Updated package with new NixtlaClient class.

Nixtla · May 20, 2024 · b87bf32 · b87bf32
1 parent a80013a
commit b87bf32
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diff --git a/CRAN-SUBMISSION b/CRAN-SUBMISSION
@@ -1,3 +1,3 @@
 Version: 1.0.0
-Date: 2024-02-02 04:29:49 UTC
-SHA: 16e8099d0af53baa187225d9bc33efad76e1cbca
+Date: 2024-02-03 19:44:30 UTC
+SHA: a80013ab126ba73c3c0a809177f4ad168e5365dd
diff --git a/NAMESPACE b/NAMESPACE
@@ -1,17 +1,17 @@
 # Generated by roxygen2: do not edit by hand
 
-export(.get_token)
-export(.timegpt_data_prep)
+export(.get_api_key)
+export(.nixtla_data_prep)
 export(.validate_exogenous)
 export(date_conversion)
 export(infer_frequency)
-export(nixtla_set_token)
-export(nixtla_validate_token)
-export(timegpt_anomaly_detection)
-export(timegpt_cross_validation)
-export(timegpt_forecast)
-export(timegpt_historic)
-export(timegpt_plot)
+export(nixtla_client_anomaly_detection)
+export(nixtla_client_cross_validation)
+export(nixtla_client_forecast)
+export(nixtla_client_historic)
+export(nixtla_client_plot)
+export(nixtla_set_api_key)
+export(nixtla_validate_api_key)
 importFrom(dplyr,bind_rows)
 importFrom(dplyr,group_by)
 importFrom(dplyr,inner_join)

diff --git a/R/get_api_key.R b/R/get_api_key.R
@@ -0,0 +1,27 @@
+#' Get NIXTLA_API_KEY from options or from .Renviron
+#' This is a private function of nixtlar
+#'
+#' @return If available, the NIXTLA_API_KEY. Otherwise it returns an error and a message asking the user to set the API key.
+#' @export
+#' @keywords internal
+#' @examples
+#' \dontrun{
+#'   .get_api_key()
+#' }
+#'
+.get_api_key <- function(){
+
+  # Get API key from options
+  api_key <- Sys.getenv("NIXTLA_API_KEY", unset = NA)
+  # If not available, get it from .Renviron
+  if(is.na(api_key)) {
+    api_key <- getOption("NIXTLA_API_KEY", default = NA)
+  }
+
+  # Return API key or, if not available, stop
+  if(!is.na(api_key)){
+    return(api_key)
+  }else{
+    stop("Please set NIXTLA_API_KEY. Use nixtla_set_api_key() or set it as an environment variable in .Renviron")
+  }
+}
diff --git a/R/get_token.R b/R/get_token.R
diff --git a/R/timegpt_anomaly_detection.R → R/nixtla_client_anomaly_detection.R b/R/timegpt_anomaly_detection.R → R/nixtla_client_anomaly_detection.R
@@ -14,12 +14,12 @@
 #'
 #' @examples
 #' \dontrun{
-#'   nixtlar::nixtla_set_token("YOUR_TOKEN")
+#'   nixtlar::nixtla_set_api_key("YOUR_API_KEY")
 #'   df <- nixtlar::electricity
-#'   fcst <- nixtlar::timegpt_anomaly_detection(df, id_col="unique_id")
+#'   fcst <- nixtlar::nixtla_client_anomaly_detection(df, id_col="unique_id")
 #' }
 #'
-timegpt_anomaly_detection <- function(df, freq=NULL, id_col=NULL, time_col="ds", target_col="y", level=c(99), clean_ex_first=TRUE, model="timegpt-1"){
+nixtla_client_anomaly_detection <- function(df, freq=NULL, id_col=NULL, time_col="ds", target_col="y", level=c(99), clean_ex_first=TRUE, model="timegpt-1"){
 
   # Prepare data ----
   names(df)[which(names(df) == time_col)] <- "ds"
@@ -35,7 +35,7 @@ timegpt_anomaly_detection <- function(df, freq=NULL, id_col=NULL, time_col="ds",
     names(df)[which(names(df) == id_col)] <- "unique_id"
   }
 
-  data <- .timegpt_data_prep(df, freq, id_col, time_col, target_col)
+  data <- .nixtla_data_prep(df, freq, id_col, time_col, target_col)
   freq <- data$freq
   y <- data$y
 
