text: from dbcv import get_score
  from sklearn import datasets
  from sklearn.cluster import KMeans
  
  
  def generate_data(n_samples=1000, noise=0.05):
      noisy_moons = datasets.make_moons(n_samples=n_samples, noise=noise)
      X = noisy_moons[0]
      return X
  
  
  def generate_labels(X):
      kmeans = KMeans(n_clusters=2)
      kmeans_labels = kmeans.fit_predict(X)
      return kmeans_labels
  
  
  if __name__ == '__main__':
      X = generate_data()
      labels = generate_labels(X)
      score = get_score(X, labels, 'euclidean', verbose=True)
  
  