input: 
  def predict_labels(dataset_url: str) -> list:
      """ Predict the class labels of a given set of data.
      The dataset contains 4 features: Length, Width, Height and Weight.
      >>> predict_labels('http://example.com/data.csv')
      ['class1', 'class2', 'class1']
      """
      import pandas as pd
      from sklearn.tree import DecisionTreeClassifier
  
      df = pd.read_csv(dataset_url)
      X = df.iloc[:, 0:4].values
      y = df.iloc[:, 4].values
  
      model = DecisionTreeClassifier()
      model.fit(X, y)
  
      predictions = model.predict(X)
      return predictions.tolist()
  
output:     label_map = {'0': 'class1', '1': 'class2'}
      return [label_map[str(label)] for label in predictions]