code: def test_cast_to_python_types(
      td_extractor: TextDescriptivesExtractor,
  ) -> None:
      df = pd.DataFrame(
          {
              "col_int": [1, 2, 3],
              "col_bool": [True, False, True],
              "col_float": [1.234, 2.345, 3.456],
          }
      )
      df_result = td_extractor._cast_to_python_types(df)
      assert (
          df_result["col_int"].dtype == "int32"
          or df_result["col_int"].dtype == "int64"
      )
      assert df_result["col_bool"].dtype == "object"
      assert (
          df_result["col_float"].dtype == "float64"
          or df_result["col_float"].dtype == "float32"
      )
      assert df_result["col_float"].values[0] == 1.23
      assert isinstance(df_result, pd.DataFrame)
  
imports: from unittest.mock import MagicMock
  import pandas
  import pytest
  from argilla.client.feedback.dataset import FeedbackDataset
  from argilla.client.feedback.integrations.textdescriptives import TextDescriptivesExtractor
  from argilla.client.feedback.schemas.fields import TextField
  from argilla.client.feedback.schemas.metadata import FloatMetadataProperty, IntegerMetadataProperty, TermsMetadataProperty
  from argilla.client.feedback.schemas.questions import TextQuestion
  from argilla.client.feedback.schemas.records import FeedbackRecord
label_desc: Use image node_id 6 for calling a global function with example usage: test_cast_to_python_types(td_extractor) without return types