Files
uscogdata/R/provenance.R
T
jared c682e6547d feat: cog_spending + cog_revenue + cog_explain
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).
2026-04-24 09:49:09 -04:00

84 lines
2.5 KiB
R

# R/provenance.R
# Shared provenance construction. Matches inst/schemas/provenance-v1.json.
#' @noRd
.build_provenance <- function(verb, call, govid, years, category,
per_capita, adjust_to_year, result, sql,
subtype_col) {
manifest <- .uscogdata_env$manifest
codes <- result[["codes_included"]]
codes_observed <- if (length(codes) == 0L) {
character(0)
} else {
sorted <- sort(unique(unlist(strsplit(codes, ",", fixed = TRUE))))
sorted[nzchar(sorted)]
}
agg_flag <- result[["aggregate_fallback"]]
agg_applied <- isTRUE(any(agg_flag, na.rm = TRUE))
agg_years <- if (agg_applied) {
unique(as.integer(result$year[which(agg_flag)]))
} else {
integer(0)
}
gov_names <- if (nrow(result) == 0L) {
character(0)
} else {
unique(result$gov_name)
}
list(
verb = verb,
call = paste(deparse(call), collapse = " "),
target = list(
canonical_govid = as.character(govid),
gov_name = gov_names
),
years = as.integer(years),
category = category,
scope = list(
gov_types_included = as.integer(unlist(manifest$scope$gov_types_included)),
gov_types_excluded = as.integer(unlist(manifest$scope$gov_types_excluded)),
scope_note = manifest$scope$scope_note %||% ""
),
codes_summed = list(
observed = codes_observed,
subtype_column = subtype_col
),
aggregate_fallback = list(
applied = agg_applied,
years = agg_years
),
transformations = list(
units_conversion = list(
applied = TRUE,
source_unit = "$1,000s (raw Census)",
target_unit = "$USD",
multiplier = 1000L
),
per_capita = list(
applied = isTRUE(per_capita),
denominator_source = if (isTRUE(per_capita)) {
"ACS 2018-2022 B01003_001 (population_acs from canonical_fips_xwalk)"
} else {
NA_character_
}
),
inflation = list(
applied = !is.null(adjust_to_year),
base_year = if (is.null(adjust_to_year)) NA_integer_ else as.integer(adjust_to_year),
index = if (is.null(adjust_to_year)) NA_character_ else "CPI-U (BLS CPIAUCSL annual average, bundled)"
)
),
series_break_refs = character(0),
manifest = list(
schema_version = as.integer(manifest$schema_version),
pipeline_commit = manifest$pipeline_commit %||% NA_character_,
built_at = manifest$built_at %||% NA_character_
),
sql_query = sql
)
}