Improvement on decorators (#822)

# Pull Request

Fixes insightsengineering/coredev-tasks#605

#### Changes description

- [x] Use updated `utils.R` functions
- [x] Source code standardization (avoids repeated complex call to
reactive)
- [x] Update documentation
- [ ] ~Revert ggplot2_args to roxygen2 `@template`~
- I think we should keep this as is, it is the recommended way by
`roxygen2` documentation.
- [x] Revisit `{lifecycle}` dependency
- [x] Remove decorators that are not present in report

#### Modules that need recheck (for reviewer):

- `tm_data_table`: decorators removed
- `tm_missing_data`: Decorators using rlisting instead of DataTable
- `tm_distribution`: Was decorating data.frames in report, moved to
rlisting
- `tm_outliers`: Code improvement

<details>

<summary>Big example app</summary>

```r
pkgload::load_all(".")

# ######################################################
#
#   _____                           _
#  |  __ \                         | |
#  | |  | | ___  ___ ___  _ __ __ _| |_ ___  _ __ ___
#  | |  | |/ _ \/ __/ _ \| '__/ _` | __/ _ \| '__/ __|
#  | |__| |  __/ (_| (_) | | | (_| | || (_) | |  \__ \
#  |_____/ \___|\___\___/|_|  \__,_|\__\___/|_|  |___/
#
#
#
#  Decorators
# #####################################################

plot_grob_decorator <- function(default_footnote = "I am a good decorator", .var_to_replace = "plot") {
  teal_transform_module(
    label = "Caption (grob)",
    ui = function(id) shiny::textInput(shiny::NS(id, "footnote"), "Footnote", value = default_footnote),
    server = function(id, data) {
      moduleServer(id, function(input, output, session) {
        logger::log_info("🟠 plot_grob with default: {default_footnote}!", namespace = "teal.modules.general")
        reactive({
          req(data(), input$footnote)
          logger::log_info("changing the footnote {default_footnote}", namespace = "teal.modules.general")
          teal.code::eval_code(data(), substitute(
            {
              footnote_grob <- grid::textGrob(footnote, x = 0, hjust = 0, gp = grid::gpar(fontsize = 10, fontface = "italic", col = "gray50"))
              # Arrange the plot and footnote
              .var_to_replace <- gridExtra::arrangeGrob(
                .var_to_replace,
                footnote_grob,
                ncol = 1,
                heights = grid::unit.c(grid::unit(1, "npc") - grid::unit(1, "lines"), grid::unit(1, "lines"))
              )
            },
            env = list(
              footnote = input$footnote,
              .var_to_replace = as.name(.var_to_replace)
            )))
        })
      })
    }
  )
}
caption_decorator <- function(default_caption = "I am a good decorator", .var_to_replace = "plot") {
  teal_transform_module(
    label = "Caption",
    ui = function(id) shiny::textInput(shiny::NS(id, "footnote"), "Footnote", value = default_caption),
    server = make_teal_transform_server(
      substitute({
        my_name <- .var_name
        .var_to_replace <- .var_to_replace + ggplot2::labs(caption = footnote)
      }, env = list(.var_to_replace = as.name(.var_to_replace), .var_name = .var_to_replace))
    )
  )
}

treelis_subtitle_decorator <- function(default_caption = "I am a good decorator", .var_to_replace = "plot") {
  teal_transform_module(
    label = "Caption",
    ui = function(id) shiny::textInput(shiny::NS(id, "footnote"), "Footnote", value = default_caption),
    server = make_teal_transform_server(
      substitute({
        .var_to_replace <- update(.var_to_replace, sub = footnote)
      }, env = list(.var_to_replace = as.name(.var_to_replace)))
    )
  )
}

insert_rrow_decorator <- function(default_caption = "I am a good new row", .var_to_replace = "table") {
  teal_transform_module(
    label = "New row",
    ui = function(id) shiny::textInput(shiny::NS(id, "new_row"), "New row", value = default_caption),
    server = make_teal_transform_server(
      substitute({
        .var_to_replace <- rtables::insert_rrow(.var_to_replace, rtables::rrow(new_row))
      }, env = list(.var_to_replace = as.name(.var_to_replace)))
    )
  )
}

rlisting_decorator <- function(default_caption = "I am a good new row", .var_to_replace = "table") {
  teal_transform_module(
    label = "New row",
    ui = function(id) shiny::textInput(shiny::NS(id, "new_row"), "New row", value = default_caption),
    server = make_teal_transform_server(
      substitute({
        rlistings::main_title(.var_to_replace) <- new_row
      }, env = list(.var_to_replace = as.name(.var_to_replace)))
    )
  )
}
