Dirichlet process mixture models for clustering using R?

I was following along with this blog post - http://blog.echen.me/2012/03/20/infinite-mixture-models-with-nonparametric-bayes-and-the-dirichlet-process/ where he explains clustering through the used of DPMM's, and at the bottom he has a cool example of clustering the McDonald's menu.

He just simply uses scikit-learn’s Dirichlet Process Gaussian Mixture Model in Python to perform this clustering. I was checking to see if there was a package available in CRAN to perform similar function in R, and the closest I found was dpmixsim, which only works on a vector, so we would not be able to give it a data frame.

Does anyone know of a similar function in R that would handle data frames? (If not, I'll just export my data from R to python, but it seems like there should be something...)