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uscogdata/man/cog_spending.Rd
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fix: exercise real harmonized-view SQL in tests; unambiguous recipe provenance
test-views.R's harmonized-view test previously ran a hand-rolled REPLACE
query with no WHERE clause, so a regression in any of
inst/sql/22-spending_long_harmonized.sql / 23-revenue_long_harmonized.sql's
three predicates (NOT is_aggregate, harmonized_code IS NOT NULL, the
E/F/G/K or T/A/U/B/C/D prefix filter) would go uncaught. Replaced it with a
test that reads the real SQL files off disk, substitutes {url} exactly as
.register_views() does, and executes them (plus their 10-long.sql
dependency) against a synthetic hive-partitioned parquet tree written via
DuckDB's own COPY ... TO (FORMAT PARQUET) (no arrow dependency, matching
this package's existing convention). Ten rows are crafted so each predicate
is independently falsifiable by a specific row; manually broke each
predicate in turn to confirm the test fails exactly as expected, then
restored the SQL files (see the task report for the RED-phase transcript).

Also fixes a provenance ambiguity: a recipe= query bypasses
spending_annotated(_harmonized)/revenue_annotated(_harmonized) entirely
(.run_recipe() joins `long` directly), so basis= has no effect on it, but
provenance was still reporting basis = "harmonized"/"raw" (whatever the
argument resolved to) with harmonization$applied = FALSE alongside it --
misleading, since it looks like harmonization was evaluated and found
nothing to exclude rather than "not applicable here." Recipe results now
report basis = "recipe" with an inert harmonization block carrying an
explicit note, regardless of what basis= was passed.
2026-07-18 23:55:48 -04:00

73 lines
3.1 KiB
R

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/spending.R
\name{cog_spending}
\alias{cog_spending}
\title{Summarized spending by category}
\usage{
cog_spending(
govid,
years,
category = NULL,
per_capita = FALSE,
adjust_to_year = NULL,
basis = c("harmonized", "raw"),
recipe = NULL
)
}
\arguments{
\item{govid}{Character vector of `canonical_govid` values.}
\item{years}{Integer vector of years.}
\item{category}{Character vector of category names (from
`summary_categories.category`), or `NULL` for all categories.}
\item{per_capita}{If `TRUE`, adds `amt_per_capita_nominal` (and
`amt_per_capita_real` when `adjust_to_year` is set) using the per-year
Census F-33 population from `gov_population_yearly`. Result also gains
a `pop_source` column with values `"census_f33"` or `"unavailable"`
(the latter for gov types 4/5 and any row whose population is missing
in that year).}
\item{adjust_to_year}{Integer base year for CPI-U real-dollar conversion,
or `NULL` for nominal only.}
\item{basis}{`"harmonized"` (default) sums item codes through the
cross-vintage harmonization mapping (folding series-break-affected
codes onto a comparable target and excluding aggregate / discontinued
rows -- see the `harmonization` block in `cog_explain()`); `"raw"`
reproduces the pre-Phase-R2 behavior (published item codes, no
folding). On a corpus with `schema_version < 5` (no harmonization
tables), `basis` silently resolves to `"raw"` when left at its default
and the resolution is recorded in the provenance; explicitly passing
`basis = "harmonized"` on such a corpus aborts. Ignored when `recipe`
is set (see below).}
\item{recipe}{Optional harmonization recipe id (see [cog_recipes()]) for
multi-code cross-vintage series that a 1:1 harmonized_code mapping
can't express (e.g. a wide-era aggregate that only splits into leaf
codes in the modern era). Mutually exclusive with `category`. The
result's subtype column reads `"recipe"` and `category` reads the
recipe's label. Requires `schema_version >= 5`. A recipe query bypasses
`basis` entirely (it joins `long` directly rather than going through
the `*_annotated`/`*_annotated_harmonized` views), so the `basis`
argument is ignored and the result's provenance reports
`basis = "recipe"` with an inert `harmonization` block (`applied =
FALSE`, pointing at the `recipe` block instead) rather than a
possibly-misleading `"harmonized"`/`"raw"` value.}
}
\value{
Tibble with columns `year`, `canonical_govid`, `gov_name`,
`spend_subtype`, `category`, `amt_nominal`, optional `amt_real`,
optional `amt_per_capita_nominal`, optional `amt_per_capita_real`,
optional `pop_source`, `codes_included`, `aggregate_fallback`, `notes`.
Carries a `provenance` attribute matching `inst/schemas/provenance-v1.json`.
}
\description{
One row per `(year, canonical_govid, spend_subtype, category)`. Amounts are
returned in **full U.S. dollars** (the raw corpus stores them in $1,000s;
this verb multiplies by 1000 so downstream code can freely rescale to
millions/billions). The conversion is recorded in the provenance attribute
under `transformations$units_conversion`.
}