do_nothing_decorator <- teal_transform_module(server = function(id, data) moduleServer(id, function(input, output, session) data))

# ##########################################
#
#   _             _      _       _
#  | |           | |    | |     | |
#  | |_ ___  __ _| |  __| | __ _| |_ __ _
#  | __/ _ \/ _` | | / _` |/ _` | __/ _` |
#  | ||  __/ (_| | || (_| | (_| | || (_| |
#   \__\___|\__,_|_| \__,_|\__,_|\__\__,_|
#                ______
#               |______|
#
#  teal_data
# #########################################

data <- teal_data(join_keys = default_cdisc_join_keys[c("ADSL", "ADRS")])
data <- within(data, {
  require(nestcolor)
  ADSL <- rADSL
  ADRS <- rADRS
})

# For tm_outliers
fact_vars_adsl <- names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
vars <- choices_selected(variable_choices(data[["ADSL"]], fact_vars_adsl))

# For tm_g_distribution

vars1 <- choices_selected(
  variable_choices(data[["ADSL"]], c("ARM", "COUNTRY", "SEX")),
  selected = NULL
)


init(
  data = data,
  modules = modules(
    # ###################################################
    #
    #                                    _
    #                                   (_)
    #   _ __ ___  __ _ _ __ ___  ___ ___ _  ___  _ __
    #  | '__/ _ \/ _` | '__/ _ \/ __/ __| |/ _ \| '_ \
    #  | | |  __/ (_| | | |  __/\__ \__ \ | (_) | | | |
    #  |_|  \___|\__, |_|  \___||___/___/_|\___/|_| |_|
    #             __/ |
    #            |___/
    #
    #  regression
    # ##################################################
    tm_a_regression(
      label = "Regression",
      response = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variable:",
          choices = "BMRKR1",
          selected = "BMRKR1",
          multiple = FALSE,
          fixed = TRUE
        )
      ),
      regressor = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variables:",
          choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
          selected = "AGE",
          multiple = TRUE,
          fixed = FALSE
        )
      ),
      decorators = list(caption_decorator("I am Regression", "plot"))
    ),
    # #########################################################
    #
    #       _ _     _        _ _           _   _
    #      | (_)   | |      (_) |         | | (_)
    #    __| |_ ___| |_ _ __ _| |__  _   _| |_ _  ___  _ __
    #   / _` | / __| __| '__| | '_ \| | | | __| |/ _ \| '_ \
    #  | (_| | \__ \ |_| |  | | |_) | |_| | |_| | (_) | | | |
    #   \__,_|_|___/\__|_|  |_|_.__/ \__,_|\__|_|\___/|_| |_|
    #
    #
    #
    #  distribution
    # ########################################################
    tm_g_distribution(
      dist_var = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
          selected = "BMRKR1",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      strata_var = data_extract_spec(
        dataname = "ADSL",
        filter = filter_spec(
          vars = vars1,
          multiple = TRUE
        )
      ),
      group_var = data_extract_spec(
        dataname = "ADSL",
        filter = filter_spec(
          vars = vars1,
          multiple = TRUE
        )
      ),
      decorators = list(
        histogram_plot = caption_decorator("I am density!", "histogram_plot"),
        qq_plot = caption_decorator("I am QQ!", "qq_plot"),
        summary_table = rlisting_decorator("summary row", "summary_table"),
        test_table = rlisting_decorator("test row", "test_table")
      )
    ),
    # ####################
    #
    #
    #
    #   _ __   ___ __ _
    #  | '_ \ / __/ _` |
    #  | |_) | (_| (_| |
    #  | .__/ \___\__,_|
    #  | |
    #  |_|
    #
    #  pca
    # ###################
    tm_a_pca(
      "PCA",
      dat = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data = data[["ADSL"]], c("BMRKR1", "AGE", "EOSDY")),
          selected = c("BMRKR1", "AGE")
        )
      ),
      decorators = list(
        elbow_plot = caption_decorator("I am PCA / elbow", "elbow_plot"),
        circle_plot = caption_decorator("I am a PCA / circle", "circle_plot"),
        biplot = caption_decorator("I am a PCA / bipot", "biplot"),
        eigenvector_plot = caption_decorator("I am a PCA / eigenvector", "eigenvector_plot")
      )
    ),
    ######################################
    #
    #               _   _ _
    #              | | | (_)
    #    ___  _   _| |_| |_  ___ _ __ ___
    #   / _ \| | | | __| | |/ _ \ '__/ __|
    #  | (_) | |_| | |_| | |  __/ |  \__ \
    #   \___/ \__,_|\__|_|_|\___|_|  |___/
    #
    #
    #
    #  outliers
    # #####################################
    tm_outliers(
