code: def test_rename(generator_helper, data_helper):
      # Given
      input_data = data_helper.generate_multi_feature_full()
  
      generator = RenameFeatureGenerator(
          name_prefix="pre_", name_suffix="_suf"
      )
  
      expected_feature_metadata_in_full = {
          ("category", ()): ["cat"],
          ("datetime", ()): ["datetime"],
          ("float", ()): ["float"],
          ("int", ()): ["int_bool", "int"],
          ("object", ()): ["obj"],
          ("object", ("datetime_as_object",)): ["datetime_as_object"],
          ("object", ("text",)): ["text"],
      }
  
      expected_feature_metadata_full = {
          ("category", ()): ["pre_cat_suf"],
          ("datetime", ()): ["pre_datetime_suf"],
          ("float", ()): ["pre_float_suf"],
          ("int", ()): ["pre_int_bool_suf", "pre_int_suf"],
          ("object", ()): ["pre_obj_suf"],
          ("object", ("datetime_as_object",)): [
              "pre_datetime_as_object_suf"
          ],
          ("object", ("text",)): ["pre_text_suf"],
      }
  
      # When
      output_data = generator_helper.fit_transform_assert(
          input_data=input_data,
          generator=generator,
          expected_feature_metadata_in_full=expected_feature_metadata_in_full,
          expected_feature_metadata_full=expected_feature_metadata_full,
      )
  
      # Therefore
      output_data.columns = input_data.columns
  
      assert input_data.equals(output_data)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_rename(generator_helper, data_helper) without return types