jared
4de915b557
Adds cog_recipes() to list the curated harmonization_recipes catalog (24 recipes / schema_version >= 5), and a recipe= argument on cog_spending()/ cog_revenue() that runs a recipe's generic multi-code join instead of the category view: SUM(amt * weight) across whichever component codes are present for a (year, canonical_govid), scoped by gov_type_scope. The join deliberately does not filter is_aggregate -- the wide era (<= 2011) exposes these split families (corrections 04+05, IG *89/*47, U4- rents, etc.) ONLY as aggregate rows, with leaf codes first appearing in 2012, so excluding aggregates would zero out the wide-era half of every recipe. This is safe by corpus construction: wide-era rows are aggregate-only, modern rows are leaf-only, and every component is year-scoped, so there is no double-counting. recipe= is mutually exclusive with category=; the result's subtype column reads "recipe" and category reads the recipe's label. Adds recipe-component-driven signposting: when a basis="harmonized" + category query comes back with zero rows in a requested year, and a harmonization recipe covering that category would actually produce rows for this government in that year (via the same join .run_recipe() uses), the recipe is surfaced in provenance$suggestions plus one cli::cli_inform() message. This is deliberately keyed off recipe components rather than harmonization_map's suggested_recipe_id column (which is empty on every live row -- the wide era's split families are NA-by-construction via aggregate exclusion, not an NA ruling to hang a suggestion off of). Also populates the previously-always-empty provenance$series_break_refs (schema v5 only: series_breaks_pq rows whose fin_code is among the observed codes and whose break_year falls in the requested span), and extends cog_explain() with Basis/Harmonization/Recipe/Suggestions/Series breaks sections.
uscogdata
Curated R reader for the Civilytics US Census of Governments finance corpus.
Provides unit-level financial profiles, geographic rollups, and peer comparisons with auditable provenance and built-in cross-vintage correctness. Reads the published corpus (Hive-partitioned parquet + manifest.json) directly from Nextcloud via DuckDB httpfs — no local bulk downloads required.
Status
Under active development (Phase 2 of the cog_pipeline project). See
../cog_pipeline/docs/reader-specification.md for the reader contract this
package implements.
Installation
# pak::pkg_install("gitea.civilytics.org/Civilytics/uscogdata")
Configuration
USCOGDATA_URL— corpus root URL (public Nextcloud share, trailing slash)USCOGDATA_CACHE_DIR— optional override for the manifest cache directoryUSCOGDATA_MANIFEST_TTL_SECS— optional manifest re-fetch TTL (default 3600)
Developer notes
Testing
The package ships a bundled fixture corpus at inst/extdata/fixture_corpus/ —
a 3.6 MB two-year slice (2019 + 2020) of the full corpus covering all 50
states. tests/testthat/setup.R automatically points USCOGDATA_URL at this
fixture, so the full test suite runs offline with no network dependency:
devtools::test() # uses bundled fixture, no credentials required
Releasing against the live corpus
Before cutting a release, run the test suite against the published corpus to catch any drift between the fixture and the real data:
Sys.setenv(USCOGDATA_URL = "<published-corpus-url-with-trailing-slash>")
devtools::test()
When the live-corpus run is clean, strip the fixture from the built package by
adding this line to .Rbuildignore:
^inst/extdata/fixture_corpus$
The test suite is URL-agnostic — setup.R falls back to USCOGDATA_URL when
the bundled fixture is absent, so no test code changes are needed for the
release run or after stripping the fixture.