REF: dont patch assert_frame_equal

pandas/tests/extension/json/test_json.py

@@ -79,74 +79,14 @@ def data_for_grouping():
 
 
 class BaseJSON:
-    # NumPy doesn't handle an array of equal-length UserDicts.
-    # The default assert_series_equal eventually does a
-    # Series.values, which raises. We work around it by
-    # converting the UserDicts to dicts.
-    @classmethod
-    def assert_series_equal(cls, left, right, *args, **kwargs):
-        if left.dtype.name == "json":
-            assert left.dtype == right.dtype
-            left = pd.Series(
-                JSONArray(left.values.astype(object)), index=left.index, name=left.name
-            )
-            right = pd.Series(
-                JSONArray(right.values.astype(object)),
-                index=right.index,
-                name=right.name,
-            )
-        tm.assert_series_equal(left, right, *args, **kwargs)
-
-    @classmethod
-    def assert_frame_equal(cls, left, right, *args, **kwargs):
-        obj_type = kwargs.get("obj", "DataFrame")
-        tm.assert_index_equal(
-            left.columns,
-            right.columns,
-            exact=kwargs.get("check_column_type", "equiv"),
-            check_names=kwargs.get("check_names", True),
-            check_exact=kwargs.get("check_exact", False),
-            check_categorical=kwargs.get("check_categorical", True),
-            obj=f"{obj_type}.columns",
-        )
-
-        jsons = (left.dtypes == "json").index
-
-        for col in jsons:
-            cls.assert_series_equal(left[col], right[col], *args, **kwargs)
-
-        left = left.drop(columns=jsons)
-        right = right.drop(columns=jsons)
-        tm.assert_frame_equal(left, right, *args, **kwargs)
+    pass
 
 
 class TestDtype(BaseJSON, base.BaseDtypeTests):
     pass
 
 
 class TestInterface(BaseJSON, base.BaseInterfaceTests):
-    def test_custom_asserts(self):
-        # This would always trigger the KeyError from trying to put
-        # an array of equal-length UserDicts inside an ndarray.
-        data = JSONArray(
-            [
-                collections.UserDict({"a": 1}),
-                collections.UserDict({"b": 2}),
-                collections.UserDict({"c": 3}),
-            ]
-        )
-        a = pd.Series(data)
-        self.assert_series_equal(a, a)
-        self.assert_frame_equal(a.to_frame(), a.to_frame())
-
-        b = pd.Series(data.take([0, 0, 1]))
-        msg = r"Series are different"
-        with pytest.raises(AssertionError, match=msg):
-            self.assert_series_equal(a, b)
-
-        with pytest.raises(AssertionError, match=msg):
-            self.assert_frame_equal(a.to_frame(), b.to_frame())
-
     @pytest.mark.xfail(
         reason="comparison method not implemented for JSONArray (GH-37867)"
     )
@@ -385,3 +325,66 @@ class TestComparisonOps(BaseJSON, base.BaseComparisonOpsTests):
 
 class TestPrinting(BaseJSON, base.BasePrintingTests):
     pass
+
+
+def custom_assert_series_equal(left, right, *args, **kwargs):
+    # NumPy doesn't handle an array of equal-length UserDicts.
+    # The default assert_series_equal eventually does a
+    # Series.values, which raises. We work around it by
+    # converting the UserDicts to dicts.
+    if left.dtype.name == "json":
+        assert left.dtype == right.dtype
+        left = pd.Series(
+            JSONArray(left.values.astype(object)), index=left.index, name=left.name
+        )
+        right = pd.Series(
+            JSONArray(right.values.astype(object)),
+            index=right.index,
+            name=right.name,
+        )
+    tm.assert_series_equal(left, right, *args, **kwargs)
+
+
+def custom_assert_frame_equal(left, right, *args, **kwargs):
+    obj_type = kwargs.get("obj", "DataFrame")
+    tm.assert_index_equal(
+        left.columns,
+        right.columns,
+        exact=kwargs.get("check_column_type", "equiv"),
+        check_names=kwargs.get("check_names", True),
+        check_exact=kwargs.get("check_exact", False),
+        check_categorical=kwargs.get("check_categorical", True),
+        obj=f"{obj_type}.columns",
+    )
+
+    jsons = (left.dtypes == "json").index
+
+    for col in jsons:
+        custom_assert_series_equal(left[col], right[col], *args, **kwargs)
+
+    left = left.drop(columns=jsons)
+    right = right.drop(columns=jsons)
+    tm.assert_frame_equal(left, right, *args, **kwargs)
+
+
+def test_custom_asserts():
+    # This would always trigger the KeyError from trying to put
+    # an array of equal-length UserDicts inside an ndarray.
+    data = JSONArray(
+        [
+            collections.UserDict({"a": 1}),
+            collections.UserDict({"b": 2}),
+            collections.UserDict({"c": 3}),
+        ]
+    )
+    a = pd.Series(data)
+    custom_assert_series_equal(a, a)
+    custom_assert_frame_equal(a.to_frame(), a.to_frame())
+
+    b = pd.Series(data.take([0, 0, 1]))
+    msg = r"Series are different"
+    with pytest.raises(AssertionError, match=msg):
+        custom_assert_series_equal(a, b)
+
+    with pytest.raises(AssertionError, match=msg):
+        custom_assert_frame_equal(a.to_frame(), b.to_frame())