CLN: remove is_null_datetimelike

pandas/_libs/lib.pyx

@@ -1462,7 +1462,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
     for i in range(n):
         val = values[i]
 
-        # do not use is_null_datetimelike to keep
+        # do not use checknull to keep
         # np.datetime64('nat') and np.timedelta64('nat')
         if val is None or util.is_nan(val):
             pass

pandas/_libs/missing.pyx

@@ -21,7 +21,6 @@ from pandas._libs.tslibs.nattype cimport (
     c_NaT as NaT,
     checknull_with_nat,
     is_dt64nat,
-    is_null_datetimelike,
     is_td64nat,
 )
 from pandas._libs.tslibs.np_datetime cimport (
@@ -121,11 +120,20 @@ cpdef bint checknull(object val, bint inf_as_na=False):
     -------
     bool
     """
-    return (
-        val is C_NA
-        or is_null_datetimelike(val, inat_is_null=False, inf_as_na=inf_as_na)
-        or is_decimal_na(val)
-    )
+    if val is None or val is NaT or val is C_NA:
+        return True
+    elif util.is_float_object(val) or util.is_complex_object(val):
+        if val != val:
+            return True
+        elif inf_as_na:
+            return val == INF or val == NEGINF
+        return False
+    elif util.is_timedelta64_object(val):
+        return get_timedelta64_value(val) == NPY_NAT
+    elif util.is_datetime64_object(val):
+        return get_datetime64_value(val) == NPY_NAT
+    else:
+        return is_decimal_na(val)
 
 
 cdef inline bint is_decimal_na(object val):

pandas/_libs/tslibs/__init__.py

@@ -5,7 +5,6 @@
     "NaTType",
     "iNaT",
     "nat_strings",
-    "is_null_datetimelike",
     "OutOfBoundsDatetime",
     "OutOfBoundsTimedelta",
     "IncompatibleFrequency",
@@ -37,7 +36,6 @@
     NaT,
     NaTType,
     iNaT,
-    is_null_datetimelike,
     nat_strings,
 )
 from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime

pandas/_libs/tslibs/nattype.pxd

@@ -18,4 +18,3 @@ cdef _NaT c_NaT
 cdef bint checknull_with_nat(object val)
 cdef bint is_dt64nat(object val)
 cdef bint is_td64nat(object val)
-cpdef bint is_null_datetimelike(object val, bint inat_is_null=*, bint inf_as_na=*)

pandas/_libs/tslibs/nattype.pyi

@@ -12,10 +12,6 @@ NaT: NaTType
 iNaT: int
 nat_strings: set[str]
 
-def is_null_datetimelike(
-    val: object, inat_is_null: bool = ..., inf_as_na: bool = ...
-) -> bool: ...
-
 class NaTType(datetime):
     value: np.int64
     def asm8(self) -> np.datetime64: ...

pandas/_libs/tslibs/nattype.pyx

@@ -1218,45 +1218,3 @@ cdef inline bint is_td64nat(object val):
     if util.is_timedelta64_object(val):
         return get_timedelta64_value(val) == NPY_NAT
     return False
-
-
-cdef:
-    cnp.float64_t INF = <cnp.float64_t>np.inf
-    cnp.float64_t NEGINF = -INF
-
-
-cpdef bint is_null_datetimelike(
-    object val, bint inat_is_null=True, bint inf_as_na=False
-):
-    """
-    Determine if we have a null for a timedelta/datetime (or integer versions).
-
-    Parameters
-    ----------
-    val : object
-    inat_is_null : bool, default True
-        Whether to treat integer iNaT value as null
-    inf_as_na : bool, default False
-        Whether to treat INF or -INF value as null.
-
-    Returns
-    -------
-    bool
-    """
-    if val is None:
-        return True
-    elif val is c_NaT:
-        return True
-    elif util.is_float_object(val) or util.is_complex_object(val):
-        if val != val:
-            return True
-        if inf_as_na:
-            return val == INF or val == NEGINF
-        return False
-    elif util.is_timedelta64_object(val):
-        return get_timedelta64_value(val) == NPY_NAT
-    elif util.is_datetime64_object(val):
-        return get_datetime64_value(val) == NPY_NAT
-    elif inat_is_null and util.is_integer_object(val):
-        return val == NPY_NAT
-    return False

pandas/tests/dtypes/test_missing.py

@@ -8,10 +8,7 @@
 from pandas._config import config as cf
 
 from pandas._libs import missing as libmissing
-from pandas._libs.tslibs import (
-    iNaT,
-    is_null_datetimelike,
-)
+from pandas._libs.tslibs import iNaT
 
 from pandas.core.dtypes.common import (
     is_float,
@@ -687,26 +684,6 @@ def test_checknull_old(self):
         for value in never_na_vals:
             assert not libmissing.checknull_old(value)
 
-    def test_is_null_datetimelike(self):
-        for value in na_vals:
-            assert is_null_datetimelike(value)
-            assert is_null_datetimelike(value, False)
-
-        for value in inf_vals:
-            assert not is_null_datetimelike(value)
-            assert not is_null_datetimelike(value, False)
-
-        for value in int_na_vals:
-            assert is_null_datetimelike(value)
-            assert not is_null_datetimelike(value, False)
-
-        for value in sometimes_na_vals:
-            assert not is_null_datetimelike(value)
-            assert not is_null_datetimelike(value, False)
-
-        for value in never_na_vals:
-            assert not is_null_datetimelike(value)
-
     def test_is_matching_na(self, nulls_fixture, nulls_fixture2):
         left = nulls_fixture
         right = nulls_fixture2

pandas/tests/tslibs/test_api.py

@@ -29,7 +29,6 @@ def test_namespace():
         "NaT",
         "NaTType",
         "iNaT",
-        "is_null_datetimelike",
         "nat_strings",
         "OutOfBoundsDatetime",
         "OutOfBoundsTimedelta",