jared
377eed1240
Three pieces:
1. cog_gov_search: name/state/type search over canonical_fips_xwalk
for resolving human-readable place names into canonical_govids.
Accepts USPS abbrev ('FL') or FIPS int (12) for state; integer
0-3 or name ('state','county','city','township') for type. Types
4/5 emit an explanatory cli message and return an empty tibble
(v0.1 corpus excludes them). USPS<->FIPS table hardcoded with
50 states + DC + territories; FIPS 66 = GU (not GA).
2. cog_mirror: downloads manifest-listed files to a local directory
with SHA-256 idempotency (files with matching hash return status
'cached'). Supports HTTP and local-path fixture URLs. Round-trip
test: mirror + re-open against the mirror + query Broward 2020
returns identical results.
3. Scope-aware verbs: .check_govids_in_scope() helper in session.R
queries canonical_fips_xwalk for the requested govids, emits a
cli_inform listing any missing ones, and records the found/missing
sets under provenance$scope. Wired into cog_spending (and
transitively into cog_revenue, cog_geographic_rollup,
cog_peer_compare via their cog_spending calls).
Also: dropped dbplyr from Imports (unused).
Tests: +29 (22 search + 12 mirror - 5 refactored) / 159 total pass.
devtools::check() now clean: 0E / 0W / 0N.
98 lines
3.7 KiB
R
98 lines
3.7 KiB
R
test_that("cog_spending returns expected shape for Broward Corrections 2020", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", years = 2020L, category = "Corrections")
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expect_s3_class(r, "tbl_df")
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expected_cols <- c("year", "canonical_govid", "gov_name", "spend_subtype",
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"category", "amt_nominal", "codes_included",
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"aggregate_fallback", "notes")
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expect_true(all(expected_cols %in% names(r)))
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expect_equal(unique(r$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$amt_nominal))
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})
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test_that("cog_spending with adjust_to_year adds real column", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", 2015:2020, "Corrections",
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adjust_to_year = 2022L)
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expect_true("amt_real" %in% names(r))
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r2015 <- dplyr::filter(r, year == 2015L)
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expect_true(any(r2015$amt_nominal != r2015$amt_real))
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})
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test_that("cog_spending with per_capita + adjust_to_year adds all columns", {
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skip_if_no_corpus()
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r <- cog_spending("101006006", 2020L, "Corrections",
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per_capita = TRUE, adjust_to_year = 2022L)
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expect_true(all(c("amt_nominal", "amt_real",
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"amt_per_capita_nominal", "amt_per_capita_real") %in%
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names(r)))
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})
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test_that("cog_spending for unknown govid returns empty tibble + informs", {
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skip_if_no_corpus()
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expect_message(
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r <- cog_spending("XXXINVALID", 2020L, "Corrections"),
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"not found|v0.1"
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)
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expect_s3_class(r, "tbl_df")
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expect_equal(nrow(r), 0L)
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expect_true("notes" %in% names(r))
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prov <- attr(r, "provenance")
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expect_false(is.null(prov))
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expect_equal(prov$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(123, 2020L), "character")
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expect_error(cog_spending("101006006", "2020"), "years")
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})
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