DEPR: Enforce datetimelike deprecations (pandas-dev#57999)

* DEPR: Enforce datetimelike deprecations

* update message in tests

* update overload

* mypy fixup

* post-merge fixup

* update asvs

* Update doc/source/whatsnew/v3.0.0.rst

---------

Co-authored-by: Matthew Roeschke <[email protected]>

Author: jbrockmendel

asv_bench/benchmarks/categoricals.py

@@ -24,7 +24,7 @@ def setup(self):
         self.codes = np.tile(range(len(self.categories)), N)
 
         self.datetimes = pd.Series(
-            pd.date_range("1995-01-01 00:00:00", periods=N / 10, freq="s")
+            pd.date_range("1995-01-01 00:00:00", periods=N // 10, freq="s")
         )
         self.datetimes_with_nat = self.datetimes.copy()
         self.datetimes_with_nat.iloc[-1] = pd.NaT

asv_bench/benchmarks/timeseries.py

@@ -29,7 +29,7 @@ def setup(self, index_type):
             "dst": date_range(
                 start="10/29/2000 1:00:00", end="10/29/2000 1:59:59", freq="s"
             ),
-            "repeated": date_range(start="2000", periods=N / 10, freq="s").repeat(10),
+            "repeated": date_range(start="2000", periods=N // 10, freq="s").repeat(10),
             "tz_aware": date_range(start="2000", periods=N, freq="s", tz="US/Eastern"),
             "tz_local": date_range(
                 start="2000", periods=N, freq="s", tz=dateutil.tz.tzlocal()

doc/source/whatsnew/v3.0.0.rst

@@ -222,7 +222,8 @@ Removal of prior version deprecations/changes
 - 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`)
 - Enforce deprecation in :func:`testing.assert_series_equal` and :func:`testing.assert_frame_equal` with object dtype and mismatched null-like values, which are now considered not-equal (:issue:`18463`)
-- Enforced deprecation ``all`` and ``any`` reductions with ``datetime64`` and :class:`DatetimeTZDtype` dtypes (:issue:`58029`)
+- Enforced deprecation ``all`` and ``any`` reductions with ``datetime64``, :class:`DatetimeTZDtype`, and :class:`PeriodDtype` dtypes (:issue:`58029`)
+- Enforced deprecation disallowing ``float`` "periods" in :func:`date_range`, :func:`period_range`, :func:`timedelta_range`, :func:`interval_range`,  (:issue:`56036`)
 - Enforced deprecation disallowing parsing datetimes with mixed time zones unless user passes ``utc=True`` to :func:`to_datetime` (:issue:`57275`)
 - Enforced deprecation in :meth:`Series.value_counts` and :meth:`Index.value_counts` with object dtype performing dtype inference on the ``.index`` of the result (:issue:`56161`)
 - Enforced deprecation of :meth:`.DataFrameGroupBy.get_group` and :meth:`.SeriesGroupBy.get_group` allowing the ``name`` argument to be a non-tuple when grouping by a list of length 1 (:issue:`54155`)

pandas/core/arrays/datetimelike.py

@@ -1661,20 +1661,24 @@ def _groupby_op(
         dtype = self.dtype
         if dtype.kind == "M":
             # Adding/multiplying datetimes is not valid
-            if how in ["any", "all", "sum", "prod", "cumsum", "cumprod", "var", "skew"]:
+            if how in ["sum", "prod", "cumsum", "cumprod", "var", "skew"]:
                 raise TypeError(f"datetime64 type does not support operation '{how}'")
+            if how in ["any", "all"]:
+                # GH#34479
+                raise TypeError(
+                    f"'{how}' with datetime64 dtypes is no longer supported. "
+                    f"Use (obj != pd.Timestamp(0)).{how}() instead."
+                )
 
         elif isinstance(dtype, PeriodDtype):
             # Adding/multiplying Periods is not valid
             if how in ["sum", "prod", "cumsum", "cumprod", "var", "skew"]:
                 raise TypeError(f"Period type does not support {how} operations")
             if how in ["any", "all"]:
                 # GH#34479
-                warnings.warn(
-                    f"'{how}' with PeriodDtype is deprecated and will raise in a "
-                    f"future version. Use (obj != pd.Period(0, freq)).{how}() instead.",
-                    FutureWarning,
-                    stacklevel=find_stack_level(),
+                raise TypeError(
+                    f"'{how}' with PeriodDtype is no longer supported. "
+                    f"Use (obj != pd.Period(0, freq)).{how}() instead."
                 )
         else:
             # timedeltas we can add but not multiply
@@ -2424,17 +2428,17 @@ def validate_periods(periods: None) -> None: ...
 
 
 @overload
-def validate_periods(periods: int | float) -> int: ...
+def validate_periods(periods: int) -> int: ...
 
 
-def validate_periods(periods: int | float | None) -> int | None:
+def validate_periods(periods: int | None) -> int | None:
     """
     If a `periods` argument is passed to the Datetime/Timedelta Array/Index
     constructor, cast it to an integer.
 
