jared
488d03d74b
Discovery verb over the summary_categories view, grouped one row per (category, subtype). Parallels cog_gov_search: analysts use it to find the valid `category` values to pass into cog_spending(), cog_revenue(), cog_geographic_rollup(). Columns: category, category_type, subtype, n_codes, item_codes (comma-separated, alphabetical). Optional filters: type = NULL | "spending" | "revenue" pattern = regex matched case-insensitively on category The user-facing "spending" alias is translated internally to the corpus-native "expenditure" so callers don't have to learn Census vocabulary, while the returned category_type column preserves the native value for auditability. Also: fix @noRd placement in session.R so devtools::document() stops warning. Tests: +16 new / 181 total pass. check 0E/0W/0N.
63 lines
2.1 KiB
R
63 lines
2.1 KiB
R
test_that("cog_categories returns all categories grouped by subtype", {
|
|
skip_if_no_corpus()
|
|
r <- cog_categories()
|
|
expect_s3_class(r, "tbl_df")
|
|
expected <- c("category", "category_type", "subtype",
|
|
"n_codes", "item_codes")
|
|
expect_true(all(expected %in% names(r)))
|
|
expect_gt(nrow(r), 10L)
|
|
# corpus preserves Census-native "expenditure" vocabulary; the API takes
|
|
# "spending" as a friendlier alias.
|
|
expect_setequal(unique(r$category_type), c("expenditure", "revenue"))
|
|
})
|
|
|
|
test_that("cog_categories(type = 'spending') returns only expenditure rows", {
|
|
skip_if_no_corpus()
|
|
r <- cog_categories(type = "spending")
|
|
expect_true(all(r$category_type == "expenditure"))
|
|
expect_true(all(r$subtype %in% c("operations", "capital")))
|
|
})
|
|
|
|
test_that("cog_categories(type = 'revenue') returns only revenue rows", {
|
|
skip_if_no_corpus()
|
|
r <- cog_categories(type = "revenue")
|
|
expect_true(all(r$category_type == "revenue"))
|
|
expect_true(all(r$subtype %in%
|
|
c("own_source", "federal", "state", "local_aid")))
|
|
})
|
|
|
|
test_that("cog_categories(pattern = ...) filters case-insensitively", {
|
|
skip_if_no_corpus()
|
|
r <- cog_categories(pattern = "police")
|
|
expect_gt(nrow(r), 0L)
|
|
expect_true(all(grepl("Police", r$category, ignore.case = TRUE)))
|
|
})
|
|
|
|
test_that("cog_categories has one row per (category, subtype)", {
|
|
skip_if_no_corpus()
|
|
r <- cog_categories()
|
|
key <- paste(r$category, r$subtype, sep = "|")
|
|
expect_equal(length(key), length(unique(key)))
|
|
})
|
|
|
|
test_that("cog_categories item_codes is non-empty comma-separated string", {
|
|
skip_if_no_corpus()
|
|
r <- cog_categories()
|
|
expect_true(all(nzchar(r$item_codes)))
|
|
expect_true(all(r$n_codes >= 1L))
|
|
# n_codes should equal count of commas + 1
|
|
expect_equal(r$n_codes,
|
|
vapply(strsplit(r$item_codes, ","), length, integer(1)))
|
|
})
|
|
|
|
test_that("cog_categories sorted by category_type, category, subtype", {
|
|
skip_if_no_corpus()
|
|
r <- cog_categories()
|
|
sorted <- r[order(r$category_type, r$category, r$subtype), ]
|
|
expect_identical(r, sorted)
|
|
})
|
|
|
|
test_that("cog_categories rejects invalid type", {
|
|
expect_error(cog_categories(type = "both"), "type")
|
|
})
|