      outlier_var = list(
        data_extract_spec(
          dataname = "ADSL",
          select = select_spec(
            label = "Select variable:",
            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
            selected = "AGE",
            multiple = FALSE,
            fixed = FALSE
          )
        )
      ),
      categorical_var = list(
        data_extract_spec(
          dataname = "ADSL",
          filter = filter_spec(
            vars = vars,
            choices = value_choices(data[["ADSL"]], vars$selected),
            selected = value_choices(data[["ADSL"]], vars$selected),
            multiple = TRUE
          )
        )
      ),
      decorators = list(
        box_plot = caption_decorator("I am a good decorator", "box_plot"),
        density_plot = caption_decorator("I am a good decorator", "density_plot"),
        cumulative_plot = caption_decorator("I am a good decorator", "cumulative_plot"),
        table = rlisting_decorator("table row", "table")
      )
    ),
    # #######################################################
    #
    #                            _       _   _
    #                           (_)     | | (_)
    #    __ _ ___ ___  ___   ___ _  __ _| |_ _  ___  _ __
    #   / _` / __/ __|/ _ \ / __| |/ _` | __| |/ _ \| '_ \
    #  | (_| \__ \__ \ (_) | (__| | (_| | |_| | (_) | | | |
    #   \__,_|___/___/\___/ \___|_|\__,_|\__|_|\___/|_| |_|
    #
    #
    #
    #  association
    # ######################################################
    tm_g_association(
      ref = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(
            data[["ADSL"]],
            c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
          ),
          selected = "RACE"
        )
      ),
      vars = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(
            data[["ADSL"]],
            c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
          ),
          selected = "BMRKR2",
          multiple = TRUE
        )
      ),
      decorators = list(plot_grob_decorator("I am a good grob (association)"))
    ),
    # ########################################################
    #
    #                                 _        _     _
    #                                | |      | |   | |
    #    ___ _ __ ___  ___ ___ ______| |_ __ _| |__ | | ___
    #   / __| '__/ _ \/ __/ __|______| __/ _` | '_ \| |/ _ \
    #  | (__| | | (_) \__ \__ \      | || (_| | |_) | |  __/
    #   \___|_|  \___/|___/___/       \__\__,_|_.__/|_|\___|
    #
    #
    #
    #  cross-table
    # #######################################################
    tm_t_crosstable(
      label = "Cross Table",
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], subset = function(data) {
            idx <- !vapply(data, inherits, logical(1), c("Date", "POSIXct", "POSIXlt"))
            return(names(data)[idx])
          }),
          selected = "COUNTRY",
          multiple = TRUE,
          ordered = TRUE
        )
      ),
      y = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], subset = function(data) {
            idx <- vapply(data, is.factor, logical(1))
            return(names(data)[idx])
          }),
          selected = "SEX"
        )
      ),
      decorators = list(insert_rrow_decorator("I am a good new row"))
    ),
    # #######################################################################################
    #
    #                 _   _                  _       _                     _        _
    #                | | | |                | |     | |                   | |      (_)
    #   ___  ___ __ _| |_| |_ ___ _ __ _ __ | | ___ | |_   _ __ ___   __ _| |_ _ __ ___  __
    #  / __|/ __/ _` | __| __/ _ \ '__| '_ \| |/ _ \| __| | '_ ` _ \ / _` | __| '__| \ \/ /
    #  \__ \ (_| (_| | |_| ||  __/ |  | |_) | | (_) | |_  | | | | | | (_| | |_| |  | |>  <
    #  |___/\___\__,_|\__|\__\___|_|  | .__/|_|\___/ \__| |_| |_| |_|\__,_|\__|_|  |_/_/\_\
    #                                 | |
    #                                 |_|
    #
    #  scatterplot matrix
    # ######################################################################################
    tm_g_scatterplotmatrix(
      label = "Scatterplot matrix",
      variables = list(
        data_extract_spec(
          dataname = "ADSL",
          select = select_spec(
            choices = variable_choices(data[["ADSL"]]),
            selected = c("AGE", "RACE", "SEX"),
            multiple = TRUE,
            ordered = TRUE
          )
        ),
        data_extract_spec(
