jared
c682e6547d
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$units_conversion. Every result carries an attr(., "provenance") list matching inst/schemas/provenance-v1.json. cog_explain() prints the structured form via cli or returns the raw list for MCP/JSON consumers. Also: .fetch_or_cache_manifest() now handles local fixture paths so tests can point USCOGDATA_FIXTURE_URL at the pipeline publish_cache/ without a working HTTP server. Tests: 80 pass / 0 fail. devtools::check() 0E/0W/2N (both notes pre-existing / environmental).
84 lines
2.5 KiB
R
84 lines
2.5 KiB
R
# R/provenance.R
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# Shared provenance construction. Matches inst/schemas/provenance-v1.json.
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#' @noRd
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.build_provenance <- function(verb, call, govid, years, category,
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per_capita, adjust_to_year, result, sql,
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subtype_col) {
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manifest <- .uscogdata_env$manifest
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codes <- result[["codes_included"]]
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codes_observed <- if (length(codes) == 0L) {
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character(0)
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} else {
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sorted <- sort(unique(unlist(strsplit(codes, ",", fixed = TRUE))))
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sorted[nzchar(sorted)]
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}
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agg_flag <- result[["aggregate_fallback"]]
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agg_applied <- isTRUE(any(agg_flag, na.rm = TRUE))
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agg_years <- if (agg_applied) {
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unique(as.integer(result$year[which(agg_flag)]))
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} else {
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integer(0)
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}
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gov_names <- if (nrow(result) == 0L) {
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character(0)
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} else {
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unique(result$gov_name)
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}
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list(
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verb = verb,
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call = paste(deparse(call), collapse = " "),
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target = list(
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canonical_govid = as.character(govid),
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gov_name = gov_names
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),
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years = as.integer(years),
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category = category,
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scope = list(
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gov_types_included = as.integer(unlist(manifest$scope$gov_types_included)),
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gov_types_excluded = as.integer(unlist(manifest$scope$gov_types_excluded)),
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scope_note = manifest$scope$scope_note %||% ""
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),
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codes_summed = list(
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observed = codes_observed,
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subtype_column = subtype_col
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),
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aggregate_fallback = list(
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applied = agg_applied,
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years = agg_years
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),
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transformations = list(
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units_conversion = list(
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applied = TRUE,
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source_unit = "$1,000s (raw Census)",
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target_unit = "$USD",
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multiplier = 1000L
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),
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per_capita = list(
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applied = isTRUE(per_capita),
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denominator_source = if (isTRUE(per_capita)) {
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"ACS 2018-2022 B01003_001 (population_acs from canonical_fips_xwalk)"
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} else {
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NA_character_
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}
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),
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inflation = list(
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applied = !is.null(adjust_to_year),
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base_year = if (is.null(adjust_to_year)) NA_integer_ else as.integer(adjust_to_year),
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index = if (is.null(adjust_to_year)) NA_character_ else "CPI-U (BLS CPIAUCSL annual average, bundled)"
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)
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),
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series_break_refs = character(0),
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manifest = list(
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schema_version = as.integer(manifest$schema_version),
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pipeline_commit = manifest$pipeline_commit %||% NA_character_,
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built_at = manifest$built_at %||% NA_character_
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),
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sql_query = sql
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)
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}
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