add set filter

NEWS.md

@@ -2,6 +2,7 @@
 
 ### Enhancements
 
+* Added option to choose which variables can be filtered in the filter panel by using the `filterable` attributes for the per-dataset lists in the `filter` argument of `init`. 
 * `teal_module` having `data` argument in its arguments will receive a list of reactive filter data with `"code"` and `"join_keys"` attributes.
 * Updated the internals of `module_teal` to reflect changes in `teal.slice`.
 * `teal_module` having `filter_panel_api` argument in its arguments will receive a `FilterPanelAPI` object.

R/init.R

@@ -86,6 +86,9 @@
 #'     )
 #'   )
 #'   ```
+#'  By adding the `filterable` attribute it is possible to control which variables can be filtered for each
+#'  dataset. See the example below where `ADSL` can only be filtered by `AGE`, `SEX` or `RACE`.
+#'
 #' @param header (`character` or `shiny.tag`) \cr
 #'   the header of the app. Note shiny code placed here (and in the footer
 #'   argument) will be placed in the app's `ui` function so code which needs to be placed in the `ui` function
@@ -137,7 +140,7 @@
 #'     )
 #'   ),
 #'   title = "App title",
-#'   filter = list(ADSL = list(AGE = list())),
+#'   filter = list(ADSL = structure(list(AGE = list()), "filterable" = c("AGE", "SEX", "RACE"))),
 #'   header = tags$h1("Sample App"),
 #'   footer = tags$p("Copyright 2017 - 2020")
 #' )

R/module_tabs_with_filters.R

@@ -153,6 +153,12 @@ srv_tabs_with_filters <- function(id, datasets, modules, reporter = teal.reporte
     logger::log_trace(
       "srv_tabs_with_filters initializing the module with datasets { paste(datasets$datanames(), collapse = ' ') }."
     )
+
+    # set filterable variables for each dataset
+    for (filter_dataname in names(filter)) {
+      datasets$set_filterable_varnames(filter_dataname, attr(filter[[filter_dataname]], "filterable"))
+    }
+
     active_module <- srv_nested_tabs(id = "root", datasets = datasets, modules = modules, reporter = reporter)
 
     active_datanames <- eventReactive(