input: def classify_spam_emails(X_train, y_train, X_test):
      """ This function constructs a Naive Bayes classifier using Python to classify emails 
      as spam or not spam. 
      >>> X_train = [...] # Training data features
      >>> y_train = [...] # Training data labels (spam or not spam)
      >>> X_test = [...]  # Test data features for prediction
      >>> classify_spam_emails(X_train, y_train, X_test)
      array([1, 0, 1])  # Example output indicating predictions for spam (1) and not spam (0)
      """
      from sklearn.naive_bayes import GaussianNB
  
      # Create a Gaussian Classifier
      model = GaussianNB()
  
      # Train the model using the training sets 
      model.fit(X_train, y_train)
  
      # Predict Output 
      y_pred = model.predict(X_test)
      return y_pred
output:     from sklearn.naive_bayes import GaussianNB
  
      # Create a Gaussian Classifier
      model = GaussianNB()
  
      # Train the model using the training sets 
      model.fit(X_train, y_train)
  
      # Predict Output 
      y_pred = model.predict(X_test)
      return y_pred