          dataname = "ADRS",
          filter = filter_spec(
            label = "Select endpoints:",
            vars = c("PARAMCD", "AVISIT"),
            choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
            selected = "INVET - END OF INDUCTION",
            multiple = TRUE
          ),
          select = select_spec(
            choices = variable_choices(data[["ADRS"]]),
            selected = c("AGE", "AVAL", "ADY"),
            multiple = TRUE,
            ordered = TRUE
          )
        )
      ),
      decorators = list(treelis_subtitle_decorator("I am a Scatterplot matrix", "plot"))
    ),
    # #############################################
    #
    #
    #
    #   _ __ ___  ___ _ __   ___  _ __  ___  ___
    #  | '__/ _ \/ __| '_ \ / _ \| '_ \/ __|/ _ \
    #  | | |  __/\__ \ |_) | (_) | | | \__ \  __/
    #  |_|  \___||___/ .__/ \___/|_| |_|___/\___|
    #                | |
    #                |_|
    #
    #  response
    # ############################################
    tm_g_response(
      label = "Response",
      response = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("BMRKR2", "COUNTRY")))
      ),
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")), selected = "RACE")
      ),
      decorators = list(caption_decorator("I am a Response", "plot"))
    ),
    # ############################################
    #
    #   _     _                 _       _
    #  | |   (_)               (_)     | |
    #  | |__  ___   ____ _ _ __ _  __ _| |_ ___
    #  | '_ \| \ \ / / _` | '__| |/ _` | __/ _ \
    #  | |_) | |\ V / (_| | |  | | (_| | ||  __/
    #  |_.__/|_| \_/ \__,_|_|  |_|\__,_|\__\___|
    #
    #
    #
    #  bivariate
    # ###########################################
    tm_g_bivariate(
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "AGE")
      ),
      y = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "SEX")
      ),
      row_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "ARM")
      ),
      col_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "COUNTRY")
      ),
      decorators = list(caption_decorator("I am a Bivariate", "plot"))
    ),
    #####################################################
    #
    #                 _   _                  _       _
    #                | | | |                | |     | |
    #   ___  ___ __ _| |_| |_ ___ _ __ _ __ | | ___ | |_
    #  / __|/ __/ _` | __| __/ _ \ '__| '_ \| |/ _ \| __|
    #  \__ \ (_| (_| | |_| ||  __/ |  | |_) | | (_) | |_
    #  |___/\___\__,_|\__|\__\___|_|  | .__/|_|\___/ \__|
    #                                 | |
    #                                 |_|
    #
    #  scatterplot
    # ####################################################
    tm_g_scatterplot(
      label = "Scatterplot",
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")))
      ),
      y = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
          selected = "BMRKR1"
        )
      ),
      color_by = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2", "RACE", "REGION1")),
          selected = NULL
        )
      ),
      size_by = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")))
      ),
      row_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("BMRKR2", "RACE", "REGION1")),
          selected = NULL
        )
      ),
      col_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("BMRKR2", "RACE", "REGION1")),
          selected = NULL
        )
      ),
      decorators = list(caption_decorator("I am a scatterplot", "plot"))
    ),
    # ##############################################################
    #
    #             _         _                    _       _
    #            (_)       (_)                  | |     | |
    #   _ __ ___  _ ___ ___ _ _ __   __ _     __| | __ _| |_ __ _
    #  | '_ ` _ \| / __/ __| | '_ \ / _` |   / _` |/ _` | __/ _` |
    #  | | | | | | \__ \__ \ | | | | (_| |  | (_| | (_| | || (_| |
    #  |_| |_| |_|_|___/___/_|_| |_|\__, |   \__,_|\__,_|\__\__,_|
    #                                __/ |_____
    #                               |___/______|
    #
    #  missing_data
    # #############################################################
    tm_missing_data(
      label = "Missing data",
      decorators = list(
        summary_plot = plot_grob_decorator("A", "summary_plot"),
        combination_plot = plot_grob_decorator("B", "combination_plot"),
        summary_table = rlisting_decorator("table row", "table"),
        by_subject_plot = caption_decorator("by_subject_plot")
      )
    )
  )
) |> shiny::runApp()
```

