DEPR: enforce deprecation of DTI/TDI unused keywords (pandas-dev#58003)

* DEPR: enforce deprecation of DTI/TDI unused keywords

* update docstring

* un-xfail (i think) code check

Author: jbrockmendel

ci/code_checks.sh

@@ -504,7 +504,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timedelta.to_timedelta64 SA01" \
         -i "pandas.Timedelta.total_seconds SA01" \
         -i "pandas.Timedelta.view SA01" \
-        -i "pandas.TimedeltaIndex PR01" \
         -i "pandas.TimedeltaIndex.as_unit RT03,SA01" \
         -i "pandas.TimedeltaIndex.ceil SA01" \
         -i "pandas.TimedeltaIndex.components SA01" \

doc/source/whatsnew/v3.0.0.rst

@@ -197,6 +197,8 @@ Removal of prior version deprecations/changes
 - :meth:`SeriesGroupBy.agg` no longer pins the name of the group to the input passed to the provided ``func`` (:issue:`51703`)
 - All arguments except ``name`` in :meth:`Index.rename` are now keyword only (:issue:`56493`)
 - All arguments except the first ``path``-like argument in IO writers are now keyword only (:issue:`54229`)
+- Removed the "closed" and "normalize" keywords in :meth:`DatetimeIndex.__new__` (:issue:`52628`)
+- Removed the "closed" and "unit" keywords in :meth:`TimedeltaIndex.__new__` (:issue:`52628`, :issue:`55499`)
 - All arguments in :meth:`Index.sort_values` are now keyword only (:issue:`56493`)
 - All arguments in :meth:`Series.to_dict` are now keyword only (:issue:`56493`)
 - Changed the default value of ``observed`` in :meth:`DataFrame.groupby` and :meth:`Series.groupby` to ``True`` (:issue:`51811`)

pandas/core/indexes/datetimes.py

@@ -28,7 +28,6 @@
     cache_readonly,
     doc,
 )
-from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import is_scalar
 from pandas.core.dtypes.dtypes import DatetimeTZDtype
@@ -150,17 +149,6 @@ class DatetimeIndex(DatetimeTimedeltaMixin):
         inferred frequency upon creation.
     tz : pytz.timezone or dateutil.tz.tzfile or datetime.tzinfo or str
         Set the Timezone of the data.
-    normalize : bool, default False
-        Normalize start/end dates to midnight before generating date range.
-
-        .. deprecated:: 2.1.0
-
-    closed : {'left', 'right'}, optional
-        Set whether to include `start` and `end` that are on the
-        boundary. The default includes boundary points on either end.
-
-        .. deprecated:: 2.1.0
-
     ambiguous : 'infer', bool-ndarray, 'NaT', default 'raise'
         When clocks moved backward due to DST, ambiguous times may arise.
         For example in Central European Time (UTC+01), when going from 03:00
@@ -322,32 +310,13 @@ def __new__(
         data=None,
         freq: Frequency | lib.NoDefault = lib.no_default,
         tz=lib.no_default,
-        normalize: bool | lib.NoDefault = lib.no_default,
-        closed=lib.no_default,
         ambiguous: TimeAmbiguous = "raise",
         dayfirst: bool = False,
         yearfirst: bool = False,
         dtype: Dtype | None = None,
         copy: bool = False,
         name: Hashable | None = None,
     ) -> Self:
-        if closed is not lib.no_default:
-            # GH#52628
-            warnings.warn(
-                f"The 'closed' keyword in {cls.__name__} construction is "
-                "deprecated and will be removed in a future version.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        if normalize is not lib.no_default:
-            # GH#52628
-            warnings.warn(
-                f"The 'normalize' keyword in {cls.__name__} construction is "
-                "deprecated and will be removed in a future version.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-
         if is_scalar(data):
             cls._raise_scalar_data_error(data)
 

pandas/core/indexes/timedeltas.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 from typing import TYPE_CHECKING
-import warnings
 
