input: from typing import List
  
  def predict(data: List[float]) -> int:
      """Predict the class label of a given set of data. The dataset contains 4 features: Length, Width, Height, and Weight.
      >>> predict([2.0, 3.0, 4.0, 5.0])
      1
      >>> predict([1.0, 2.0, 3.0, 4.0])
      0
      """
      import pandas as pd
      from sklearn.tree import DecisionTreeClassifier
  
      # Load the dataset
      csv_url = 'http://test.test/test.csv'
      df = pd.read_csv(csv_url)
  
      # Split the dataset into features and label
      X = df.iloc[:, 0:4].values
      y = df.iloc[:, 4].values
  
      # Create and fit the model
      model = DecisionTreeClassifier()
      model.fit(X, y)
  
      # Predict the label
      predicted_label = model.predict([data])[0]
      return predicted_label
output:     return predicted_label