</details>

---------

Signed-off-by: André Veríssimo <[email protected]>
Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Lluís Revilla <[email protected]>

Author: 3 people

DESCRIPTION

@@ -35,7 +35,7 @@ Imports:
     DT (>= 0.13),
     forcats (>= 1.0.0),
     grid,
-    lifecycle (>= 0.2.0),
+    rlistings (>= 0.2.8),
     scales,
     shinyjs,
     shinyTree (>= 0.2.8),
@@ -66,6 +66,7 @@ Suggests:
     jsonlite,
     knitr (>= 1.42),
     lattice (>= 0.18-4),
+    lifecycle (>= 0.2.0),
     logger (>= 0.2.0),
     MASS,
     nestcolor (>= 0.1.0),

R/roxygen2_templates.R

@@ -1,18 +1,4 @@
 # nocov start
-roxygen_decorators_param <- function(module_name) {
-  paste(
-    sep = " ",
-    lifecycle::badge("experimental"),
-    " (`list` of `teal_transform_module`, named `list` of `teal_transform_module` or",
-    "`NULL`) optional, if not `NULL`, decorator for tables or plots included in the module.",
-    "When a named list of `teal_transform_module`, the decorators are applied to the",
-    "respective output objects.\n\n",
-    "Otherwise, the decorators are applied to all objects, which is equivalent as using the name `default`.\n\n",
-    sprintf("See section \"Decorating `%s`\"", module_name),
-    "below for more details."
-  )
-}
-
 roxygen_ggplot2_args_param <- function(...) {
   paste(
     sep = " ",
@@ -21,7 +7,7 @@ roxygen_ggplot2_args_param <- function(...) {
     "The argument is merged with options variable `teal.ggplot2_args` and default module setup.\n\n",
     sprintf(
       "List names should match the following: `c(\"default\", %s)`.\n\n",
-      paste("\"", unlist(rlang::list2(...)), "\"", collapse = ", ", sep = "")
+      paste("\"", unlist(list(...)), "\"", collapse = ", ", sep = "")
     ),
     "For more details see the vignette: `vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\")`."
   )

R/tm_a_pca.R

@@ -14,11 +14,10 @@
 #' - If vector of `length == 1` then the font sizes will have a fixed size.
 #' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
 #' @param ggplot2_args `r roxygen_ggplot2_args_param("Elbow plot", "Circle plot", "Biplot", "Eigenvector plot")`
-#' @param decorators `r roxygen_decorators_param("tm_a_pca")`
 #'
 #' @inherit shared_params return
 #'
-#' @section Decorating `tm_a_pca`:
+#' @section Decorating Module:
 #'
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `elbow_plot` (`ggplot2`)
@@ -1121,9 +1120,12 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
       )
     })
 
+    # Render R code.
+    source_code_r <- reactive(teal.code::get_code(req(decorated_output_q())))
+
     teal.widgets::verbatim_popup_srv(
       id = "rcode",
-      verbatim_content = reactive(teal.code::get_code(req(decorated_output_q()))),
+      verbatim_content = source_code_r,
       title = "R Code for PCA"
     )
 
@@ -1146,7 +1148,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
           card$append_text("Comment", "header3")
           card$append_text(comment)
         }
-        card$append_src(teal.code::get_code(req(decorated_output_q())))
+        card$append_src(source_code_r())
         card
       }
       teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)

