Address lints.

.lintr.R

@@ -0,0 +1,21 @@
+linters <- lintr::default_linters             # -[ diff with dv.templates 3ca8d7a10cfc7ad2307644dcac603e1f1f0feb72]-
+linters <- lintr::modify_defaults(
+  linters
+  , line_length_linter = NULL                 # we see how long lines are when we write them
+  , indentation_linter = NULL
+  , trailing_whitespace_linter = NULL
+  , cyclocomp_linter = NULL                   # prevents trivial amount of nesting and long but straightforward functions
+  , object_name_linter = NULL                 # we have reasons to capitalize. nobody in our team CamelCase. shiny does
+  , object_length_linter = NULL               # we don't type long var names just because
+  , pipe_continuation_linter = NULL           # wickham being overly prescriptive
+  , trailing_blank_lines_linter = NULL        # natural extension of trailing_whitespace_linter, present on the template
+)
+
+if(identical(Sys.getenv('CI'), "true")){
+  linters <- lintr::modify_defaults(
+    linters
+    , object_usage_linter = NULL              # R lacks var declarations; it's easy to assign to the wrong variable by mistake
+  )                                           # We only disable this lint rule on github because it fails there because
+}                                             # of a long-standing lintr bug 
+
+linters

R/mock_local_filter.R

@@ -30,7 +30,7 @@ mock_local_filter_server <- function(input, output, session) {
     data_list$adae <- data_list$adae %>%
       dplyr::mutate(
         # Note: conversion below is only for mock purpose and changes the data
-        AEREL = dplyr::if_else(AEREL == "NONE", "N", "Y")
+        AEREL = dplyr::if_else(.data[["AEREL"]] == "NONE", "N", "Y")
       )
     data_list <- purrr::set_names(names(data_list)) %>%
       purrr::map(function(x) {

R/mod_clinical_timelines.R

@@ -520,13 +520,13 @@ mod_clinical_timelines_API_spec <- TC$group(
     trt_start_var = TC$col("subject_level_dataset_name", TC$or(TC$date(), TC$datetime())),
     trt_end_var = TC$col("subject_level_dataset_name", TC$or(TC$date(), TC$datetime())),
     icf_date_var = TC$col("subject_level_dataset_name", TC$or(TC$date(), TC$datetime()))
-  ) |> TC$flag('ignore'),
-  mapping = TC$group() |> TC$flag('ignore'),
-  drug_admin = TC$group() |> TC$flag('ignore'),
-  filter = TC$group() |> TC$flag('ignore'),
-  subjid_var = TC$character() |> TC$flag("optional", "ignore"), # TODO: TC$col("subject_level_dataset_name", TC$or(TC$factor(), TC$character())) |> TC$flag("subjid_var"),
-  default_plot_settings = TC$group() |> TC$flag('ignore'),
-  ms = TC$group() |> TC$flag('ignore'),
+  ) |> TC$flag("ignore"),
+  mapping = TC$group() |> TC$flag("ignore"),
+  drug_admin = TC$group() |> TC$flag("ignore"),
+  filter = TC$group() |> TC$flag("ignore"),
+  subjid_var = TC$character() |> TC$flag("optional", "ignore"), # TODO: Maybe TC$col("subject_level_dataset_name", TC$or(TC$factor(), TC$character())) |> TC$flag("subjid_var"),
+  default_plot_settings = TC$group() |> TC$flag("ignore"),
+  ms = TC$group() |> TC$flag("ignore"),
   receiver_id = TC$character() |> TC$flag("optional", "ignore")
 ) |> TC$attach_docs(mod_clinical_timelines_API_docs)
 
@@ -538,15 +538,14 @@ dataset_info_clinical_timelines <- function(basic_info, mapping, filter, ...) {
 }
 
 check_mod_clinical_timelines <- function(
-  afmm, datasets, module_id, basic_info, mapping, drug_admin, filter, subjid_var, default_plot_settings, ms, receiver_id
-) {
+    afmm, datasets, module_id, basic_info, mapping, drug_admin, filter, subjid_var, default_plot_settings, ms, receiver_id) {
   warn <- CM$container()
   err <- CM$container()
 
   # TODO: Replace this function with a generic one that performs the checks based on mod_clinical_timelines_API_spec.
   # Something along the lines of OK <- CM$check_API(mod_clinical_timelines_API_spec, args = match.call(), warn, err)
 
-  OK <- check_mod_clinical_timelines_auto(
+  OK <- check_mod_clinical_timelines_auto( # nolint
     afmm, datasets,
     module_id, basic_info, mapping, drug_admin, filter, subjid_var, default_plot_settings, ms, receiver_id,
     warn, err

R/mod_main_view.R

@@ -326,7 +326,7 @@ mod_main_view_server <- function(module_id, initial_data, changed,
         # (which is produced by a ggplot2 internal function)
         ggdata_y <- create_ggdata_y(plot_obj()$plot, input$plot_hover)
 
-        hover_info <- create_hover_info(
+        hover_info <- create_hover_info(   # nolint
           input$plot_hover,
           ggdata_y,
           initial_data(),

R/server_functions_local_filter.R

@@ -31,7 +31,7 @@ get_filter_status <- function(all_filters, chosen_filters) {
 #' @keywords internal
 set_pts <- function(status_filters, soc, prepped_data, filter) {
   if (status_filters[["soc"]] && !is.null(soc)) {
-    pt_choices <- prepped_data %>%
+    pt_choices <- prepped_data %>%                                # nolint
       dplyr::filter(.data[[filter$soc_var]] %in% soc) %>%
       dplyr::select(tidyselect::all_of(filter$pref_term_var)) %>%
       dplyr::distinct() %>%

R/server_functions_main_view.R

@@ -40,10 +40,10 @@ color_lookup <- function(groups) {
 #'
 create_plot_data <- function(work_data, time_range, filter_event) {
   if (lubridate::is.timepoint(time_range)) {
-    first <- "start_dt_var"
-    last <- "end_dt_var"
-    first_exp <- "start_exp"
-    last_exp <- "end_exp"
+    first <- "start_dt_var"   # nolint
+    last <- "end_dt_var"      # nolint
+    first_exp <- "start_exp"  # nolint
+    last_exp <- "end_exp"     # nolint
   } else {
     first <- "start_dy_var"
     last <- "end_dy_var"
@@ -429,7 +429,7 @@ create_tooltip <- function(hover, y_screen_pct) {
   # Calculate cursor position as percent
   left_pct <- (hover$x - hover$domain$left) /
     (hover$domain$right - hover$domain$left)
-  top_pct <- (hover$domain$top - hover$y) /
+  top_pct <- (hover$domain$top - hover$y) /             # nolint
     (hover$domain$top - hover$domain$bottom)
 
   # Distance from left and top side of the picture in pixels