     Parameters
     ----------
-    periods : None, float, int
+    periods : None, int
 
     Returns
     -------
@@ -2443,22 +2447,13 @@ def validate_periods(periods: int | float | None) -> int | None:
     Raises
     ------
     TypeError
-        if periods is None, float, or int
+        if periods is not None or int
     """
-    if periods is not None:
-        if lib.is_float(periods):
-            warnings.warn(
-                # GH#56036
-                "Non-integer 'periods' in pd.date_range, pd.timedelta_range, "
-                "pd.period_range, and pd.interval_range are deprecated and "
-                "will raise in a future version.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-            periods = int(periods)
-        elif not lib.is_integer(periods):
-            raise TypeError(f"periods must be a number, got {periods}")
-    return periods
+    if periods is not None and not lib.is_integer(periods):
+        raise TypeError(f"periods must be an integer, got {periods}")
+    # error: Incompatible return value type (got "int | integer[Any] | None",
+    # expected "int | None")
+    return periods  # type: ignore[return-value]
 
 
 def _validate_inferred_freq(

pandas/tests/groupby/test_raises.py

@@ -241,8 +241,8 @@ def test_groupby_raises_datetime(
             return
 
     klass, msg = {
-        "all": (TypeError, "datetime64 type does not support operation 'all'"),
-        "any": (TypeError, "datetime64 type does not support operation 'any'"),
+        "all": (TypeError, "'all' with datetime64 dtypes is no longer supported"),
+        "any": (TypeError, "'any' with datetime64 dtypes is no longer supported"),
         "bfill": (None, ""),
         "corrwith": (TypeError, "cannot perform __mul__ with this index type"),
         "count": (None, ""),

pandas/tests/indexes/datetimes/test_date_range.py

@@ -135,16 +135,14 @@ def test_date_range_name(self):
         assert idx.name == "TEST"
 
     def test_date_range_invalid_periods(self):
-        msg = "periods must be a number, got foo"
+        msg = "periods must be an integer, got foo"
         with pytest.raises(TypeError, match=msg):
             date_range(start="1/1/2000", periods="foo", freq="D")
 
     def test_date_range_fractional_period(self):
-        msg = "Non-integer 'periods' in pd.date_range, pd.timedelta_range"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            rng = date_range("1/1/2000", periods=10.5)
-        exp = date_range("1/1/2000", periods=10)
-        tm.assert_index_equal(rng, exp)
+        msg = "periods must be an integer"
+        with pytest.raises(TypeError, match=msg):
+            date_range("1/1/2000", periods=10.5)
 
     @pytest.mark.parametrize(
         "freq,freq_depr",
@@ -1042,7 +1040,7 @@ def test_constructor(self):
         bdate_range(START, periods=20, freq=BDay())
         bdate_range(end=START, periods=20, freq=BDay())
 
-        msg = "periods must be a number, got B"
+        msg = "periods must be an integer, got B"
         with pytest.raises(TypeError, match=msg):
             date_range("2011-1-1", "2012-1-1", "B")
 
@@ -1120,7 +1118,7 @@ def test_constructor(self):
         bdate_range(START, periods=20, freq=CDay())
         bdate_range(end=START, periods=20, freq=CDay())
 
-        msg = "periods must be a number, got C"
+        msg = "periods must be an integer, got C"
         with pytest.raises(TypeError, match=msg):
             date_range("2011-1-1", "2012-1-1", "C")
 

pandas/tests/indexes/interval/test_interval_range.py

@@ -236,11 +236,10 @@ def test_interval_dtype(self, start, end, expected):
 
     def test_interval_range_fractional_period(self):
         # float value for periods
-        expected = interval_range(start=0, periods=10)
-        msg = "Non-integer 'periods' in pd.date_range, .* pd.interval_range"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = interval_range(start=0, periods=10.5)
-        tm.assert_index_equal(result, expected)
+        msg = "periods must be an integer, got 10.5"
+        ts = Timestamp("2024-03-25")
+        with pytest.raises(TypeError, match=msg):
+            interval_range(ts, periods=10.5)
 
     def test_constructor_coverage(self):
         # equivalent timestamp-like start/end
@@ -340,7 +339,7 @@ def test_errors(self):
             interval_range(start=Timedelta("1 day"), end=Timedelta("10 days"), freq=2)
 
         # invalid periods
-        msg = "periods must be a number, got foo"
+        msg = "periods must be an integer, got foo"
         with pytest.raises(TypeError, match=msg):
             interval_range(start=0, periods="foo")
 

pandas/tests/indexes/period/test_constructors.py

@@ -196,11 +196,9 @@ def test_constructor_invalid_quarters(self):
             )
 
     def test_period_range_fractional_period(self):
-        msg = "Non-integer 'periods' in pd.date_range, pd.timedelta_range"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = period_range("2007-01", periods=10.5, freq="M")
-        exp = period_range("2007-01", periods=10, freq="M")
-        tm.assert_index_equal(result, exp)
+        msg = "periods must be an integer, got 10.5"
+        with pytest.raises(TypeError, match=msg):
+            period_range("2007-01", periods=10.5, freq="M")
 
     def test_constructor_with_without_freq(self):
         # GH53687

pandas/tests/indexes/period/test_period_range.py

@@ -70,7 +70,7 @@ def test_start_end_non_nat(self):
 
     def test_periods_requires_integer(self):
         # invalid periods param
-        msg = "periods must be a number, got foo"
+        msg = "periods must be an integer, got foo"
         with pytest.raises(TypeError, match=msg):
             period_range(start="2017Q1", periods="foo")
 

pandas/tests/indexes/timedeltas/test_constructors.py

@@ -143,14 +143,12 @@ def test_constructor_iso(self):
         tm.assert_index_equal(result, expected)
 
     def test_timedelta_range_fractional_period(self):
-        msg = "Non-integer 'periods' in pd.date_range, pd.timedelta_range"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            rng = timedelta_range("1 days", periods=10.5)
-        exp = timedelta_range("1 days", periods=10)
-        tm.assert_index_equal(rng, exp)
+        msg = "periods must be an integer"
+        with pytest.raises(TypeError, match=msg):
+            timedelta_range("1 days", periods=10.5)
 
     def test_constructor_coverage(self):
-        msg = "periods must be a number, got foo"
+        msg = "periods must be an integer, got foo"
         with pytest.raises(TypeError, match=msg):
             timedelta_range(start="1 days", periods="foo", freq="D")