R/tm_a_regression.R

@@ -40,11 +40,10 @@
 # nolint start: line_length.
 #' @param ggplot2_args `r roxygen_ggplot2_args_param("Response vs Regressor", "Residuals vs Fitted", "Scale-Location", "Cook's distance", "Residuals vs Leverage", "Cook's dist vs Leverage")`
 # nolint end: line_length.
-#' @param decorators `r roxygen_decorators_param("tm_a_regression")`
 #'
 #' @inherit shared_params return
 #'
-#' @section Decorating `tm_a_regression`:
+#' @section Decorating Module:
 #'
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`ggplot2`)
@@ -1006,9 +1005,12 @@ srv_a_regression <- function(id,
       )
     })
 
+    # Render R code.
+    source_code_r <- reactive(teal.code::get_code(req(decorated_output_q())))
+
     teal.widgets::verbatim_popup_srv(
       id = "rcode",
-      verbatim_content = reactive(teal.code::get_code(req(decorated_output_q()))),
+      verbatim_content = source_code_r,
       title = "R code for the regression plot",
     )
 
@@ -1027,7 +1029,7 @@ srv_a_regression <- function(id,
           card$append_text("Comment", "header3")
           card$append_text(comment)
         }
-        card$append_src(teal.code::get_code(req(decorated_output_q())))
+        card$append_src(source_code_r())
         card
       }
       teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)

R/tm_data_table.R

@@ -26,18 +26,9 @@
 #' `list(searching = FALSE, pageLength = 30, lengthMenu = c(5, 15, 30, 100), scrollX = TRUE)`
 #' @param server_rendering (`logical`) should the data table be rendered server side
 #' (see `server` argument of [DT::renderDataTable()])
-#' @param decorators `r roxygen_decorators_param("tm_data_table")`
 #'
 #' @inherit shared_params return
 #'
-#' @section Decorating `tm_data_table`:
-#'
-#' This module generates the following objects, which can be modified in place using decorators:
-#' - `table` ([DT::datatable()])
-#'
-#' For additional details and examples of decorators, refer to the vignette
-#' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
-#'
 #' @examplesShinylive
 #' library(teal.modules.general)
 #' interactive <- function() TRUE
@@ -105,8 +96,7 @@ tm_data_table <- function(label = "Data Table",
                           ),
                           server_rendering = FALSE,
                           pre_output = NULL,
-                          post_output = NULL,
-                          decorators = NULL) {
+                          post_output = NULL) {
   message("Initializing tm_data_table")
 
   # Start of assertions
@@ -132,8 +122,6 @@ tm_data_table <- function(label = "Data Table",
   checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
-  decorators <- normalize_decorators(decorators)
-  assert_decorators(decorators, null.ok = TRUE, "table")
   # End of assertions
 
   ans <- module(
@@ -146,8 +134,7 @@ tm_data_table <- function(label = "Data Table",
       datasets_selected = datasets_selected,
       dt_args = dt_args,
       dt_options = dt_options,
-      server_rendering = server_rendering,
-      decorators = decorators
+      server_rendering = server_rendering
     ),
     ui_args = list(
       pre_output = pre_output,
@@ -197,8 +184,7 @@ srv_page_data_table <- function(id,
                                 variables_selected,
                                 dt_args,
                                 dt_options,
-                                server_rendering,
-                                decorators) {
+                                server_rendering) {
   checkmate::assert_class(data, "reactive")
   checkmate::assert_class(isolate(data()), "teal_data")
   moduleServer(id, function(input, output, session) {
@@ -251,8 +237,7 @@ srv_page_data_table <- function(id,
                     ui_data_table(
                       id = session$ns(x),
                       choices = choices,
-                      selected = variables_selected,
-                      decorators = decorators
+                      selected = variables_selected
                     )
                   )
                 )
@@ -274,19 +259,15 @@ srv_page_data_table <- function(id,
           if_distinct = if_distinct,
           dt_args = dt_args,
           dt_options = dt_options,
-          server_rendering = server_rendering,
-          decorators = decorators
+          server_rendering = server_rendering
         )
       }
     )
   })
 }
 
