Fix tm_outliers module to work without join keys for single datasets

R/tm_outliers.R

@@ -438,11 +438,33 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
       }
     })
 
-    anl_merged_input <- teal.transform::merge_expression_srv(
-      selector_list = reactive_select_input,
-      datasets = data,
-      merge_function = "dplyr::inner_join"
-    )
+    anl_merged_input <- reactive({
+      dataname_first <- names(data())[[1]]
+      join_keys <- teal.data::join_keys(data())[dataname_first, dataname_first]
+
+      if (length(join_keys) == 0) {
+        # No join keys - single dataset, no merging needed
+        # Return the same structure as merge_expression_srv but with simple assignment
+        list(
+          expr = substitute(ANL <- dataname, list(dataname = as.name(dataname_first))),
+          columns_source = list(
+            outlier_var = reactive_select_input()$outlier_var()$select,
+            categorical_var = if (!is.null(reactive_select_input()$categorical_var)) {
+              names(reactive_select_input()$categorical_var()$filter)
+            } else {
+              character(0)
+            }
+          )
+        )
+      } else {
+        # Join keys exist - use merge_expression_srv
+        teal.transform::merge_expression_srv(
+          selector_list = reactive_select_input,
+          datasets = data,
+          merge_function = "dplyr::inner_join"
+        )()
+      }
+    })
 
     anl_merged_q <- reactive({
       req(anl_merged_input())
@@ -616,25 +638,33 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
       )
 
       # ANL_OUTLIER_EXTENDED is the base table
-      qenv <- teal.code::eval_code(
-        qenv,
-        substitute(
-          expr = {
-            ANL_OUTLIER_EXTENDED <- dplyr::left_join(
-              ANL_OUTLIER,
-              dplyr::select(
-                dataname,
-                dplyr::setdiff(names(dataname), dplyr::setdiff(names(ANL_OUTLIER), join_keys))
-              ),
-              by = join_keys
+      join_keys <- as.character(teal.data::join_keys(data())[dataname_first, dataname_first])
+
+      if (length(join_keys) == 0) {
+        # No join keys - single dataset, no join needed
+        qenv <- teal.code::eval_code(qenv, quote(ANL_OUTLIER_EXTENDED <- ANL_OUTLIER))
+      } else {
+        # Join keys exist - perform left join
+        qenv <- teal.code::eval_code(
+          qenv,
+          substitute(
+            expr = {
+              ANL_OUTLIER_EXTENDED <- dplyr::left_join(
+                ANL_OUTLIER,
+                dplyr::select(
+                  dataname,
+                  dplyr::setdiff(names(dataname), dplyr::setdiff(names(ANL_OUTLIER), join_keys))
+                ),
+                by = join_keys
+              )
+            },
+            env = list(
+              dataname = as.name(dataname_first),
+              join_keys = join_keys
             )
-          },
-          env = list(
-            dataname = as.name(dataname_first),
-            join_keys = as.character(teal.data::join_keys(data())[dataname_first, dataname_first])
           )
         )
-      )
+      }
 
       qenv <- if (length(categorical_var) > 0) {
         qenv <- teal.code::eval_code(

tests/testthat/test-shinytest2-tm_outliers.R

@@ -319,3 +319,69 @@ testthat::test_that("e2e - tm_outliers: Outlier table is displayed with proper c
 
   app_driver$stop()
 })
+
+testthat::test_that("e2e - tm_outliers: works without join keys", {
+  # Test for issue where tm_outliers fails if data has no joining keys
+  # This test reproduces the exact scenario described in the issue
+  testthat::skip("chromium")
+  skip_if_too_deep(5)
+
+  # Create data without join keys (as per issue description)
+  data <- teal.data::teal_data()
+  data <- within(data, {
+    CO2 <- CO2 # nolint: object_name
+  })
+  # Note: No join_keys defined here, which should NOT cause the issue after fix
+
+  vars <- teal.transform::choices_selected(
+    teal.transform::variable_choices(
+      data[["CO2"]],
+      c("Plant", "Type", "Treatment")
+    )
+  )
+
+  # This should NOT fail after the fix
+  app_driver <- init_teal_app_driver(
+    data = data,
+    modules = tm_outliers(
+      outlier_var = list(
+        teal.transform::data_extract_spec(
+          dataname = "CO2",
+          select = teal.transform::select_spec(
+            label = "Select variable:",
+            choices = teal.transform::variable_choices(data[["CO2"]], c("conc", "uptake")),
+            selected = "uptake",
+            multiple = FALSE,
+            fixed = FALSE
+          )
+        )
+      ),
+      categorical_var = list(
+        teal.transform::data_extract_spec(
+          dataname = "CO2",
+          filter = teal.transform::filter_spec(
+            vars = vars,
+            choices = teal.transform::value_choices(data[["CO2"]], vars$selected),
+            selected = teal.transform::value_choices(data[["CO2"]], vars$selected),
+            multiple = TRUE
+          )
+        )
+      ),
+      ggplot2_args = list(
+        teal.widgets::ggplot2_args(
+          labs = list(subtitle = "Plot generated by Outliers Module")
+        )
+      )
+    )
+  )
+
+  app_driver$expect_no_shiny_error()
+
+  # Verify the module loads correctly
+  testthat::expect_equal(
+    app_driver$get_text("#teal-teal_modules-active_tab .active"),
+    "Outliers Module"
+  )
+
+  app_driver$stop()
+})