fix: cast JSON and nested struct columns to string for anywidget rendering (#17189)

This Pull Request resolves visualization crashes when rendering
DataFrames or Series containing raw JSON and nested JSON struct
structures. It ensures that these columns are safely pre-serialized into
clean, flat JSON string format on the database level prior to visual
layout rendering.

Verified at: screen/424ojbuqyBPinTb

Fixes #<514763826> 🦕

Author: shuoweil

packages/bigframes/bigframes/dataframe.py

@@ -819,9 +819,25 @@ def __repr__(self) -> str:
             column_count=len(self.columns),
         )
 
-    def _get_display_df_and_blob_cols(self) -> tuple[DataFrame, list[str]]:
-        """Process ObjectRef columns for display. (Deprecated)"""
-        return self, []
+    def _get_display_df(self) -> DataFrame:
+        """Process ObjectRef and JSON/nested JSON columns for display."""
+        df = self
+        # Arrow/Pandas to_pandas_batches does not support raw JSON/nested JSON
+        # columns. Pre-serialize them to string format to bypass this limit.
+        # Using TO_JSON_STRING via SqlScalarOp handles complex nested STRUCT
+        # types correctly.
+        json_cols = [
+            col
+            for col in df.columns
+            if bigframes.dtypes.contains_db_dtypes_json_dtype(df[col].dtype)
+        ]
+        if json_cols:
+            op = ops.SqlScalarOp(
+                _output_type=bigframes.dtypes.STRING_DTYPE,
+                sql_template="TO_JSON_STRING({0})",
+            )
+            df = df.assign(**{col: df[col]._apply_unary_op(op) for col in json_cols})
+        return df
 
     def _repr_mimebundle_(self, include=None, exclude=None):
         """

packages/bigframes/bigframes/display/html.py

@@ -30,6 +30,7 @@
 import bigframes.formatting_helpers as formatter
 from bigframes._config import display_options, options
 from bigframes.display import plaintext
+from bigframes.series import Series
 
 if typing.TYPE_CHECKING:
     import bigframes.dataframe
@@ -191,8 +192,6 @@ def create_html_representation(
     total_columns: int,
 ) -> str:
     """Create an HTML representation of the DataFrame or Series."""
-    from bigframes.series import Series
-
     opts = options.display
     with display_options.pandas_repr(opts):
         if isinstance(obj, Series):
@@ -217,8 +216,6 @@ def create_html_representation(
 def _get_obj_metadata(
     obj: Union[bigframes.dataframe.DataFrame, bigframes.series.Series],
 ) -> tuple[bool, bool]:
-    from bigframes.series import Series
-
     is_series = isinstance(obj, Series)
     if is_series:
         has_index = len(obj._block.index_columns) > 0
@@ -237,12 +234,8 @@ def get_anywidget_bundle(
     This function encapsulates the logic for anywidget display.
     """
     from bigframes import display
-    from bigframes.series import Series
 
-    if isinstance(obj, Series):
-        df = obj.to_frame()
-    else:
-        df, _ = obj._get_display_df_and_blob_cols()
+    df = obj._get_display_df()
 
     widget = display.TableWidget(df)
     widget_repr_result = widget._repr_mimebundle_(include=include, exclude=exclude)
@@ -290,18 +283,11 @@ def repr_mimebundle_deferred(
 def repr_mimebundle_head(
     obj: Union[bigframes.dataframe.DataFrame, bigframes.series.Series],
 ) -> dict[str, str]:
-    from bigframes.series import Series
-
     opts = options.display
-    if isinstance(obj, Series):
-        pandas_df, row_count, query_job = obj._block.retrieve_repr_request_results(
-            opts.max_rows
-        )
-    else:
-        df, _ = obj._get_display_df_and_blob_cols()
-        pandas_df, row_count, query_job = df._block.retrieve_repr_request_results(
-            opts.max_rows
-        )
+    df = obj._get_display_df()
+    pandas_df, row_count, query_job = df._block.retrieve_repr_request_results(
+        opts.max_rows
+    )
 
     obj._set_internal_query_job(query_job)
     column_count = len(pandas_df.columns)

packages/bigframes/bigframes/series.py

@@ -572,6 +572,9 @@ def reset_index(
                 block = block.assign_label(self._value_column, name)
             return bigframes.dataframe.DataFrame(block)
 
+    def _get_display_df(self) -> bigframes.dataframe.DataFrame:
+        return self.to_frame()._get_display_df()
+
     def _repr_mimebundle_(self, include=None, exclude=None):
         """
         Custom display method for IPython/Jupyter environments.