 # UI function for the data_table module
-ui_data_table <- function(id,
-                          choices,
-                          selected,
-                          decorators) {
+ui_data_table <- function(id, choices, selected) {
   ns <- NS(id)
 
   if (!is.null(selected)) {
@@ -298,7 +279,6 @@ ui_data_table <- function(id,
   tagList(
     teal.widgets::get_dt_rows(ns("data_table"), ns("dt_rows")),
     fluidRow(
-      ui_decorate_teal_data(ns("decorator"), decorators = select_decorators(decorators, "table")),
       teal.widgets::optionalSelectInput(
         ns("variables"),
         "Select variables:",
@@ -322,8 +302,7 @@ srv_data_table <- function(id,
                            if_distinct,
                            dt_args,
                            dt_options,
-                           server_rendering,
-                           decorators) {
+                           server_rendering) {
   moduleServer(id, function(input, output, session) {
     iv <- shinyvalidate::InputValidator$new()
     iv$add_rule("variables", shinyvalidate::sv_required("Please select valid variable names"))
@@ -367,15 +346,9 @@ srv_data_table <- function(id,
       )
     })
 
-    decorated_data_table_data <- srv_decorate_teal_data(
-      id = "decorator",
-      data = data_table_data,
-      decorators = select_decorators(decorators, "table")
-    )
-
     output$data_table <- DT::renderDataTable(server = server_rendering, {
       teal::validate_inputs(iv)
-      req(decorated_data_table_data())[["table"]]
+      req(data_table_data())[["table"]]
     })
   })
 }

R/tm_g_association.R

@@ -21,11 +21,10 @@
 #' Default to `"gray"`.
 #'
 #' @param ggplot2_args `r roxygen_ggplot2_args_param("Bivariate1", "Bivariate2")`
-#' @param decorators `r roxygen_decorators_param("tm_g_association")`
 #'
 #' @inherit shared_params return
 #'
-#' @section Decorating `tm_g_association`:
+#' @section Decorating Module:
 #'
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`grob` created with [ggplot2::ggplotGrob()])
@@ -526,9 +525,12 @@ srv_tm_g_association <- function(id,
       teal.code::dev_suppress(output_q()[["title"]])
     })
 
+    # Render R code.
+    source_code_r <- reactive(teal.code::get_code(req(decorated_output_grob_q())))
+
     teal.widgets::verbatim_popup_srv(
       id = "rcode",
-      verbatim_content = reactive(teal.code::get_code(req(decorated_output_grob_q()))),
+      verbatim_content = source_code_r,
       title = "Association Plot"
     )
 
@@ -547,7 +549,7 @@ srv_tm_g_association <- function(id,
           card$append_text("Comment", "header3")
           card$append_text(comment)
         }
-        card$append_src(teal.code::get_code(req(decorated_output_grob_q())))
+        card$append_src(source_code_r())
         card
       }
       teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)

R/tm_g_bivariate.R

@@ -43,11 +43,10 @@
 #' @param free_y_scales (`logical`) optional, whether Y scaling shall be changeable.
 #' Does not allow scaling to be changed by default (`FALSE`).
 #' @param swap_axes (`logical`) optional, whether to swap X and Y axes. Defaults to `FALSE`.
-#' @param decorators `r roxygen_decorators_param("tm_g_bivariate")`
 #'
 #' @inherit shared_params return
 #'
-#' @section Decorating `tm_g_bivariate`:
+#' @section Decorating Module:
 #'
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`ggplot2`)
@@ -715,9 +714,12 @@ srv_g_bivariate <- function(id,
       width = plot_width
     )
 
+    # Render R code.
+    source_code_r <- reactive(teal.code::get_code(req(decorated_output_q_facets())))
+
     teal.widgets::verbatim_popup_srv(
       id = "rcode",
-      verbatim_content = reactive(teal.code::get_code(req(decorated_output_q_facets()))),
+      verbatim_content = source_code_r,
       title = "Bivariate Plot"
     )
 
@@ -736,7 +738,7 @@ srv_g_bivariate <- function(id,
           card$append_text("Comment", "header3")
           card$append_text(comment)
         }
-        card$append_src(teal.code::get_code(req(decorated_output_q_facets)))
+        card$append_src(source_code_r())
         card
       }
       teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)