CLN/BUG: array_equivalent on nested objects (#28347)

Author: jbrockmendel

pandas/_libs/testing.pyx

@@ -143,11 +143,9 @@ cpdef assert_almost_equal(a, b,
                 from pandas.util.testing import assert_attr_equal
                 assert_attr_equal('dtype', a, b, obj=obj)
 
-            try:
-                if array_equivalent(a, b, strict_nan=True):
-                    return True
-            except:
-                pass
+            if array_equivalent(a, b, strict_nan=True):
+                return True
+
         else:
             na, nb = len(a), len(b)
 

pandas/core/dtypes/missing.py

@@ -445,7 +445,7 @@ def array_equivalent(left, right, strict_nan=False):
                 if not isinstance(right_value, float) or not np.isnan(right_value):
                     return False
             else:
-                if left_value != right_value:
+                if np.any(left_value != right_value):
                     return False
         return True
 

pandas/tests/dtypes/test_missing.py

@@ -360,6 +360,20 @@ def test_array_equivalent_str():
         )
 
 
+def test_array_equivalent_nested():
+    # reached in groupby aggregations, make sure we use np.any when checking
+    #  if the comparison is truthy
+    left = np.array([np.array([50, 70, 90]), np.array([20, 30, 40])], dtype=object)
+    right = np.array([np.array([50, 70, 90]), np.array([20, 30, 40])], dtype=object)
+
+    assert array_equivalent(left, right, strict_nan=True)
+    assert not array_equivalent(left, right[::-1], strict_nan=True)
+
+    left = np.array([np.array([50, 50, 50]), np.array([40, 40, 40])], dtype=object)
+    right = np.array([50, 40])
+    assert not array_equivalent(left, right, strict_nan=True)
+
+
 @pytest.mark.parametrize(
     "dtype, na_value",
     [