test_that("all classification datasets have minimum expected names", {
  classification_data <- list(
    isic_classification = isic_classification,
    nace_classification = nace_classification,
    naics_classification = naics_classification
  )

  actual <- vapply(
    classification_data,
    function(.x) all(c("code", "sector", "borderline") %in% names(.x)),
    FUN.VALUE = logical(1)
  )
  expect <- c(
    isic_classification = TRUE,
    nace_classification = TRUE,
    naics_classification = TRUE
  )
  expect_equal(actual, expect)
})

test_that("nace and naics are not identical (#85)", {
  expect_false(identical(nace_classification, naics_classification))
})

test_that("In classification datasets, `code` is of type 'character' (#185)", {
  datasets <- enlist_datasets("r2dii.data", "classification")
  types <- unlist(lapply(datasets, function(x) typeof(x[["code"]])))
  expect_equal(unique(types), "character")
})

test_that("In classification datasets, values of `code` are unique per sector and dataset (#229)", {
  datasets <- enlist_datasets("r2dii.data", "classification")

  # FIXME: This removes known offending datasets from the test.
  # These datasets will be deprecated. Deprecation process tracked in #329
  datasets$cnb_classification <- NULL
  datasets$isic_classification <- NULL
  datasets$sector_classifications <- NULL

  no_duplicate_codes <- lapply(datasets, function(x) {
    distinct_code_sector <- unique(x[c("code", "sector")])
    result <- subset(as.data.frame(table(distinct_code_sector$code)), Freq > 1)
    nrow(result) == 0
  })

  for (i in seq_along(no_duplicate_codes)) {
    expect_true(no_duplicate_codes[[i]], info = names(no_duplicate_codes)[i])
  }
})