How to call predict for 3 different algorithms from same custom R package function?

Question

I'm working on a custom R package (it is private, not hosted anywhere). In this package, I have a function that takes xgboost, RandomForest (from the ranger function), and glmnet models and uses them to predict on a new dataset.

Each time I'm predicting, I use the same generalized predict function. If I don't namespace the function, R doesn't know which library to use for the predict.

The error I get is:

Error in UseMethod("predict") : 
  no applicable method for 'predict' applied to an object of class "c('lognet', 'glmnet')" 

If I load the functions manually, it works, but I know that loading packages manually within an R library is a taboo.

I tried using glmnet::glmnet.predict, etc. but this is giving me errors, as well. What would be the proper way to namespace these predict functions to avoid loading the libraries manually?

Answer 1

I've run into this myself on occasion where, for example, this works:

ranger::predictions(predict(model, data))

but this does not, under identical circumstances:

predict(model, data)

Your package presumably Imports the necessary dependency, but the various S3 methods, including predict.<class>(), are never registered for use unless you tell R to use them at some point earlier in your program. You can fix this by adding requireNamespace(<package name>, quietly = TRUE) either at the top of the given function or in .onLoad(). This causes R to register the appropriate S3 methods, etc., and you can confirm this by checking methods(predict) before and after. Importantly, this is true for non-exported methods that disallow roxygen2 declarations like #' @importFrom <package name> <predict.class>.

In my particular example above, :: causes R to load ranger along with its various S3 methods, including predict.ranger(), so predict() dispatches just fine.