Swaps every hardcoded 9-char canonical_govid literal (Broward County,
Fort Lauderdale City, Florida/Alabama state govts, Bexar/Tarrant/Wayne
counties, San Diego/Oakland/Miami/Austin cities) for its 12-char Phase P
equivalent, resolved by name+type+state against the regenerated fixture
xwalk. Also updates two gov_name search patterns that no longer match
under Phase P canonical naming ("FLORIDA STATE GOVT" -> "FLORIDA"; the
"Miami" substring test now pins type = "city" since MIAMI-DADE COUNTY's
canonical name now also contains "Miami", which would otherwise make the
match ambiguous across govs_types instead of resolving via largest-pop).
Underlying per-year population figures for Broward County and Alabama
are unchanged, so no expected data-value literals needed recomputation.
Suite: 126 test blocks / 336 expectations, 0 FAIL / 0 WARN / 0 SKIP.
Updates transformations\$per_capita with the new denominator_source string,
popyear_range, and pop_source_counts. .attach_per_capita stashes
popyear_range on the result; .verb_spendrev strips the helper attr after
provenance is built.
.notes_column now joins multiple per-row notes with '; '. Adds the
'No population denominator available for this gov type' note when
pop_source is 'unavailable'. Gracefully handles absent pop_source
(per_capita = FALSE). Two new tests: one corpus-level (census_f33
branch) and one synthetic unit test covering multi-note concatenation.
Adds a RED test asserting that cog_spending(per_capita = TRUE) divides
by the per-year F-33 population (Broward 2019: 1,935,878; 2020: 1,952,778)
rather than the static ACS value (1,940,907). Uses absolute-tolerance
expect_true(abs(...) < 1) instead of expect_equal(tolerance=1) because
testthat 3 treats the tolerance argument as relative.
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.
Two UX fixes surfaced by first real-user use:
1. cog_spending / cog_revenue / cog_geographic_rollup now accept either
a character vector OR a data.frame with a canonical_govid column
(e.g. output of cog_gov_search() or cog_find_peers()). Shared
.coerce_govid_input() helper in session.R. This lets the natural
pipe work:
cog_gov_search('MIAMI', state='FL', type='city') |>
cog_spending(years=2022, category='Police')
cog_peer_compare already accepted a data.frame for the peer arg;
behavior there is unchanged.
2. .check_govids_in_scope() message reworded. The old text led with
'v0.1 covers gov_types 0-3' which falsely implied the missing govids
were scope-excluded types when the more common real cause is a typo
or a guessed value. New message leads with typo + pre-2017 PID,
mentions scope exclusion as one possibility, and points at
cog_gov_search() as the recovery path.
Tests: 165 pass / 0 fail. check 0E/0W/0N.
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.
Three core query verbs over the spending_annotated / revenue_annotated
DuckDB views. Each verb accepts vector govid, vector years, optional
category filter, per_capita flag, and adjust_to_year for CPI-U
real-dollar conversion (bundled index).
Amounts are returned in full USD (SUM(amt) * 1000) so callers can
freely rescale to millions/billions. The $1,000s -> $USD conversion
is recorded in provenance$transformations$units_conversion.
Every result carries an attr(., "provenance") list matching
inst/schemas/provenance-v1.json. cog_explain() prints the structured
form via cli or returns the raw list for MCP/JSON consumers.
Also: .fetch_or_cache_manifest() now handles local fixture paths so
tests can point USCOGDATA_FIXTURE_URL at the pipeline publish_cache/
without a working HTTP server.
Tests: 80 pass / 0 fail. devtools::check() 0E/0W/2N (both notes
pre-existing / environmental).
jared