@@ -66,12 +66,12 @@ timegpt_anomaly_detection <- function(df, freq=NULL, id_col=NULL, time_col="ds",
   timegpt_data[["level"]] <- level
 
   # Make request ----
-  url_anomaly <- "https://dashboard.nixtla.io/api/timegpt_multi_series_anomalies"
+  url_anomaly <- "https://dashboard.nixtla.io/api/anomaly_detection_multi_series"
   resp_anomaly <- httr2::request(url_anomaly) |>
     httr2::req_headers(
       "accept" = "application/json",
       "content-type" = "application/json",
-      "authorization" = paste("Bearer", .get_token())
+      "authorization" = paste("Bearer", .get_api_key())
     ) |>
     httr2::req_user_agent("nixtlar") |>
     httr2::req_body_json(data = timegpt_data) |>

diff --git a/R/timegpt_cross_validation.R → R/nixtla_client_cross_validation.R b/R/timegpt_cross_validation.R → R/nixtla_client_cross_validation.R
@@ -19,12 +19,12 @@
 #'
 #' @examples
 #' \dontrun{
-#'   nixtlar::nixtla_set_token("YOUR_TOKEN")
+#'   nixtlar::nixtla_set_api_key("YOUR_API_KEY")
 #'   df <- nixtlar::electricity
-#'   fcst <- nixtlar::timegpt_cross_validation(df, h = 8, id_col = "unique_id", n_windows = 5)
+#'   fcst <- nixtlar::nixtla_client_cross_validation(df, h = 8, id_col = "unique_id", n_windows = 5)
 #' }
 #'
-timegpt_cross_validation <- function(df, h=8, freq=NULL, id_col=NULL, time_col="ds", target_col="y", X_df=NULL, level=NULL, n_windows=1, step_size=NULL, finetune_steps=0, clean_ex_first=TRUE, model="timegpt-1"){
+nixtla_client_cross_validation <- function(df, h=8, freq=NULL, id_col=NULL, time_col="ds", target_col="y", X_df=NULL, level=NULL, n_windows=1, step_size=NULL, finetune_steps=0, clean_ex_first=TRUE, model="timegpt-1"){
 
   # Prepare data ----
   names(df)[which(names(df) == time_col)] <- "ds"
@@ -39,7 +39,7 @@ timegpt_cross_validation <- function(df, h=8, freq=NULL, id_col=NULL, time_col="
     names(df)[which(names(df) == id_col)] <- "unique_id"
   }
 
-  data <- .timegpt_data_prep(df, freq, id_col, time_col, target_col)
+  data <- .nixtla_data_prep(df, freq, id_col, time_col, target_col)
   freq <- data$freq
   y <- data$y
 
@@ -93,12 +93,12 @@ timegpt_cross_validation <- function(df, h=8, freq=NULL, id_col=NULL, time_col="
   }
 
   # Make request ----
-  url_cv <- "https://dashboard.nixtla.io/api/timegpt_multi_series_cross_validation"
+  url_cv <- "https://dashboard.nixtla.io/api/cross_validation_multi_series"
   resp_cv <- httr2::request(url_cv) |>
     httr2::req_headers(
       "accept" = "application/json",
       "content-type" = "application/json",
-      "authorization" = paste("Bearer", .get_token())
+      "authorization" = paste("Bearer", .get_api_key())
     ) |>
     httr2::req_user_agent("nixtlar") |>
     httr2::req_body_json(data = timegpt_data) |>

diff --git a/R/timegpt_forecast.R → R/nixtla_client_forecast.R b/R/timegpt_forecast.R → R/nixtla_client_forecast.R
@@ -18,12 +18,12 @@
 #'
 #' @examples
 #' \dontrun{
-#'   nixtlar::nixtla_set_token("YOUR_TOKEN")
+#'   nixtlar::nixtla_set_api_key("YOUR_API_KEY")
 #'   df <- nixtlar::electricity
-#'   fcst <- nixtlar::timegpt_forecast(df, h=8, id_col="unique_id", level=c(80,95))
+#'   fcst <- nixtlar::nixtla_client_forecast(df, h=8, id_col="unique_id", level=c(80,95))
 #' }
 #'
-timegpt_forecast <- function(df, h=8, freq=NULL, id_col=NULL, time_col="ds", target_col="y", X_df=NULL, level=NULL, finetune_steps=0, clean_ex_first=TRUE, add_history=FALSE, model="timegpt-1"){
+nixtla_client_forecast <- function(df, h=8, freq=NULL, id_col=NULL, time_col="ds", target_col="y", X_df=NULL, level=NULL, finetune_steps=0, clean_ex_first=TRUE, add_history=FALSE, model="timegpt-1"){
 
