to use validate_inclusive in util

pandas/core/arrays/datetimelike.py

@@ -1823,71 +1823,6 @@ def validate_periods(periods):
     return periods
 
 
-def validate_inclusiveness(inclusive):
-    """
-    Check that the `inclusive` argument is among {"both", "neither", "left", "right"}.
-
-    Parameters
-    ----------
-    inclusive : {"both", "neither", "left", "right"}
-
-    Returns
-    -------
-    left_inclusive : bool
-    right_inclusive : bool
-
-    Raises
-    ------
-    ValueError : if argument is not among valid values
-    """
-    left_right_inclusive: tuple[bool, bool] | None = {
-        "both": (True, True),
-        "left": (True, False),
-        "right": (False, True),
-        "neither": (False, False),
-    }.get(inclusive)
-
-    if left_right_inclusive is None:
-        raise ValueError(
-            "Inclusive has to be either 'both', 'neither', 'left', 'right'"
-        )
-    left_inclusive, right_inclusive = left_right_inclusive
-    return left_inclusive, right_inclusive
-
-
-def validate_endpoints(closed):
-    """
-    Check that the `closed` argument is among [None, "left", "right"]
-
-    Parameters
-    ----------
-    closed : {None, "left", "right"}
-
-    Returns
-    -------
-    left_closed : bool
-    right_closed : bool
-
-    Raises
-    ------
-    ValueError : if argument is not among valid values
-    """
-    left_closed = False
-    right_closed = False
-
-    if closed is None:
-        left_closed = True
-        right_closed = True
-    elif closed == "left":
-        left_closed = True
-    elif closed == "right":
-        right_closed = True
-    else:
-        raise ValueError("Closed has to be either 'left', 'right' or None")
-
-    return left_closed, right_closed
-
-
 def validate_inferred_freq(freq, inferred_freq, freq_infer):
     """
     If the user passes a freq and another freq is inferred from passed data,

pandas/core/arrays/datetimes.py

@@ -39,7 +39,7 @@
 )
 from pandas._typing import npt
 from pandas.errors import PerformanceWarning
-from pandas.util._validators import validate_endpoints
+from pandas.util._validators import validate_inclusive
 
 from pandas.core.dtypes.cast import astype_dt64_to_dt64tz
 from pandas.core.dtypes.common import (
@@ -417,7 +417,7 @@ def _generate_range(
         if start is NaT or end is NaT:
             raise ValueError("Neither `start` nor `end` can be NaT")
 
-        left_inclusive, right_inclusive = dtl.validate_inclusiveness(inclusive)
+        left_inclusive, right_inclusive = validate_inclusive(inclusive)
         start, end, _normalized = _maybe_normalize_endpoints(start, end, normalize)
         tz = _infer_tz_from_endpoints(start, end, tz)