Sparsification (cog_pipeline#64, SB194) stopped the corpus storing the wide era's explicit zeros, which made absence ambiguous: <= FY2011 dense_source absent => Census published $0 >= FY2012 sparse_source absent => not reported, unknown A wide-era query whose cells were all $0 had begun returning nothing at all, with no way to get them back -- strictly less than the reader exposed before, which is why #64 filed this follow-on. complete = TRUE fills the requested grid from `code_set` and stamps every row with value_source: "reported", "census_zero" (amt 0), or "not_reported" (amt NA). The NA is the point. Filling a modern absence with 0 would invent data, which is exactly the error the representation contract exists to prevent -- and it makes this strictly MORE informative than the pre-sparsification corpus, which could not tell a published zero from an unreported cell either. Measured on the fixture, Broward County: FY2011 returns 28 reported + 16 census_zero; FY2019 returns 30 reported + 14 not_reported. The five categories that walkthrough finding F-006 read as "retired at FY2012" now report themselves correctly as census_zero before and not_reported after. Scoping decisions, each of which would invent rows if taken loosely: - The grid is per government TYPE (code_set.type). Filling against the union of all types would give a county cells like "state IG transfer to school districts", indistinguishable from real census zeros. - NOT is_aggregate, mirroring spending_long/revenue_long. Without it the grid offers cells those views never return, so each would fill as a phantom $0. - Filling happens BEFORE per_capita and inflation, so a census_zero stays 0 through both and a not_reported stays NA rather than becoming 0. Two new views (36-representation, 37-code_set) are gated on the manifest LISTING those tables, not on schema_version. Sparsification did not bump the version -- the fixture this package shipped against until 2026-07-30 was already v6 and carried neither table -- so a version gate would register a view over a missing file and fail at CREATE VIEW time on exactly the corpora the check exists to tolerate. with_corpus_missing_representation() models that corpus and asserts the abort. Refused where the fill would be guesswork, both classed uscogdata_complete_unsupported: a recipe defines its own component codes and never touches summary_categories; the intergovernmental leg deliberately keeps aggregate rows (inst/sql/24-ig_long.sql) so its cells are not the ones code_set describes. Expected cell sets in the tests are computed from the corpus parquet directly, never through the verb -- verifying what a filter does through that same filter proves nothing. Closes DoD 2, 3 and 4 of #18. DoD 5 (the cog-api follow-on) is filed separately. Suite: 658 pass / 0 fail / 3 skip (was 629/0/3). rcmdcheck clean.
228 lines
7.6 KiB
R
228 lines
7.6 KiB
R
# R/explain.R
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#' Explain a verb result's provenance
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#'
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#' Prints the structured provenance attached to a tibble returned by any
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#' `cog_*` verb, or returns it as a list for downstream use (MCP tools,
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#' dashboards, JSON export).
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#'
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#' @param result A tibble returned by a `cog_*` verb.
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#' @param format `"print"` (default) for a human-readable cli summary;
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#' returns `result` invisibly for chaining. `"list"` returns the raw
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#' provenance list (identical to `attr(result, "provenance")`).
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#' @return Either `result` (invisibly) or the provenance list.
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#' @export
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cog_explain <- function(result, format = c("print", "list")) {
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format <- match.arg(format)
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prov <- attr(result, "provenance")
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if (is.null(prov)) {
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cli::cli_abort(c(
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"No `provenance` attribute on result.",
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i = "Pass a tibble returned by a cog_* verb (e.g. cog_spending())."
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))
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}
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if (format == "list") return(prov)
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.print_provenance(prov)
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invisible(result)
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}
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#' @noRd
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.print_provenance <- function(prov) {
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cli::cli_h1("{prov$verb}()")
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tgt_ids <- paste(prov$target$canonical_govid, collapse = ", ")
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tgt_names <- if (length(prov$target$gov_name) == 0L) {
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"(no rows returned)"
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} else {
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paste(prov$target$gov_name, collapse = ", ")
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}
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cli::cli_text("Target: {tgt_names} [canonical_govid: {tgt_ids}]")
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yrs <- prov$years
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cli::cli_text(if (length(yrs) == 1L) {
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"Year: {yrs}"
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} else {
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"Years: {min(yrs)}-{max(yrs)} ({length(yrs)} years)"
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})
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if (!is.null(prov$category)) {
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cli::cli_text("Category: {paste(prov$category, collapse = ', ')}")
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} else {
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cli::cli_text("Category: (all)")
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}
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if (!is.null(prov$basis)) {
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note <- if (!is.null(prov$basis_note) && !is.na(prov$basis_note)) {
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sprintf(" (%s)", prov$basis_note)
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} else {
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""
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}
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cli::cli_text("Basis: {prov$basis}{note}")
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}
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if (!is.null(prov$expenditure_concept)) {
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concept_note <- if (!is.null(prov$expenditure_concept_note) &&
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!is.na(prov$expenditure_concept_note)) {
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sprintf(" (%s)", prov$expenditure_concept_note)
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} else {
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""
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}
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cli::cli_text("Concept: {prov$expenditure_concept}{concept_note}")
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if (isTRUE(prov$expenditure_concept_direct_suppressed)) {
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cli::cli_alert_warning(
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"Direct leg unavailable for at least one requested (year, category) -- affected rows report intergovernmental dollars alone, not Direct + IG. See each row's notes."
