How to use the kmodes.util.dissim.euclidean_dissim function in kmodes

    def __init__(self, n_clusters=8, max_iter=100, num_dissim=euclidean_dissim,
                 cat_dissim=matching_dissim, init='Huang', n_init=10, gamma=None,
                 verbose=0, random_state=None, n_jobs=1):

        super(KPrototypes, self).__init__(n_clusters, max_iter, cat_dissim, init,
                                          verbose=verbose, random_state=random_state,
                                          n_jobs=n_jobs)
        self.num_dissim = num_dissim
        self.gamma = gamma
        self.n_init = n_init
        if isinstance(self.init, list) and self.n_init > 1:
            if self.verbose:
                print("Initialization method is deterministic. "
                      "Setting n_init to 1.")
            self.n_init = 1