Hiya,
In python's sklearn methods like K-Means and K-Mediods take an n_init parameter:
To use their description:

n_init : int, default: 10
Number of time the k-means algorithm will be run with different centroid seeds. The final results will be the best output of n_init consecutive runs ...

I think it would be good to have that here,
particularly since a single run of k-means is fairly poor as a method for clustering data.
Running it several times and taking the best is common practice.