test_generate_concept_cohort_set <- function(con, cdm_schema, write_schema) {
  # if (dbms(con) == "bigquery") return(skip("failing test"))

  if (dbms(con) == "bigquery") {
    return(skip("failing test"))
  }

  # withr::local_options("CDMConnector.cohort_as_temp" = FALSE) # temp cohort tables are not implemented yet
  cdm <- cdm_from_con(con,
    cdm_schema = cdm_schema,
    write_schema = write_schema
  )

  # check that we have records
  cdm$condition_occurrence %>%
    dplyr::filter(condition_concept_id == 192671) %>%
    dplyr::count() %>%
    dplyr::pull("n") %>%
    expect_gt(10)

  # default (no descendants) ----
  cdm <- generateConceptCohortSet(
    cdm = cdm,
    conceptSet = list(gibleed = 192671),
    name = "gibleed",
    overwrite = TRUE
  )

  cohort <- readCohortSet(system.file("cohorts3", package = "CDMConnector")) %>%
    dplyr::filter(cohort_name == "GiBleed_default") %>%
    dplyr::mutate(cohort_definition_id = 1L)

  cdm <- generateCohortSet(cdm, cohortSet = cohort, name = "gibleed2", overwrite = TRUE)

  expected <- dplyr::collect(cdm$gibleed2) %>%
    dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
    dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

  actual <- dplyr::collect(cdm$gibleed) %>%
    dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
    dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

  expect_true(nrow(expected) > 0)
  expect_true(nrow(actual) == nrow(expected))

  # setdiff(unique(expected$subject_id), unique(actual$subject_id))
  # setdiff(unique(actual$subject_id), unique(expected$subject_id))

  expect_setequal(unique(expected$subject_id), unique(actual$subject_id))
  expect_equal(actual, expected)


  expect_error({
    # should be fail fast case
    generateConceptCohortSet(
      cdm = cdm,
      conceptSet = list(gibleed = 192671),
      name = "gibleed",
      overwrite = FALSE
    )
  })


  cdm <- generateConceptCohortSet(cdm,
    conceptSet = list(gibleed = 192671), name = "gibleed3",
    requiredObservation = c(2, 2),
    overwrite = TRUE
  )

  cdm <- generateConceptCohortSet(cdm,
    conceptSet = list(gibleed = 192671), name = "gibleed4",
    requiredObservation = c(2, 200),
    overwrite = TRUE
  )

  expect_identical(cohortSet(cdm$gibleed4)$limit, "first")
  expect_identical(cohortSet(cdm$gibleed4)$end, "observation_period_end_date")
  expect_identical(cohortSet(cdm$gibleed4)$prior_observation, 2)
  expect_identical(cohortSet(cdm$gibleed4)$future_observation, 200)

  expect_true({
    cohort_count(cdm$gibleed3)$number_records >= cohort_count(cdm$gibleed4)$number_records
  })

  # default (with descendants) ----
  if (FALSE) {
    # if (rlang::is_installed("Capr")) { # failing for some reason. gives different results.
    # we need Capr to include descendants
    cdm <- generateConceptCohortSet(
      cdm = cdm,
      conceptSet = list(gibleed = Capr::cs(Capr::descendants(192671), name = "gibleed")),
      name = "gibleed",
      overwrite = TRUE
    )

    cohort <- readCohortSet(system.file("cohorts3", package = "CDMConnector")) %>%
      dplyr::filter(cohort_name == "GiBleed_default_with_descendants") %>%
      dplyr::mutate(cohort_definition_id = 1L)

    cdm <- generateCohortSet(cdm, cohortSet = cohort, name = "gibleed2", overwrite = TRUE)

    expected <- dplyr::collect(cdm$gibleed2) %>%
      dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
      dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

    actual <- dplyr::collect(cdm$gibleed) %>%
      dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
      dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

    # setdiff(unique(expected$subject_id), unique(actual$subject_id))
    # setdiff(unique(actual$subject_id), unique(expected$subject_id))
    expect_true(nrow(expected) > 0)
    expect_true(nrow(actual) == nrow(expected))

    expect_setequal(unique(expected$subject_id), unique(actual$subject_id))
    expect_equal(actual, expected)
  }

