Adds inst/extdata/fixture_corpus/ — a 3.6 MB two-year (2019/2020) slice of the published corpus (OH+VT+WY fixture from cog_pipeline test profile plus all 50 states). Includes canonical_fips_xwalk.parquet, summary_categories.parquet, docs/, and a trimmed manifest.json. setup.R now points USCOGDATA_URL at the bundled fixture automatically, bypassing HTTP / Nextcloud entirely. DuckDB reads local parquet via the existing .is_local_path() fast-path in manifest.R; no httpfs required. session is reset between test files via withr::defer(cog_close()). helper-fixture.R gains fixture_corpus_path(), a richer skip_if_no_corpus() that checks the bundled fixture first, and with_fixture_corpus() for tests that need explicit session isolation. test-spending.R: adjust the inflate-column test to use 2019 (fixture year) instead of 2015 (absent from fixture). Result: 181 PASS / 0 FAIL / 0 SKIP — all tests run against real parquet data with real DuckDB queries and no network dependency.
119 lines
4.5 KiB
R
119 lines
4.5 KiB
R
test_that("cog_spending returns expected shape for Broward Corrections 2020", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", years = 2020L, category = "Corrections")
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expect_s3_class(r, "tbl_df")
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expected_cols <- c("year", "canonical_govid", "gov_name", "spend_subtype",
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"category", "amt_nominal", "codes_included",
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"aggregate_fallback", "notes")
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expect_true(all(expected_cols %in% names(r)))
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expect_equal(unique(r$canonical_govid), "101006006")
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expect_equal(unique(r$year), 2020L)
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expect_equal(unique(r$category), "Corrections")
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expect_true(all(r$spend_subtype %in% c("operations", "capital")))
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expect_true(all(r$amt_nominal > 0))
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})
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test_that("cog_spending vectorised years + categories", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", 2019:2020,
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category = c("Corrections", "Police"))
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expect_true(all(r$year %in% 2019:2020))
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expect_true(all(r$category %in% c("Corrections", "Police")))
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expect_gte(nrow(r), 4L)
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})
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test_that("cog_spending with per_capita adds per-capita nominal column", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", 2020L, "Corrections", per_capita = TRUE)
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expect_true("amt_per_capita_nominal" %in% names(r))
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expect_false("amt_real" %in% names(r))
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expect_false("amt_per_capita_real" %in% names(r))
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expect_true(all(is.finite(r$amt_per_capita_nominal)))
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expect_true(all(r$amt_per_capita_nominal < r$amt_nominal))
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})
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test_that("cog_spending with adjust_to_year adds real column", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", 2019:2020, "Corrections",
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adjust_to_year = 2022L)
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expect_true("amt_real" %in% names(r))
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r2019 <- dplyr::filter(r, year == 2019L)
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expect_true(any(r2019$amt_nominal != r2019$amt_real))
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})
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test_that("cog_spending with per_capita + adjust_to_year adds all columns", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", 2020L, "Corrections",
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per_capita = TRUE, adjust_to_year = 2022L)
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expect_true(all(c("amt_nominal", "amt_real",
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"amt_per_capita_nominal", "amt_per_capita_real") %in%
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names(r)))
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})
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test_that("cog_spending for unknown govid returns empty tibble + informs", {
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skip_if_no_corpus()
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expect_message(
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r <- cog_spending("XXXINVALID", 2020L, "Corrections"),
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"not found|v0.1"
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)
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expect_s3_class(r, "tbl_df")
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expect_equal(nrow(r), 0L)
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expect_true("notes" %in% names(r))
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prov <- attr(r, "provenance")
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expect_false(is.null(prov))
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expect_equal(prov$scope$govids_missing, "XXXINVALID")
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expect_equal(length(prov$scope$govids_found), 0L)
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})
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test_that("cog_spending records found + missing govids in provenance", {
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skip_if_no_corpus()
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suppressMessages(
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r <- cog_spending(c("101006006", "XXXINVALID"), 2020L, "Corrections")
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)
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prov <- attr(r, "provenance")
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expect_equal(sort(prov$scope$govids_found), "101006006")
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expect_equal(sort(prov$scope$govids_missing), "XXXINVALID")
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})
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test_that("cog_spending result has provenance attribute matching schema", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", 2020L, "Corrections")
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prov <- attr(r, "provenance")
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expect_type(prov, "list")
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expect_equal(prov$verb, "cog_spending")
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required <- c("verb", "target", "years", "scope", "manifest", "sql_query")
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expect_true(all(required %in% names(prov)))
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expect_equal(prov$years, 2020L)
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expect_equal(prov$category, "Corrections")
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expect_type(prov$sql_query, "character")
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expect_true(grepl("spending_annotated", prov$sql_query))
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expect_type(prov$codes_summed$observed, "character")
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expect_true(all(c("E04") %in% prov$codes_summed$observed))
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})
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test_that("cog_spending rejects invalid inputs", {
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expect_error(cog_spending(list(), 2020L), "character|data frame")
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expect_error(cog_spending("101006006", "2020"), "years")
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})
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test_that("cog_spending accepts a cog_gov_search result directly", {
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skip_if_no_corpus()
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picks <- cog_gov_search("^BROWARD COUNTY$", state = "FL", type = "county")
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expect_gt(nrow(picks), 0L)
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r <- cog_spending(picks, 2020L, "Corrections")
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expect_equal(unique(r$canonical_govid), "101006006")
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})
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test_that("cog_spending accepts a cog_find_peers result directly", {
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skip_if_no_corpus()
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peers <- cog_find_peers("101006006", max_peers = 3L)
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r <- cog_spending(peers, 2020L, "Police")
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expect_setequal(unique(r$canonical_govid),
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sort(peers$canonical_govid))
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})
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test_that("cog_spending rejects data.frame without canonical_govid column", {
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bad <- tibble::tibble(foo = "bar")
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expect_error(cog_spending(bad, 2020L), "canonical_govid")
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})
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