from sklearnex import patch_sklearn
patch_sklearn()

from sklearn.cluster import DBSCAN
import numpy as np

X = np.array([[1., 2.], [2., 2.], [2., 3.],
              [8., 7.], [8., 8.], [25., 80.]], dtype=np.float32)
clustering = DBSCAN(eps=3, min_samples=2).fit(X)
print(clustering.labels_)  # [ 0  0  0  1  1 -1]