code: def test_0_predict_file_flow(self):
      from lightwood.api.high_level import predictor_from_problem
  
      df = pd.read_csv("tests/data/airline_sentiment.csv")[:500]
      target = "airline_sentiment"
  
      predictor = predictor_from_problem(
          df,
          ProblemDefinition.from_dict(
              {"target": target, "time_aim": 80}
          ),
      )
      train_and_check_time_aim(predictor, df, ignore_time_aim=True)
      predictions = predictor.predict(df)
  
      # sanity checks
      self.assertTrue(
          accuracy_score(df[target], predictions["prediction"]) > 0.5
      )
      self.assertTrue(
          all([0 <= p <= 1 for p in predictions["confidence"]])
      )
  
file_path: lightwood/tests/integration/basic/test_airline.py
imports: import unittest
  import pandas
  from sklearn.metrics import accuracy_score
  from tests.utils.timing import train_and_check_time_aim
  from lightwood.api.types import ProblemDefinition
label_desc: Use image node_id 1 for calling the TestBasic obj's underlying member method code with example usage: obj.test_0_predict_file_flow() without return types