code: def test_flat_aggregate_list_view(self):
      import pandas as pd
  
      my_concat = udtaf(ListViewConcatTableAggregateFunction())
      self.t_env.get_config().set(
          "python.fn-execution.bundle.size", "2"
      )
      # trigger the cache eviction in a bundle.
      self.t_env.get_config().set("python.state.cache-size", "2")
      t = self.t_env.from_elements(
          [
              (1, "Hi", "Hello"),
              (3, "Hi", "hi"),
              (3, "Hi2", "hi"),
              (3, "Hi", "hi"),
              (2, "Hi", "Hello"),
              (1, "Hi2", "Hello"),
              (3, "Hi3", "hi"),
              (3, "Hi2", "Hello"),
              (3, "Hi3", "hi"),
              (2, "Hi3", "Hello"),
          ],
          ["a", "b", "c"],
      )
      result = (
          t.group_by(t.c)
          .flat_aggregate(my_concat(t.b, ",").alias("b"))
          .select(t.b, t.c)
          .alias("a", "c")
      )
      assert_frame_equal(
          result.to_pandas().sort_values("c").reset_index(drop=True),
          pd.DataFrame(
              [
                  ["Hi,Hi,Hi2,Hi2,Hi3", "Hello"],
                  ["Hi,Hi,Hi2,Hi2,Hi3", "Hello"],
                  ["Hi,Hi2,Hi,Hi3,Hi3", "hi"],
                  ["Hi,Hi2,Hi,Hi3,Hi3", "hi"],
              ],
              columns=["a", "c"],
          ),
      )
  
imports: import unittest
  from pandas.testing import assert_frame_equal
  from pyflink.common import Row
  from pyflink.table import expressions, ListView
  from pyflink.table.types import DataTypes
  from pyflink.table.udf import udf, udtf, udaf, AggregateFunction, TableAggregateFunction, udtaf
  from pyflink.testing import source_sink_utils
  from pyflink.testing.test_case_utils import PyFlinkBatchTableTestCase, PyFlinkStreamTableTestCase
label_desc: Use image node_id 3 for calling the StreamRowBasedOperationITTests obj's underlying member method code with example usage: obj.test_flat_aggregate_list_view() without return types