more suggests packages

DESCRIPTION

@@ -13,7 +13,6 @@ Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 Imports: 
     cli,
-    dotenv,
     dplyr,
     fs,
     furrr,
@@ -22,7 +21,6 @@ Imports:
     httr,
     purrr,
     qs,
-    readr,
     rlang,
     s2,
     sf,
@@ -34,15 +32,17 @@ Imports:
 RoxygenNote: 7.2.3
 Suggests: 
     curl,
+    dotenv,
     ggplot2,
     hexbin,
     knitr,
     lwgeom,
-    rmarkdown,
     mappp,
-    tidync,
+    readr,
+    rmarkdown,
     scales,
     testthat (>= 3.0.0),
+    tidync,
     viridis
 Config/testthat/edition: 3
 Config/testthat/parallel: true

R/aqs.R

@@ -23,6 +23,7 @@
 #' get_daily_aqs("pm25", "2023")
 #' @export
 get_daily_aqs <- function(pollutant = c("pm25", "ozone", "no2"), year = as.character(2017:2023)) {
+  rlang::check_installed("readr", "to read daily AQS CSV files from the EPA.")
   pollutant <- rlang::arg_match(pollutant)
   year <- rlang::arg_match(year)
   pollutant_code <-

R/merra.R

@@ -108,6 +108,8 @@ install_merra_data <- function(merra_year = as.character(2016:2023)) {
 #' @export
 #' @rdname get_merra_data
 create_daily_merra_data <- function(merra_date) {
+  rlang::check_installed("tidync", "to read daily MERRA files.")
+  rlang::check_installed("dotenv", "to read Earthdata credentials; see Details.")
   the_date <- as.Date(merra_date)
   if (file.exists(".env")) dotenv::load_dot_env()
   earthdata_secrets <- Sys.getenv(c("EARTHDATA_USERNAME", "EARTHDATA_PASSWORD"), unset = NA)
@@ -129,7 +131,6 @@ create_daily_merra_data <- function(merra_date) {
     httr::authenticate(user = earthdata_secrets["EARTHDATA_USERNAME"], password = earthdata_secrets["EARTHDATA_PASSWORD"]),
     httr::write_disk(tf)
   )
-  rlang::check_installed("tidync", "to read daily MERRA files.")
   out <-
     tidync::tidync(tf) |>
     tidync::hyper_filter(

R/nei.R

@@ -47,6 +47,7 @@ get_nei_point_summary <- function(x, year = c("2020", "2017"), pollutant_code =
 #' @rdname get_nei_point_summary
 #' @export
 install_nei_point_data <- function(year = c("2020", "2017")) {
+  rlang::check_installed("readr", "to read and install NEI CSV files from the EPA.")
   year <- rlang::arg_match(year)
   dest_file <- fs::path(tools::R_user_dir("appc", "data"), glue::glue("nei_{year}.rds"))
   if (file.exists(dest_file)) {

justfile

@@ -50,7 +50,7 @@ train_model:
 # upload grf model and training data to current github release
 release_model:
   gh release upload v{{pkg_version}} "{{geomarker_folder}}/training_data_v{{pkg_version}}.rds"
-  gh release upload v{{pkg_version}} "{{geomarker_folder}}/rf_pm_v{{pkg_version}}.rds"
+  gh release upload v{{pkg_version}} "{{geomarker_folder}}/rf_pm_v{{pkg_version}}.qs"
 
 # install smoke data from source and upload to github release
 release_hms_smoke_data: