Best practices of orchestrating Python and R code in ML projects

“Because of performances it was decided that Random Forest classifier should be implemented in Python (it shows better performances than random forest package in R).” Given that the author used a standard sklearn RandomForestClassifier, I’d be surprised if the ranger implementation in R was the one that was tested in whatever benchmark he or she read. I ran both versions last spring, GitHub - ercbk/nested-cross-validation-comparison: Experimenting with various implementations and methods of nested cross-validation in R and Python, and sklearn’s rf was very slow.