text: import pickle
  from main import clf
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler
  
  
  def test_accuracy():
  
      # Load test data
      with open("data/test_data.pkl", "rb") as file:
          test_data = pickle.load(file)
  
      # Unpack the tuple
      X_test, y_test = test_data
  
      # Compute accuracy of classifier
      acc = clf.score(X_test, y_test)
  
      # Accuracy should be over 90%
      assert acc > 0.9
  
  def test_pipeline_and_scaler():
  
      # Check if clf is an instance of sklearn.pipeline.Pipeline 
      isPipeline = isinstance(clf, Pipeline)
      assert isPipeline
      
      if isPipeline:
          # Check if first step of pipeline is an instance of 
          # sklearn.preprocessing.StandardScaler
          firstStep = [v for v in clf.named_steps.values()][0]
          assert isinstance(firstStep, StandardScaler)