improve file_path and id

DESCRIPTION

 Package: algoli
 Type: Package
-Version: 0.0.2
+Version: 0.0.3
 Authors@R: c(person("Jean-Marie", "Lepioufle", , "jml@nilu.no", role=c("aut","cre")),
              person("NILU",role="cph"))
 Title: algoli
@@ -9,6 +9,8 @@ Description: Make the use of algorithms for fitting/prediction easy.
    One simple syntax for every libraries.
 Depends:
     R (>= 3.4.1)
+Imports:
+    stringi
 Suggests:
     knitr
 License: MIT + file LICENSE

R/fit.R

@@ -10,19 +10,20 @@
 #' @param predictors predictors in character
 #' @param train train percentage
 #' @param test test percentage
-#' @param MODEL_DIR boolean save model in a specific recoverable folder, temporary solution
 #' @keywords algoli
 #' @export
 #' @examples
 #' \dontrun{
 #' do_fit()
 #' }
-do_fit <- function(service,algorithm=NULL,...,dataset,col_bind=NULL,target,predictors, train=0.8,test=0.2,MODEL_DIR=FALSE){
+do_fit <- function(service,algorithm=NULL,...,dataset,col_bind=NULL,target,predictors, train=0.8,test=0.2){
 
-  fileCheck_path <- file.path(getwd(),"algoli")
+  id <- stringi::stri_rand_strings(1, 16,'[a-z0-9]')
+
+  fileCheck_path <- normalizePath(file.path(tempdir(),"algoli"),mustWork = FALSE)
   fileCheck_path <- normalizePath(fileCheck_path,mustWork = FALSE)
   dir.create(fileCheck_path, showWarnings = TRUE, recursive = TRUE)
-  fileCheck <- file.path(fileCheck_path,"fit-check.log")
+  fileCheck <- file.path(fileCheck_path,paste0('fit-check_',id,'_.log'))
   file.create(fileCheck)
 
   target <- gsub("\\.","_",target)
@@ -45,21 +46,9 @@ do_fit <- function(service,algorithm=NULL,...,dataset,col_bind=NULL,target,predi
 
   # exporting model ...
   cat(c(as.character(Sys.time()),"export model\n"), file=fileCheck,append=TRUE)
-  tmp_model_path <- normalizePath(file.path(tempdir(),"model"),mustWork = FALSE)
+  tmp_model_path <- normalizePath(file.path(tempdir(),"algoli",id),mustWork = FALSE)
   dir.create(tmp_model_path, showWarnings = TRUE, recursive = TRUE)
-  from <- hello$export_model(res_fit,tmp_model_path)
-
-  if (!MODEL_DIR) {
-     tmp <- list(id=NULL,model_path=from)
-  } else if (MODEL_DIR) {
-      # for an internal access to the binary, temporary solution
-    tmp <- dir_tmp_model()
-    if (!is.null(tmp$model_path)){
-      to <- file.path(tmp$model_path,"model.mod")
-      file.copy(from=from,to=to)
-    } else tmp <- list(id=NULL,model_path=NULL)
-  } else tmp <- list(id=NULL,model_path=NULL)
-
+  model_path <- hello$export_model(res_fit,tmp_model_path)
 
   # Prediction on the test dataset ...
   cat(c(as.character(Sys.time()),"predict\n"), file=fileCheck,append=TRUE)
@@ -70,9 +59,10 @@ do_fit <- function(service,algorithm=NULL,...,dataset,col_bind=NULL,target,predi
               args = list(...),
               target = target,
               predictors = predictors,
+              col_bind = col_bind,
               pred = res_pred,
-              id = tmp$id,
-              path = tmp$model_path)
+              id = id,
+              path = model_path)
 
   # disconnect ...
   cat(c(as.character(Sys.time()),"disconnect\n"), file=fileCheck,append=TRUE)

R/predict.R

@@ -14,10 +14,12 @@
 #' }
 do_predict <- function(service,model_path=NULL,model_id=NULL,dataset=NULL,col_bind=NULL){
 
-  fileCheck_path <- file.path(getwd(),"algoli")
+  id <- stringi::stri_rand_strings(1, 16,'[a-z0-9]')
+
+  fileCheck_path <- normalizePath(file.path(tempdir(),"algoli"),mustWork = FALSE)
   fileCheck_path <- normalizePath(fileCheck_path,mustWork = FALSE)
   dir.create(fileCheck_path, showWarnings = TRUE, recursive = TRUE)
-  fileCheck <- file.path(fileCheck_path,"predict-check.log")
+  fileCheck <- file.path(fileCheck_path,paste0('predict-check_',id,'_.log'))
   file.create(fileCheck)
 
   # new algoli

man/do_fit.Rd

@@ -6,7 +6,7 @@
 do_fit}
 \usage{
 do_fit(service, algorithm = NULL, ..., dataset, col_bind = NULL,
-  target, predictors, train = 0.8, test = 0.2, MODEL_DIR = FALSE)
+  target, predictors, train = 0.8, test = 0.2)
 }
 \arguments{
 \item{service}{service}
@@ -26,8 +26,6 @@ do_fit(service, algorithm = NULL, ..., dataset, col_bind = NULL,
 \item{train}{train percentage}
 
 \item{test}{test percentage}
-
-\item{MODEL_DIR}{boolean save model in a specific recoverable folder, temporary solution}
 }
 \description{
 do_fit