code: def test_json_nested_mixed_types_in_list(jsonl_string):
      # utility function for this test:
      # replace list elements with None if it has dict and non-dict (ignore None)
      def _replace_in_list(list_to_replace, replace_items):
          return [
              _replace_in_list(x, replace_items)
              if isinstance(x, list)
              else None
              if x in replace_items
              else x
              for x in list_to_replace
          ]
  
      def _replace_with_nulls(df, replace_items):
          for col in df.columns:
              if df[col].dtype == "object":
                  df[col] = df[col].apply(
                      lambda x: _replace_in_list(x, replace_items)
                      if isinstance(x, list)
                      else x
                  )
          return df
  
      # both json lines and json string tested.
      json_string = "[" + jsonl_string.replace("\n", ",") + "]"
      pdf = pd.read_json(jsonl_string, orient="records", lines=True)
      pdf2 = pd.read_json(json_string, orient="records", lines=False)
      assert_eq(pdf, pdf2)
      # replace list elements with None if it has dict and non-dict
      # in above test cases, these items are mixed with dict/list items
      # so, replace them with None.
      pdf = _replace_with_nulls(pdf, [123, "123", 12.3, "abc"])
      gdf = cudf.read_json(
          StringIO(jsonl_string),
          orient="records",
          lines=True,
      )
      gdf2 = cudf.read_json(
          StringIO(json_string),
          engine="cudf",
          orient="records",
          lines=False,
      )
      if """[{"0": 123}, {}]""" not in jsonl_string:
          # {} in pandas is represented as {"0": None} in cudf
          assert_eq(gdf, pdf)
          assert_eq(gdf2, pdf)
      pa_table_pdf = pa.Table.from_pandas(
          pdf, schema=gdf.to_arrow().schema, safe=False
      )
      assert gdf.to_arrow().equals(pa_table_pdf)
      assert gdf2.to_arrow().equals(pa_table_pdf)
  
imports: import copy
  import gzip
  import itertools
  import os
  from io import BytesIO, StringIO
  from pathlib import Path
  import numpy
  import pandas
  import pyarrow
  import pytest
  import cudf
  from cudf.testing._utils import DATETIME_TYPES, NUMERIC_TYPES, TIMEDELTA_TYPES, assert_eq
label_desc: Use image node_id 42 for calling a global function with example usage: test_json_nested_mixed_types_in_list(jsonl_string) and returns: unknown, df