end, periods

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If I look at the docs, they don't even use three exactly, when looking at the code they are using the fact that freq defaults to None but is then replaced by D for day.
https://pandas.pydata.org/docs/dev/reference/api/pandas.timedelta_range.html#pandas.timedelta_range

See https://github.com/pandas-dev/pandas/blob/78ec27668163808b3488da6ed2c64d0b8e9bfbc8/pandas/core/indexes/timedeltas.py#L330-L331 for the code where they change freq=None to freq="D"
Should we force the user to do 3 args even if the docs example only uses 2.
Happy to open a PR in the pandas repo to ask for clarification.

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Sorry took a bit of time to find all the docs and you had answered before.
Let me setup a quick test to validate that we need two out of three of start, end, and periods.

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Seems like the freq is indeed the argument that does not need to be passed (it is also the last one in the order).
I think the correct way to type hint is like you said forcing 2 out of the 3 with freq being an str | None = ... without the need to be passed when you pass two other. I have also tried passing four and that works as long as one of the three is None (yet it would be a strange use case of passing None since it is a default).

>>> pd.date_range("2023-04-05", "2023-04-07", freq="D")
DatetimeIndex(['2023-04-05', '2023-04-06', '2023-04-07'], dtype='datetime64[ns]', freq='D')
>>> pd.date_range("2023-04-05", "2023-04-07")
DatetimeIndex(['2023-04-05', '2023-04-06', '2023-04-07'], dtype='datetime64[ns]', freq='D')

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pandas-dev/pandas#62161

I have asked for clarifications.

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I have read and reread the docs, it is a bit confusing at first glance but I will add all the tests for it.

freq: str | timedelta | Timedelta | BaseOffset | None = None,
tz: TimeZones = None,
normalize: bool = False,
name: Hashable | None = None,
inclusive: IntervalClosedType = "both",
unit: TimeUnit | None = None,
) -> DatetimeIndex: ...
@overload
def date_range(
start: str | DateAndDatetimeLike,
*,
periods: int = ...,
freq: str | timedelta | Timedelta | BaseOffset | None = None,
tz: TimeZones = None,
normalize: bool = False,
name: Hashable | None = None,
inclusive: IntervalClosedType = "both",
unit: TimeUnit | None = None,
) -> DatetimeIndex: ...
@overload
def date_range(
start: str | DateAndDatetimeLike = ...,
end: str | DateAndDatetimeLike = ...,
*,
freq: str | timedelta | Timedelta | BaseOffset | None = None,
tz: TimeZones = None,
normalize: bool = False,
name: Hashable | None = None,
inclusive: IntervalClosedType = "both",
unit: TimeUnit | None = None,
) -> DatetimeIndex: ...
@overload
def date_range(
start: str | DateAndDatetimeLike = ...,
end: str | DateAndDatetimeLike = ...,
periods: int = ...,
*,
tz: TimeZones = None,
normalize: bool = False,
name: Hashable | None = None,
Expand Down
46 changes: 43 additions & 3 deletions pandas-stubs/core/indexes/timedeltas.pyi
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Expand Up @@ -79,13 +79,53 @@ class TimedeltaIndex(
def to_series(self, index=..., name: Hashable = ...) -> TimedeltaSeries: ...
def shift(self, periods: int = 1, freq=...) -> Self: ...

@overload
def timedelta_range(
start: TimedeltaConvertibleTypes | None = None,
end: TimedeltaConvertibleTypes | None = None,
periods: int | None = None,
start: TimedeltaConvertibleTypes = ...,
end: TimedeltaConvertibleTypes = ...,
periods: int = ...,
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same issue here as with date_range()

*,
name: Hashable | None = None,
closed: Literal["left", "right"] | None = None,
unit: None | str = ...,
) -> TimedeltaIndex: ...
@overload
def timedelta_range(
start: TimedeltaConvertibleTypes = ...,
periods: int = ...,
freq: None = None,
name: Hashable | None = None,
closed: Literal["left", "right"] | None = None,
*,
unit: None | str = ...,
) -> TimedeltaIndex: ...
@overload
def timedelta_range(
start: TimedeltaConvertibleTypes = ...,
*,
periods: int = ...,
freq: str | DateOffset | Timedelta | dt.timedelta | None = None,
name: Hashable | None = None,
closed: Literal["left", "right"] | None = None,
unit: None | str = ...,
) -> TimedeltaIndex: ...
@overload
def timedelta_range(
start: TimedeltaConvertibleTypes = ...,
end: TimedeltaConvertibleTypes = ...,
*,
freq: str | DateOffset | Timedelta | dt.timedelta | None = None,
name: Hashable | None = None,
closed: Literal["left", "right"] | None = None,
unit: None | str = ...,
) -> TimedeltaIndex: ...
@overload
def timedelta_range(
*,
end: TimedeltaConvertibleTypes,
periods: int,
freq: str | DateOffset | Timedelta | dt.timedelta | None = None,
name: Hashable | None = None,
closed: Literal["left", "right"] | None = None,
unit: None | str = ...,
) -> TimedeltaIndex: ...
5 changes: 4 additions & 1 deletion tests/test_styler.py
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Expand Up @@ -22,6 +22,7 @@
from pandas._typing import Scalar

from tests import (
PD_LTE_23,
check,
ensure_clean,
)
Expand Down Expand Up @@ -141,7 +142,9 @@ def test_highlight_quantile() -> None:


def test_loader() -> None:
check(assert_type(DF.style.loader, PackageLoader), PackageLoader)
if PD_LTE_23:
# see GH62123 for pandas main repo, type changes in pandas 3.0
check(assert_type(DF.style.loader, PackageLoader), PackageLoader)


def test_pipe() -> None:
Expand Down
14 changes: 14 additions & 0 deletions tests/test_timefuncs.py
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Expand Up @@ -1563,6 +1563,13 @@ def test_timedelta_range() -> None:
pd.TimedeltaIndex,
)

if TYPE_CHECKING_INVALID_USAGE:
day1 = pd.Timedelta(1, unit="D")
day10 = pd.Timedelta(10, unit="D")
pd.timedelta_range(
day1, day10, 10, "D" # type: ignore[call-overload] # pyright: ignore[reportArgumentType]
)
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should add checks where only 0, 1 or 2 of the 3 arguments are specified, as that should fail as well.



def test_dateoffset_freqstr() -> None:
offset = DateOffset(minutes=10)
Expand Down Expand Up @@ -1743,6 +1750,13 @@ def test_creating_date_range() -> None:
dr = pd.date_range(start="2021-12-01", periods=24, freq="h")
check(assert_type(dr.strftime("%H:%M:%S"), pd.Index), pd.Index, str)

if TYPE_CHECKING_INVALID_USAGE:
day1 = pd.Timestamp("2023-04-03")
day10 = pd.Timedelta("2023-04-08")
pd.date_range(
day1, day10, 10, "D" # type: ignore[call-overload] # pyright: ignore[reportCallIssue]
)
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same comment - need to check that 0, 1 or 2 arguments specified causes a failure.



def test_timestamp_to_list_add() -> None:
# https://github.com/microsoft/python-type-stubs/issues/110
Expand Down
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