data_modify works with functions that return character vectors

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: datawizard
 Title: Easy Data Wrangling and Statistical Transformations
-Version: 0.7.1.12
+Version: 0.7.1.13
 Authors@R: c(
     person("Indrajeet", "Patil", , "[email protected]", role = "aut",
            comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets")),

R/data_modify.R

@@ -149,7 +149,17 @@ data_modify.data.frame <- function(data, ...) {
     if (!is.character(symbol)) {
       eval_symbol <- .dynEval(symbol, ifnotfound = NULL)
       if (is.character(eval_symbol)) {
-        symbol <- str2lang(paste0(names(dots)[i], " = ", eval_symbol))
+        symbol <- try(str2lang(paste0(names(dots)[i], " = ", eval_symbol)), silent = TRUE)
+        # we may have the edge-case of having a function that returns a character
+        # vector, like "new_var = sample(letters[1:3])". In this case, "eval_symbol"
+        # is of type character, but no symbol, thus str2lang() above creates a
+        # wrong pattern. We then take "eval_symbol" as character input.
+        if (inherits(symbol, "try-error")) {
+          symbol <- str2lang(paste0(
+            names(dots)[i],
+            " = c(", paste0("\"", eval_symbol, "\"", collapse = ","), ")"
+          ))
+        }
       }
     }
 

tests/testthat/test-data_modify.R

@@ -482,3 +482,11 @@ test_that("data_modify works with grouped df when overwriting existing variables
   )
   expect_equal(head(out$Sepal.Length2), 2 * c(0.53333, 0.4, 0.26667, 0.2, 0.46667, 0.73333), tolerance = 1e-3)
 })
+
+
+test_that("data_modify works with functions that return character vectors", {
+  data(iris)
+  set.seed(123)
+  out <- data_modify(iris, grp = sample(letters[1:3], nrow(iris), TRUE))
+  expect_identical(head(out$grp), c("c", "c", "c", "b", "c", "b"))
+})