check and load pacakges in predict() for #308

Author: topepo

NAMESPACE

@@ -53,6 +53,8 @@ S3method(print,rand_forest)
 S3method(print,surv_reg)
 S3method(print,svm_poly)
 S3method(print,svm_rbf)
+S3method(req_pkgs,model_fit)
+S3method(req_pkgs,model_spec)
 S3method(tidy,model_fit)
 S3method(tidy,nullmodel)
 S3method(translate,boost_tree)
@@ -144,6 +146,7 @@ export(predict_raw)
 export(predict_raw.model_fit)
 export(rand_forest)
 export(repair_call)
+export(req_pkgs)
 export(rpart_train)
 export(set_args)
 export(set_dependency)

NEWS.md

@@ -18,6 +18,10 @@
 
  * A function named `repair_call()` was added. This can help change the underlying models `call` object to better reflect what they would have obtained if the model function had been used directly (instead of via `parsnip`). This is only useful when the user chooses a formula interface and the model uses a formula interface. It will also be of limited use when a recipes is used to construct the feature set in `workflows` or `tune`. 
 
+ * The `predict()` function now checks to see if required modeling packages are installed. The packages are loaded (but not attached). (#249) (#308) (tidymodels/workflows#45)
+ 
+ * The function `req_pkgs()` is a user interface to determining the required packages.  (#308)
+ 
 # parsnip 0.1.1
 
 ## New Features

R/aaa.R

@@ -66,7 +66,7 @@ utils::globalVariables(
     'lab', 'original', 'predicted_label', 'prediction', 'value', 'type',
     "neighbors", ".submodels", "has_submodel", "max_neighbor", "max_penalty",
     "max_terms", "max_tree", "model", "name", "num_terms", "penalty", "trees",
-    "sub_neighbors", ".pred_class", "x", "y")
+    "sub_neighbors", ".pred_class", "x", "y", "predictor_indicators")
 )
 
 # nocov end

R/predict.R

@@ -117,6 +117,9 @@ predict.model_fit <- function(object, new_data, type = NULL, opts = list(), ...)
     return(NULL)
   }
 
+  check_installs(object$spec)
+  load_libs(object$spec, quiet = TRUE)
+
   other_args <- c("level", "std_error", "quantile") # "time" for survival probs later
   is_pred_arg <- names(the_dots) %in% other_args
   if (any(!is_pred_arg)) {