  # all occurrences (no descendants) ----
  cdm <- generateConceptCohortSet(
    cdm = cdm,
    conceptSet = list(gibleed = 192671),
    name = "gibleed",
    limit = "all",
    overwrite = TRUE
  )

  cohort <- readCohortSet(system.file("cohorts3", package = "CDMConnector")) %>%
    dplyr::filter(cohort_name == "GiBleed_all") %>%
    dplyr::mutate(cohort_definition_id = 1L)

  cdm <- generateCohortSet(cdm, cohortSet = cohort, name = "gibleed2", overwrite = TRUE)

  expect_equal(
    as.integer(dplyr::pull(dplyr::tally(cdm$gibleed2), "n")),
    as.integer(dplyr::pull(dplyr::tally(cdm$gibleed), "n"))
  )

  expected <- dplyr::collect(cdm$gibleed2) %>%
    dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
    dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

  actual <- dplyr::collect(cdm$gibleed) %>%
    dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
    dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

  # setdiff(unique(expected$subject_id), unique(actual$subject_id))
  # setdiff(unique(actual$subject_id), unique(expected$subject_id))

  expect_true(nrow(expected) > 0)
  expect_true(nrow(actual) == nrow(expected))

  expect_setequal(unique(expected$subject_id), unique(actual$subject_id))
  expect_equal(actual, expected)

  # all occurrences (no descendants) fixed end date ----
  cdm <- generateConceptCohortSet(
    cdm = cdm,
    conceptSet = list(gibleed = 192671),
    name = "gibleed",
    limit = "all",
    end = 10,
    overwrite = TRUE
  )

  cohort <- readCohortSet(system.file("cohorts3", package = "CDMConnector")) %>%
    dplyr::filter(cohort_name == "GiBleed_all_end10") %>%
    dplyr::mutate(cohort_definition_id = 1L)

  cdm <- generateCohortSet(cdm, cohortSet = cohort, name = "gibleed2", overwrite = TRUE)

  expect_equal(
    as.integer(dplyr::pull(dplyr::tally(cdm$gibleed2), "n")),
    as.integer(dplyr::pull(dplyr::tally(cdm$gibleed), "n"))
  )

  expected <- dplyr::collect(cdm$gibleed2) %>%
    dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
    dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

  actual <- dplyr::collect(cdm$gibleed) %>%
    dplyr::arrange(.data$cohort_definition_id, .data$subject_id, .data$cohort_start_date, .data$cohort_end_date) %>%
    dplyr::mutate_if(~ "integer64" %in% class(.), as.integer)

  # setdiff(unique(expected$subject_id), unique(actual$subject_id))
  # setdiff(unique(actual$subject_id), unique(expected$subject_id))

  expect_true(nrow(expected) > 0)
  expect_true(nrow(actual) == nrow(expected))

  expect_setequal(unique(expected$subject_id), unique(actual$subject_id))
  expect_equal(actual, expected)

  # clean up
  CDMConnector::dropTable(cdm, dplyr::contains("gibleed"))
}

for (dbtype in dbToTest) {
  test_that(glue::glue("{dbtype} - generateConceptCohortSet"), {
    skip_if_not_installed("CirceR")
    con <- get_connection(dbtype)
    cdm_schema <- get_cdm_schema(dbtype)
    write_schema <- get_write_schema(dbtype)
    skip_if(any(write_schema == "") || any(cdm_schema == "") || is.null(con))
    test_generate_concept_cohort_set(con, cdm_schema, write_schema)
    disconnect(con)
  })
}


test_that("missing domains produce warning", {
  con <- DBI::dbConnect(duckdb::duckdb(), eunomia_dir())
  cdm <- cdm_from_con(con, "main", "main") %>%
    cdm_select_tbl(-drug_exposure)

  expect_warning({
    cdm <- generateConceptCohortSet(cdm, conceptSet = list(celecoxib = 1118084))
  })

  DBI::dbDisconnect(con, shutdown = TRUE)
})