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# to you under the Apache License, Version 2.0 (the
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#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
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test_that("various paths in arrow_eval", {
  expect_arrow_eval_error(
    assert_is(1, "character"),
    class = "validation_error"
  )
  expect_arrow_eval_error(
    NoTaVaRiAbLe,
    class = "validation_error"
  )
  expect_arrow_eval_error(
    match.arg("z", c("a", "b")),
    class = "validation_error"
  )
  expect_arrow_eval_error(
    stop("something something NotImplementedError"),
    class = "arrow_not_supported"
  )
})

test_that("try_arrow_dplyr/abandon_ship adds the right message about collect()", {
  tester <- function(.data, arg) {
    try_arrow_dplyr({
      if (arg == 0) {
        # This one just stops and doesn't recommend calling collect()
        validation_error("arg is 0")
      } else if (arg == 1) {
        # This one recommends calling collect()
        arrow_not_supported("arg == 1")
      } else {
        # Because this one has an alternative suggested, it adds "Or, collect()"
        arrow_not_supported(
          "arg greater than 0",
          body = c(">" = "Try setting arg to -1")
        )
      }
    })
  }

  skip_if_not_available("dataset")
  ds <- InMemoryDataset$create(arrow_table(x = 1))
  for (i in 0:2) {
    expect_snapshot(tester(ds, i), error = TRUE)
  }
})

test_that("dplyr verbs error clearly on empty column names", {
  skip_if_not_available("acero")
  # GH-40303
  tbl <- example_data
  names(tbl)[1] <- ""

  # dplyr also refuses these ("Can't transform a data frame with `NA` or
  # `""` names."), but our wording differs since the input isn't a data frame
  tab <- arrow_table(tbl)
  msg <- "Can't transform data with empty"
  expect_error(tab |> mutate(z = dbl + 1), msg)
  expect_error(tab |> filter(dbl > 4), msg)
  expect_error(tab |> arrange(dbl), msg)
  expect_error(tab |> group_by(dbl), msg)

  # select() and rename() still work as an escape hatch, as in dplyr
  compare_dplyr_binding(
    .input |> select(-1) |> mutate(z = dbl + 1) |> collect(),
    tbl
  )
  compare_dplyr_binding(
    .input |> rename(int = 1) |> mutate(z = dbl + 1) |> collect(),
    tbl
  )
})