 from pandas._libs import (
     index as libindex,
@@ -14,8 +13,6 @@
     Timedelta,
     to_offset,
 )
-from pandas._libs.tslibs.timedeltas import disallow_ambiguous_unit
-from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_scalar,
@@ -63,12 +60,6 @@ class TimedeltaIndex(DatetimeTimedeltaMixin):
     ----------
     data : array-like (1-dimensional), optional
         Optional timedelta-like data to construct index with.
-    unit : {'D', 'h', 'm', 's', 'ms', 'us', 'ns'}, optional
-        The unit of ``data``.
-
-        .. deprecated:: 2.2.0
-         Use ``pd.to_timedelta`` instead.
-
     freq : str or pandas offset object, optional
         One of pandas date offset strings or corresponding objects. The string
         ``'infer'`` can be passed in order to set the frequency of the index as
@@ -151,40 +142,16 @@ def _resolution_obj(self) -> Resolution | None:  # type: ignore[override]
     def __new__(
         cls,
         data=None,
-        unit=lib.no_default,
         freq=lib.no_default,
-        closed=lib.no_default,
         dtype=None,
         copy: bool = False,
         name=None,
     ):
-        if closed is not lib.no_default:
-            # GH#52628
-            warnings.warn(
-                f"The 'closed' keyword in {cls.__name__} construction is "
-                "deprecated and will be removed in a future version.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-
-        if unit is not lib.no_default:
-            # GH#55499
-            warnings.warn(
-                f"The 'unit' keyword in {cls.__name__} construction is "
-                "deprecated and will be removed in a future version. "
-                "Use pd.to_timedelta instead.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        else:
-            unit = None
-
         name = maybe_extract_name(name, data, cls)
 
         if is_scalar(data):
             cls._raise_scalar_data_error(data)
 
-        disallow_ambiguous_unit(unit)
         if dtype is not None:
             dtype = pandas_dtype(dtype)
 
@@ -211,7 +178,7 @@ def __new__(
         # - Cases checked above all return/raise before reaching here - #
 
         tdarr = TimedeltaArray._from_sequence_not_strict(
-            data, freq=freq, unit=unit, dtype=dtype, copy=copy
+            data, freq=freq, unit=None, dtype=dtype, copy=copy
         )
         refs = None
         if not copy and isinstance(data, (ABCSeries, Index)):

pandas/tests/indexes/datetimes/test_constructors.py

@@ -35,18 +35,6 @@
 
 
 class TestDatetimeIndex:
-    def test_closed_deprecated(self):
-        # GH#52628
-        msg = "The 'closed' keyword"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            DatetimeIndex([], closed=True)
-
-    def test_normalize_deprecated(self):
-        # GH#52628
-        msg = "The 'normalize' keyword"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            DatetimeIndex([], normalize=True)
-
     def test_from_dt64_unsupported_unit(self):
         # GH#49292
         val = np.datetime64(1, "D")

pandas/tests/indexes/timedeltas/test_constructors.py

@@ -15,12 +15,6 @@
 
 
 class TestTimedeltaIndex:
-    def test_closed_deprecated(self):
-        # GH#52628
-        msg = "The 'closed' keyword"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            TimedeltaIndex([], closed=True)
-
     def test_array_of_dt64_nat_raises(self):
         # GH#39462
         nat = np.datetime64("NaT", "ns")
@@ -36,14 +30,6 @@ def test_array_of_dt64_nat_raises(self):
         with pytest.raises(TypeError, match=msg):
             to_timedelta(arr)
 
-    @pytest.mark.parametrize("unit", ["Y", "y", "M"])
-    def test_unit_m_y_raises(self, unit):
-        msg = "Units 'M', 'Y', and 'y' are no longer supported"
-        depr_msg = "The 'unit' keyword in TimedeltaIndex construction is deprecated"
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match=depr_msg):
-                TimedeltaIndex([1, 3, 7], unit)
-
     def test_int64_nocopy(self):
         # GH#23539 check that a copy isn't made when we pass int64 data
         #  and copy=False
@@ -138,9 +124,6 @@ def test_construction_base_constructor(self):
         tm.assert_index_equal(pd.Index(arr), TimedeltaIndex(arr))
         tm.assert_index_equal(pd.Index(np.array(arr)), TimedeltaIndex(np.array(arr)))
 