   # Prepare data ----
   names(df)[which(names(df) == time_col)] <- "ds"
@@ -39,7 +39,7 @@ timegpt_forecast <- function(df, h=8, freq=NULL, id_col=NULL, time_col="ds", tar
     names(df)[which(names(df) == id_col)] <- "unique_id"
   }
 
-  data <- .timegpt_data_prep(df, freq, id_col, time_col, target_col)
+  data <- .nixtla_data_prep(df, freq, id_col, time_col, target_col)
   freq <- data$freq
   y <- data$y
 
@@ -87,12 +87,12 @@ timegpt_forecast <- function(df, h=8, freq=NULL, id_col=NULL, time_col="ds", tar
   }
 
   # Make request ----
-  url <- "https://dashboard.nixtla.io/api/timegpt_multi_series"
+  url <- "https://dashboard.nixtla.io/api/forecast_multi_series"
   resp <- httr2::request(url) |>
     httr2::req_headers(
       "accept" = "application/json",
       "content-type" = "application/json",
-      "authorization" = paste("Bearer", .get_token())
+      "authorization" = paste("Bearer", .get_api_key())
       ) |>
     httr2::req_user_agent("nixtlar") |>
     httr2::req_body_json(data = timegpt_data) |>
@@ -145,7 +145,7 @@ timegpt_forecast <- function(df, h=8, freq=NULL, id_col=NULL, time_col="ds", tar
 
   # Generate fitted values ----
   if(add_history){
-    fitted <- timegpt_historic(df, freq=freq, id_col=id_col, time_col=time_col, target_col=target_col, level=level, finetune_steps=finetune_steps, clean_ex_first=clean_ex_first)
+    fitted <- nixtla_client_historic(df, freq=freq, id_col=id_col, time_col=time_col, target_col=target_col, level=level, finetune_steps=finetune_steps, clean_ex_first=clean_ex_first)
     if(tsibble::is_tsibble(df)){
       fcst <- dplyr::bind_rows(fitted, fcst)
     }else{

diff --git a/R/timegpt_historic.R → R/nixtla_client_historic.R b/R/timegpt_historic.R → R/nixtla_client_historic.R
@@ -14,12 +14,12 @@
 #'
 #' @examples
 #' \dontrun{
-#'   nixtlar::nixtla_set_token("YOUR_TOKEN")
+#'   nixtlar::nixtla_set_api_key("YOUR_API_KEY")
 #'   df <- nixtlar::electricity
-#'   fcst <- nixtlar::timegpt_historic(df, id_col="unique_id", level=c(80,95))
+#'   fcst <- nixtlar::nixtla_client_historic(df, id_col="unique_id", level=c(80,95))
 #' }
 #'
-timegpt_historic <- function(df, freq=NULL, id_col=NULL, time_col="ds", target_col="y", level=NULL, finetune_steps=0, clean_ex_first=TRUE){
+nixtla_client_historic <- function(df, freq=NULL, id_col=NULL, time_col="ds", target_col="y", level=NULL, finetune_steps=0, clean_ex_first=TRUE){
 
   # Prepare data ----
   names(df)[which(names(df) == time_col)] <- "ds"
@@ -35,7 +35,7 @@ timegpt_historic <- function(df, freq=NULL, id_col=NULL, time_col="ds", target_c
     names(df)[which(names(df) == id_col)] <- "unique_id"
   }
 
-  data <- .timegpt_data_prep(df, freq, id_col, time_col, target_col)
+  data <- .nixtla_data_prep(df, freq, id_col, time_col, target_col)
   freq <- data$freq
   y <- data$y
 
@@ -65,12 +65,12 @@ timegpt_historic <- function(df, freq=NULL, id_col=NULL, time_col="ds", target_c
   }
 
