CLN/BUG: array_equivalent on nested objects

ci/code_checks.sh

@@ -125,6 +125,12 @@ if [[ -z "$CHECK" || "$CHECK" == "patterns" ]]; then
     # invgrep -R --include="*.py*" -E "from numpy import nan " pandas  # GH#24822 not yet implemented since the offending imports have not all been removed
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
+    # flake8 check will find bare except E722 in .py files, need to grep
+    #  to find these in cython files
+    MSG='Check for bare except statements' ; echo $MSG
+    invgrep -R --include="*.py*" -E "except:" pandas
+    RET=$(($RET + $?)) ; echo $MSG "DONE"
+
     MSG='Check for pytest warns' ; echo $MSG
     invgrep -r -E --include '*.py' 'pytest\.warns' pandas/tests/
     RET=$(($RET + $?)) ; echo $MSG "DONE"

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",
     [