-    @pytest.mark.filterwarnings(
-        "ignore:The 'unit' keyword in TimedeltaIndex construction:FutureWarning"
-    )
     def test_constructor(self):
         expected = TimedeltaIndex(
             [
@@ -162,22 +145,6 @@ def test_constructor(self):
         )
         tm.assert_index_equal(result, expected)
 
-        expected = TimedeltaIndex(
-            ["0 days 00:00:00", "0 days 00:00:01", "0 days 00:00:02"]
-        )
-        result = TimedeltaIndex(range(3), unit="s")
-        tm.assert_index_equal(result, expected)
-        expected = TimedeltaIndex(
-            ["0 days 00:00:00", "0 days 00:00:05", "0 days 00:00:09"]
-        )
-        result = TimedeltaIndex([0, 5, 9], unit="s")
-        tm.assert_index_equal(result, expected)
-        expected = TimedeltaIndex(
-            ["0 days 00:00:00.400", "0 days 00:00:00.450", "0 days 00:00:01.200"]
-        )
-        result = TimedeltaIndex([400, 450, 1200], unit="ms")
-        tm.assert_index_equal(result, expected)
-
     def test_constructor_iso(self):
         # GH #21877
         expected = timedelta_range("1s", periods=9, freq="s")

pandas/tests/scalar/timedelta/test_constructors.py

@@ -126,30 +126,26 @@ def test_unit_parser(self, unit, np_unit, wrapper):
         )
         # TODO(2.0): the desired output dtype may have non-nano resolution
 
-        msg = "The 'unit' keyword in TimedeltaIndex construction is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = to_timedelta(wrapper(range(5)), unit=unit)
-            tm.assert_index_equal(result, expected)
-            result = TimedeltaIndex(wrapper(range(5)), unit=unit)
-            tm.assert_index_equal(result, expected)
-
-            str_repr = [f"{x}{unit}" for x in np.arange(5)]
-            result = to_timedelta(wrapper(str_repr))
-            tm.assert_index_equal(result, expected)
-            result = to_timedelta(wrapper(str_repr))
-            tm.assert_index_equal(result, expected)
-
-            # scalar
-            expected = Timedelta(np.timedelta64(2, np_unit).astype("timedelta64[ns]"))
-            result = to_timedelta(2, unit=unit)
-            assert result == expected
-            result = Timedelta(2, unit=unit)
-            assert result == expected
-
-            result = to_timedelta(f"2{unit}")
-            assert result == expected
-            result = Timedelta(f"2{unit}")
-            assert result == expected
+        result = to_timedelta(wrapper(range(5)), unit=unit)
+        tm.assert_index_equal(result, expected)
+
+        str_repr = [f"{x}{unit}" for x in np.arange(5)]
+        result = to_timedelta(wrapper(str_repr))
+        tm.assert_index_equal(result, expected)
+        result = to_timedelta(wrapper(str_repr))
+        tm.assert_index_equal(result, expected)
+
+        # scalar
+        expected = Timedelta(np.timedelta64(2, np_unit).astype("timedelta64[ns]"))
+        result = to_timedelta(2, unit=unit)
+        assert result == expected
+        result = Timedelta(2, unit=unit)
+        assert result == expected
+
+        result = to_timedelta(f"2{unit}")
+        assert result == expected
+        result = Timedelta(f"2{unit}")
+        assert result == expected
 
     @pytest.mark.parametrize("unit", ["T", "t", "L", "l", "U", "u", "N", "n"])
     def test_unit_T_L_N_U_raises(self, unit):