   # Make request ----
-  url_historic <- "https://dashboard.nixtla.io/api/timegpt_multi_series_historic"
+  url_historic <- "https://dashboard.nixtla.io/api/historic_forecast_multi_series"
   resp_hist <- httr2::request(url_historic) |>
     httr2::req_headers(
       "accept" = "application/json",
       "content-type" = "application/json",
-      "authorization" = paste("Bearer", .get_token())
+      "authorization" = paste("Bearer", .get_api_key())
     ) |>
     httr2::req_user_agent("nixtlar") |>
     httr2::req_body_json(data = timegpt_data) |>

diff --git a/R/timegpt_plot.R → R/nixtla_client_plot.R b/R/timegpt_plot.R → R/nixtla_client_plot.R
@@ -15,13 +15,13 @@
 #'
 #' @examples
 #' \dontrun{
-#'   nixtlar::nixtla_set_token("YOUR_TOKEN")
+#'   nixtlar::nixtla_set_api_key("YOUR_API_KEY")
 #'   df <- nixtlar::electricity
-#'   fcst <- nixtlar::timegpt_forecast(df, h=8, id_col="unique_id", level=c(80,95))
+#'   fcst <- nixtlar::nixtla_client_forecast(df, h=8, id_col="unique_id", level=c(80,95))
 #'   nixtlar::timegpt_plot(df, fcst, h=8, id_col="unique_id")
 #' }
 #'
-timegpt_plot <- function(df, fcst=NULL, h=NULL, id_col=NULL, time_col="ds", target_col="y", unique_ids = NULL, max_insample_length=NULL, plot_anomalies=FALSE){
+nixtla_client_plot <- function(df, fcst=NULL, h=NULL, id_col=NULL, time_col="ds", target_col="y", unique_ids = NULL, max_insample_length=NULL, plot_anomalies=FALSE){
 
   if(!tsibble::is_tsibble(df) & !is.data.frame(df)){
     stop("Only tsibbles or data frames are allowed.")

diff --git a/R/timegpt_data_prep.R → R/nixtla_data_prep.R b/R/timegpt_data_prep.R → R/nixtla_data_prep.R
@@ -13,9 +13,9 @@
 #'
 #' @examples
 #' df <- nixtlar::electricity
-#' data <- .timegpt_data_prep(df, freq="H")
+#' data <- .nixtla_data_prep(df, freq="H")
 #'
-.timegpt_data_prep <- function(df, freq, id_col, time_col, target_col){
+.nixtla_data_prep <- function(df, freq, id_col, time_col, target_col){
 
   if(!tsibble::is_tsibble(df) & !is.data.frame(df)){
     stop("Only tsibbles or data frames are allowed.")

diff --git a/R/nixtla_set_api_key.R b/R/nixtla_set_api_key.R
@@ -0,0 +1,16 @@
+#' Set API key in global environment
+#'
+#' @param api_key The user's API key. Get yours here: https://dashboard.nixtla.io/
+#'
+#' @return A message indicating the API key has been set in the global environment.
+#' @export
+#'
+#' @examples
+#' \dontrun{
+#'   nixtlar::nixtla_set_api_key("YOUR_API_KEY")
+#' }
+#'
+nixtla_set_api_key <- function(api_key) {
+  options("NIXTLA_API_KEY"=api_key)
+  message("API key has been set for the current session.")
+}
diff --git a/R/nixtla_set_token.R b/R/nixtla_set_token.R
diff --git a/R/nixtla_validate_api_key.R b/R/nixtla_validate_api_key.R
@@ -0,0 +1,30 @@
+#' Validate API key
+#'
+#' @return A status code and a message indicating whether the API key is valid.
+#' @export
+#'
+#' @examples
+#' \dontrun{
+#'   nixtlar::nixtla_set_api_key("YOUR_API_KEY")
+#'   nixtlar::nixtla_validate_api_key
+#' }
+#'
+nixtla_validate_api_key <- function(){
+
+  api_key <- .get_api_key()
+
+  url <- "https://dashboard.nixtla.io/api/forecast"
+  resp <- httr2::request(url) |>
+    httr2::req_headers(
+      Authorization = paste("Bearer", api_key)
+      ) |>
+    httr2::req_user_agent("nixtla-r") |>
+    httr2::req_perform()
+
+  status_code <- httr2::resp_status(resp)
+  if(status_code >= 200 & status_code < 300){
+    message("API key validation successful. Happy forecasting! :) \nIf you have questions or need support, please email [email protected]")
+  }else{
+    message("API key validation failed. Please go https://dashboard.nixtla.io/ to get a valid API key.")
+  }
+}
diff --git a/R/nixtla_validate_token.R b/R/nixtla_validate_token.R
diff --git a/cran-comments.md b/cran-comments.md
@@ -1,3 +1,7 @@
+## Resubmission 9 Feb 2024  
+This is a resubmission. In this version I have: 
+
+
 ## Resubmission 3 Feb 2024
 This is a resubmission. In this version I have: