[skip vbump] initial release v0.1.0 (#79)

Fix #51

Author: donyunardi

DESCRIPTION

@@ -2,10 +2,21 @@ Type: Package
 Package: teal.picks
 Title: Dataset and Variable Picker and Merge Module for 'teal'
     Applications
-Version: 0.1.0.9244
-Date: 2026-05-08
-Authors@R:
-    person("insightsengineering", , , "insightsengineering@example.com", role = c("aut", "cre"))
+Version: 0.1.0
+Date: 2026-05-07
+Authors@R: c(
+    person("Dawid", "Kaledkowski", , "dawid.kaledkowski@roche.com", role = c("aut", "cre"),
+           comment = c(ORCID = "0000-0001-9533-457X")),
+    person("Andre", "Verissimo", , "andre.verissimo@roche.com", role = "aut",
+           comment = c(ORCID = "0000-0002-2212-339X")),
+    person("Marcin", "Kosinski", , "marcin.kosinski.mk1@roche.com", role = "aut"),
+    person("Lluís", "Revilla Sancho", , "lluis.revilla_sancho@roche.com", role = "aut",
+           comment = c(ORCID = "0000-0001-9747-2570")),
+    person("Oriol", "Senan", , "oriol.senan@external.roche.com", role = "aut",
+           comment = c(ORCID = "0000-0002-9621-3371")),
+    person("Dony", "Unardi", , "unardid@gene.com", role = "rev"),
+    person("F. Hoffmann-La Roche AG", role = c("cph", "fnd"))
+  )
 Description: Allows users to interactively select datasets, variables, and
     values within 'teal' applications using a 'tidyselect'-style
     interface. Selected picks can be merged and transformed into

NEWS.md

@@ -1,4 +1,4 @@
-# teal.picks 0.1.0.9244
+# teal.picks 0.1.0
 
 ### New Features
 

R/as_picks.R

@@ -14,6 +14,7 @@
 #' conversion from [`data_extract_spec`] to [`picks`]. Unfortunately, when [`data_extract_spec`]
 #' contains [`filter_spec`] then `as.picks` is unable to provide reliable [`picks`] equivalent.
 #'
+#' @return A `picks` object when conversion is possible, otherwise `NULL` with a warning (if `quiet = FALSE`).
 #' @examples
 #' # convert des with eager select_spec
 #' as.picks(

R/call_utils.R

@@ -233,6 +233,7 @@ calls_combine_by <- function(operator, calls) {
 #' @param variables (`list` of `character`) variables to select. If list is named then
 #'  variables will be renamed if their name is different than its value
 #'  (this produces a call `select(..., <name> = <value>)`).
+#' @return `call`.
 #' @keywords internal
 .call_dplyr_select <- function(dataname, variables) {
   as.call(
@@ -250,6 +251,7 @@ calls_combine_by <- function(operator, calls) {
 #'
 #' Create a `dplyr::filter` call
 #' @param x (`list`) containing `variables` and `values`
+#' @return `call`.
 #' @keywords internal
 .call_dplyr_filter <- function(x) {
   if (any(!names(x) %in% c("variables", "values"))) {

R/interaction.R

@@ -14,6 +14,16 @@
 #'   `var2` in `vars`, or `NA` where a variable is not found.
 #'
 #' @export
+#' @examples
+#' picks(
+#'   datasets("ADAE"),
+#'   variables(
+#'     c(AGE, RACE, interaction_vars("COUNTRY", "RACE")),
+#'     selected = "COUNTRY:RACE",
+#'     multiple = TRUE
+#'   ),
+#'   values()
+#' )
 interaction_vars <- function(var1, var2, vars = tidyselect::peek_vars(fn = "interaction_vars")) {
   new_var <- c(as.character(substitute(var1)), as.character(substitute(var2)))
   result <- match(new_var, vars)

R/module_merge.R

@@ -482,6 +482,8 @@ merge_srv <- function(id,
 #'
 #' @inheritParams merge_srv
 #' @param join_keys (`join_keys`) The join keys object
+#' @return `TRUE` if validation passes, otherwise raises a validation
+#' error with details on which datasets cannot be merged and why.
 #'
 #' @keywords internal
 .validate_join_keys <- function(selectors, join_keys) {

R/module_picks.R

@@ -32,6 +32,35 @@
 #' @seealso [picks()] for creating `picks`` objects
 #'
 #' @name picks_module
+#' @examples
+#' library(shiny)
+#'
+#' example_pick <- picks(
+#'   datasets("ADSL"),
+#'   variables(selected = c("SEX", "COUNTRY", "ARMCD"))
+#' )
+#' ui <- fluidPage(
+#'   picks_ui("my_picks", picks = example_pick),
+#'   h4("Resolved picks:"),
+#'   verbatimTextOutput("result"),
+#'   h4("Table:"),
+#'   tableOutput("table")
+#' )
+#' server <- function(input, output, session) {
+#'   data <- teal.data::teal_data("ADSL" = teal.data::rADSL)
+#'   teal.data::join_keys(data) <- teal.data::default_cdisc_join_keys["ADSL"]
+#'   selectors <- picks_srv(
+#'     picks = list(my_picks = example_pick),
+#'     data = reactive(data)
+#'   )
+#'   anl <- merge_srv("merge", data = reactive(data), selectors = selectors)
+#'   output$result <- renderPrint(cat(gsub("\033\\[[0-9;]*m", "", format(selectors$my_picks()))))
+#'   output$table <- renderTable(anl$data()$anl)
+#' }
+#'
+#' if (interactive()) {
+#'   shinyApp(ui, server)
+#' }
 NULL
 
 #' @rdname picks_module
@@ -327,6 +356,7 @@ picks_srv.picks <- function(id, picks, data) {
 .pick_ui_fixed <- function(id, selected) {
   htmltools::tags$div(
     class = "form-group shiny-input-container",
+    style = "visibility: hidden; position: absolute;",
     htmltools::tags$input(
       id = id,
       disabled = "disabled",
@@ -396,6 +426,7 @@ picks_srv.picks <- function(id, picks, data) {
 #' @param rv (`reactiveVal`)
 #' @param value (`vector`)
 #' @param log (`character(1)`) message to `log_debug`
+#' @return the result of `reactiveVal` update if new value is different, `NULL` otherwise.
 #' @keywords internal
 .update_rv <- function(rv, value, log) {
   if (!isTRUE(all.equal(rv(), value, tolerance = 1e-15))) { # tolerance 1e-15 is a max precision in widgets.
@@ -420,6 +451,8 @@ picks_srv.picks <- function(id, picks, data) {
 #' @param picks_resolved (`reactiveVal`)
 #' @param old_picks (`picks`)
 #' @param data (`any` asserted further in `resolver`)
+#' @return The result of changing the `picks_resolved` `reactiveVal` given as argument.
+#' It returns `NULL` if it does nothing.
 #' @keywords internal
 .resolve <- function(selected, slot_name, picks_resolved, old_picks, data) {
   checkmate::assert_vector(selected, null.ok = TRUE)
@@ -479,7 +512,6 @@ picks_srv.picks <- function(id, picks, data) {
 #' Otherwise `default`.
 #'
 #' @keywords internal
-#'
 restoreValue <- function(value, default) { # nolint: object_name.
   checkmate::assert_character("value")
   session_default <- shiny::getDefaultReactiveDomain()

R/picks.R

@@ -20,6 +20,10 @@
 #' @param check_dataset (`logical(1)`) whether to check that the first element of `picks` is `datasets()`.
 #' This is useful to set to `FALSE` when creating picks objects that have a required dataset that is not
 #'  selected by the user and defined in the module itself.
+#' @return For `picks()` it returns an object of `picks` class, which is a list of `pick` objects with additional
+#' attributes for Shiny interactivity.
+#' For `datasets()`, `variables()`, and `values()` it returns a `pick` object with
+#' class corresponding to the type of selection including the choices and selected values.
 #' @details
 #' # `tidyselect` support
 #'
@@ -377,6 +381,8 @@ values <- function(choices = function(x) !is.na(x),
 #'
 #' Create a `pick` object
 #' @inheritParams picks
+#' @return `pick` generic object that is used by [datasets()], [variables()] and [values()]
+#' to create objects of corresponding classes.
 #' @keywords internal
 .pick <- function(choices,
                   selected,
@@ -390,7 +396,7 @@ values <- function(choices = function(x) !is.na(x),
     warning(
       warningCondition(
         paste0(
-          deparse(sys.call(-1)),
+          deparse1(sys.call(-1)),
           "\n - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't ",
           "guarantee that `selected` is a subset of `choices`."
         ),
@@ -470,6 +476,9 @@ values <- function(choices = function(x) !is.na(x),
 #' - `function` when predicate function provided (delayed)
 #' - `atomic` when vector of choices/selected provided (eager)
 #' @param x (`list`, `list of picks`, `picks`, `pick`, `$choices`, `$selected`)
+#' @return A `logical(1)` indicating if any of the elements in picks is delayed.,
+#' For a single `pick`, such as [datasets()], [variables()] or [values()],
+#' it checks if either `choices` or `selected` are delayed.
 #' @keywords internal
 .is_delayed <- function(x) {
   UseMethod(".is_delayed")

R/tidyselect-helpers.R

@@ -11,8 +11,12 @@
 #' @rdname tidyselectors
 #' @param min.len (`integer(1)`) minimal number of unique values
 #' @param max.len (`integer(1)`) maximal number of unique values
+#' @return A `tidyselector` that can be used directly in `choices` or `selected` of `variables()` in `picks()`.
 #' @export
 #' @examples
+#' # Supports tidyselect helpers, e.g. to select all categorical variables with 2 to 10 unique values
+#' dplyr::select(iris, dplyr::where(is_categorical(2, 10)))
+#'
 #' p <- picks(
 #'   datasets(is.data.frame, 2L),
 #'   variables(is_categorical(2, 10))
@@ -51,6 +55,8 @@ is_categorical <- function(min.len, max.len) {
 #' columns. An informative error is raised if the resolved column type is unsupported.
 #' @param min (`numeric(1)`) Minimal value.
 #' @param max (`numeric(1)`) Maximal value.
+#' @return A function that allows the use of a range in `choices` or `selected` of `values()` in
+#' `numeric`, `Date`, or `POSIXct` variables.
 #' @export
 #' @examples
 #' p <- picks(

R/tm_merge.R

@@ -4,6 +4,7 @@
 #'
 #' @inheritParams teal::module
 #' @param picks (`list` of `picks`)
+#' @return A `teal::module` object that merges datasets based on user selections and displays the results.
 #' @examples
 #' library(teal)
 #'