code: def test_convert_featurebase_list_to_feature_list():
      col_defs = [
          ("idx", "Integer", {"index"}),
          ("f_1", "Double"),
          ("f_2", "Double"),
          ("f_3", "NaturalLanguage"),
      ]
  
      df = generate_fake_dataframe(
          col_defs=col_defs,
      )
  
      es = EntitySet(id="es")
      es.add_dataframe(df, df.ww.name)
  
      fdefs = dfs(
          entityset=es,
          target_dataframe_name=df.ww.name,
          trans_primitives=[AddNumeric, MultiOutputPrimitiveForTest],
          features_only=True,
          max_depth=1,
      )
      assert isinstance(fdefs, list)
      assert isinstance(fdefs[0], FeatureBase)
  
      converted_features = set(
          convert_featurebase_list_to_feature_list(fdefs)
      )
  
      f1 = LiteFeature("f_1", Double)
      f2 = LiteFeature("f_2", Double)
      f3 = LiteFeature("f_3", NaturalLanguage)
      fadd = LiteFeature(
          name="f_1 + f_2",
          tags={"numeric"},
          primitive=AddNumeric(),
          base_features=[f1, f2],
      )
      fmo0 = LiteFeature(
          name="TEST_MO(f_3)[0]",
          tags={"numeric"},
          primitive=MultiOutputPrimitiveForTest(),
          base_features=[f3],
          idx=0,
      )
      fmo1 = LiteFeature(
          name="TEST_MO(f_3)[1]",
          tags={"numeric"},
          primitive=MultiOutputPrimitiveForTest(),
          base_features=[f3],
          idx=1,
      )
      fmo0.related_features = {fmo1}
      fmo1.related_features = {fmo0}
  
      orig_features = set([f1, f2, fadd, fmo0, fmo1])
  
      assert (
          len(orig_features.symmetric_difference(converted_features))
          == 0
      )
  
file_path: featuretools/featuretools/tests/feature_discovery/test_convertors.py
imports: from woodwork.logical_types import Double, NaturalLanguage
  from featuretools.entityset.entityset import EntitySet
  from featuretools.feature_base.feature_base import FeatureBase, IdentityFeature, TransformFeature
  from featuretools.feature_discovery.convertors import _convert_feature_to_featurebase, convert_feature_list_to_featurebase_list, convert_featurebase_list_to_feature_list
  from featuretools.feature_discovery.feature_discovery import generate_features_from_primitives, schema_to_features
  from featuretools.feature_discovery.LiteFeature import LiteFeature
  from featuretools.primitives import Absolute, AddNumeric, Lag
  from featuretools.synthesis import dfs
  from featuretools.tests.feature_discovery.test_feature_discovery import MultiOutputPrimitiveForTest
  from featuretools.tests.testing_utils.generate_fake_dataframe import generate_fake_dataframe
label_desc: Use image node_id 1 for calling a global function with example usage: test_convert_featurebase_list_to_feature_list() without return types