BUG: fix array_equivalent with mismatched tzawareness (pandas-dev#28508)

Author: jbrockmendel

pandas/_libs/lib.pyx

@@ -55,8 +55,7 @@ cimport pandas._libs.util as util
 from pandas._libs.util cimport is_nan, UINT64_MAX, INT64_MAX, INT64_MIN
 
 from pandas._libs.tslib import array_to_datetime
-from pandas._libs.tslibs.nattype cimport NPY_NAT
-from pandas._libs.tslibs.nattype import NaT
+from pandas._libs.tslibs.nattype cimport NPY_NAT, c_NaT as NaT
 from pandas._libs.tslibs.conversion cimport convert_to_tsobject
 from pandas._libs.tslibs.timedeltas cimport convert_to_timedelta64
 from pandas._libs.tslibs.timezones cimport get_timezone, tz_compare
@@ -525,9 +524,18 @@ def array_equivalent_object(left: object[:], right: object[:]) -> bool:
 
         # we are either not equal or both nan
         # I think None == None will be true here
-        if not (PyObject_RichCompareBool(x, y, Py_EQ) or
-                (x is None or is_nan(x)) and (y is None or is_nan(y))):
-            return False
+        try:
+            if not (PyObject_RichCompareBool(x, y, Py_EQ) or
+                    (x is None or is_nan(x)) and (y is None or is_nan(y))):
+                return False
+        except TypeError as err:
+            # Avoid raising TypeError on tzawareness mismatch
+            # TODO: This try/except can be removed if/when Timestamp
+            #  comparisons are change dto match datetime, see GH#28507
+            if "tz-naive and tz-aware" in str(err):
+                return False
+            raise
+
     return True
 
 

pandas/core/dtypes/missing.py

@@ -445,8 +445,14 @@ def array_equivalent(left, right, strict_nan=False):
                 if not isinstance(right_value, float) or not np.isnan(right_value):
                     return False
             else:
-                if np.any(left_value != right_value):
-                    return False
+                try:
+                    if np.any(left_value != right_value):
+                        return False
+                except TypeError as err:
+                    if "Cannot compare tz-naive" in str(err):
+                        # tzawareness compat failure, see GH#28507
+                        return False
+                    raise
         return True
 
     # NaNs can occur in float and complex arrays.

pandas/core/indexes/base.py

@@ -4324,12 +4324,9 @@ def equals(self, other):
             # if other is not object, use other's logic for coercion
             return other.equals(self)
 
-        try:
-            return array_equivalent(
-                com.values_from_object(self), com.values_from_object(other)
-            )
-        except Exception:
-            return False
+        return array_equivalent(
+            com.values_from_object(self), com.values_from_object(other)
+        )
 
     def identical(self, other):
         """

pandas/tests/dtypes/test_missing.py

@@ -25,6 +25,9 @@
 from pandas import DatetimeIndex, Float64Index, NaT, Series, TimedeltaIndex, date_range
 from pandas.util import testing as tm
 
+now = pd.Timestamp.now()
+utcnow = pd.Timestamp.now("UTC")
+
 
 @pytest.mark.parametrize("notna_f", [notna, notnull])
 def test_notna_notnull(notna_f):
@@ -332,6 +335,29 @@ def test_array_equivalent():
     assert not array_equivalent(DatetimeIndex([0, np.nan]), TimedeltaIndex([0, np.nan]))
 
 
+@pytest.mark.parametrize(
+    "lvalue, rvalue",
+    [
+        # There are 3 variants for each of lvalue and rvalue. We include all
+        #  three for the tz-naive `now` and exclude the datetim64 variant
+        #  for utcnow because it drops tzinfo.
+        (now, utcnow),
+        (now.to_datetime64(), utcnow),
+        (now.to_pydatetime(), utcnow),
+        (now, utcnow),
+        (now.to_datetime64(), utcnow.to_pydatetime()),
+        (now.to_pydatetime(), utcnow.to_pydatetime()),
+    ],
+)
+def test_array_equivalent_tzawareness(lvalue, rvalue):
+    # we shouldn't raise if comparing tzaware and tznaive datetimes
+    left = np.array([lvalue], dtype=object)
+    right = np.array([rvalue], dtype=object)
+
+    assert not array_equivalent(left, right, strict_nan=True)
+    assert not array_equivalent(left, right, strict_nan=False)
+
+
 def test_array_equivalent_compat():
     # see gh-13388
     m = np.array([(1, 2), (3, 4)], dtype=[("a", int), ("b", float)])