Fixed issue with CRAN test by adding helper.

.Rbuildignore

@@ -9,3 +9,4 @@
 ^README\.Rmd$
 ^codecov\.yml$
 ^cran-comments\.md$
+^CRAN-SUBMISSION$

CRAN-SUBMISSION

@@ -0,0 +1,3 @@
+Version: 1.0.0
+Date: 2024-02-01 06:50:20 UTC
+SHA: 5812e42484b4d2586fe7122f9724f2e0fbcec698

R/get_token.R

@@ -1,26 +1,25 @@
 #' Get TIMEGPT_TOKEN from options or from .Renviron
 #' This is a private function of nixtlar
 #'
-#' @return If available, the TIMEGTP_TOKEN
+#' @return If available, the TIMEGTP_TOKEN. Otherwise it returns an error and a message asking the user to set the token.
 #' @export
 #' @keywords internal
 #' @examples
 #' \dontrun{
-#'   .get_token() # Assumes token was previously set successfully
+#'   .get_token()
 #' }
 #'
 .get_token <- function(){
 
   # Get token from options
-  token <- getOption("TIMEGPT_TOKEN")
-
+  token <- Sys.getenv("TIMEGPT_TOKEN", unset = NA)
   # If not available, get it from .Renviron
-  if(is.null(token)){
-    token <- Sys.getenv("TIMEGPT_TOKEN")
+  if(is.na(token)) {
+    token <- getOption("TIMEGPT_TOKEN", default = NA)
   }
 
   # Return token or, if not available, stop
-  if(nzchar(token)){
+  if(!is.na(token)){
     return(token)
   }else{
     stop("Please set TIMEGPT_TOKEN. Use nixtla_set_token() or set it as an environment variable in .Renviron")

R/nixtla_validate_token.R

@@ -1,6 +1,6 @@
 #' Validate token
 #'
-#' @return A message indicating whether the token is valid.
+#' @return A status code and a message indicating whether the token is valid.
 #' @export
 #'
 #' @examples

R/validate_exogenous.R

@@ -9,18 +9,24 @@
 #' @export
 #' @keywords internal
 #'
+#' @examples
+#' \dontrun{
+#' Download df and X_df from https://docs.nixtla.io/docs/exogenous_variables and then run
+#' .validate_exogenous(df, h=24, X_df)
+#' }
+#'
 .validate_exogenous <- function(df, h, X_df){
 
   status <- list(validation = TRUE,
-              message = NULL
-              )
+                 message = NULL
+                 )
 
   # Check if df and X_df contain the same exogenous variables
   vals_df <- setdiff(names(df), c("unique_id", "ds", "y"))
   vals_X_df <- setdiff(names(X_df), c("unique_id", "ds"))
 
   if(!setequal(vals_df, vals_X_df)){
-    status$valdiation <- FALSE
+    status$validation <- FALSE
     status$message <- "df and X_df must contain the same exogenous variables."
   }
 

tests/testthat/helper.R

@@ -0,0 +1,8 @@
+
+skip_if_no_token <- function() {
+  tryCatch({
+    nixtlar::.get_token()
+  }, error = function(e) {
+    testthat::skip("TIMEGPT_TOKEN is not set")
+  })
+}

tests/testthat/test-timegpt-anomaly_detection.R

@@ -1,5 +1,6 @@
 with_mock_dir("../mocks", {
   test_that("timegpt_anomaly_detection", {
+    skip_if_no_token()
     test_data <- nixtlar::electricity
     response <- timegpt_anomaly_detection(test_data, id_col = "unique_id")
     expect_s3_class(response, "data.frame")

tests/testthat/test-timegpt_cross_validation.R

@@ -1,5 +1,6 @@
 with_mock_dir("../mocks", {
   test_that("timegpt_cross_validation", {
+    skip_if_no_token()
     test_data <- nixtlar::electricity
     response <- timegpt_cross_validation(test_data, h = 8, id_col = "unique_id", n_windows = 5)
     expect_s3_class(response, "data.frame")

tests/testthat/test-timegpt_forecast.R

@@ -1,5 +1,6 @@
 with_mock_dir("../mocks", {
   test_that("timegpt_forecast", {
+    skip_if_no_token()
     test_data <- nixtlar::electricity
     response <- timegpt_forecast(test_data, h = 8, id_col = "unique_id", level = c(80,95))
     expect_s3_class(response, "data.frame")

tests/testthat/test-timegpt_historic.R

@@ -1,5 +1,6 @@
 with_mock_dir("../mocks", {
   test_that("timegpt historic", {
+    skip_if_no_token()
     test_data <- nixtlar::electricity
     response <- timegpt_historic(test_data, id_col = "unique_id", level = c(80,95))
     expect_s3_class(response, "data.frame")