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)
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}
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}
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cli::cli_h2("Codes observed")
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codes <- prov$codes_summed$observed
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if (length(codes) == 0L) {
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cli::cli_alert_info("No item codes matched.")
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} else {
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cli::cli_ul(codes)
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}
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if (isTRUE(prov$aggregate_fallback$applied)) {
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cli::cli_h2("Aggregate fallback")
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cli::cli_alert_warning(
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"Aggregate fallback used for years: {paste(prov$aggregate_fallback$years, collapse = ', ')}"
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)
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}
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h <- prov$harmonization
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if (!is.null(h) && isTRUE(h$applied)) {
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cli::cli_h2("Harmonization")
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cli::cli_text(
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"Excluded {h$na_rows_excluded} row(s) with no harmonized_code (${format(h$na_amount_excluded, big.mark = ',')})"
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)
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}
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rc <- prov$recipe
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if (!is.null(rc)) {
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cli::cli_h2("Recipe")
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cli::cli_text("{rc$recipe_id}: {rc$label}")
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comp_lines <- vapply(rc$components, function(x) {
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sprintf("%s (%s, %s-%s, weight=%s)", x$component_code, x$gov_type_scope,
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x$year_min, x$year_max, x$weight)
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}, character(1))
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cli::cli_ul(comp_lines)
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}
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if (length(prov$suggestions) > 0L) {
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cli::cli_h2("Suggestions")
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sugg_lines <- vapply(prov$suggestions, function(s) {
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sprintf("%s -- %s (years %s-%s): %s", s$recipe_id, s$label,
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s$available_years[1], s$available_years[2], s$hint)
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}, character(1))
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cli::cli_ul(sugg_lines)
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}
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if (isTRUE(prov$completion$applied)) {
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cli::cli_h2("Completion")
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cli::cli_text(
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"Filled {prov$completion$rows_filled} absent cell(s) from the corpus code set."
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)
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rules <- prov$completion$absence_means
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if (length(rules) > 0L) {
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cli::cli_ul(vapply(names(rules), function(y) {
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sprintf("%s: an absent cell means %s", y,
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if (identical(rules[[y]], "census_zero")) {
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"Census published $0 (filled as 0)"
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} else {
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"the government did not report (filled as NA, not 0)"
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})
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}, character(1)))
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}
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}
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if (length(prov$series_break_refs) > 0L) {
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cli::cli_h2("Series breaks")
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cli::cli_ul(.series_break_story_lines(prov$series_break_refs))
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}
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# Kept in a section of its own: these qualify the whole result, so folding
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# them in with the per-code breaks above would invite reading them as a
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# caveat about one series.
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if (length(prov$corpus_break_refs) > 0L) {
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cli::cli_h2("Corpus-wide caveats")
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cli::cli_ul(.series_break_story_lines(prov$corpus_break_refs))
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}
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cli::cli_h2("Transformations")
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uc <- prov$transformations$units_conversion
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if (isTRUE(uc$applied)) {
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cli::cli_text("Units: {uc$source_unit} -> {uc$target_unit} (x{uc$multiplier})")
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}
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pc <- prov$transformations$per_capita
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if (isTRUE(pc$applied)) {
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cli::cli_text("Per-capita denominator: {pc$denominator_source}")
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if (length(pc$popyear_range) == 2L) {
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lo <- .expand_popyear(pc$popyear_range[1])
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hi <- .expand_popyear(pc$popyear_range[2])
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cli::cli_text(" popyear range: {lo}-{hi}")
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}
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if (!is.null(pc$pop_source_counts)) {
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cli::cli_text(
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" pop_source counts: census_f33={pc$pop_source_counts$census_f33}, unavailable={pc$pop_source_counts$unavailable}"
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)
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}
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}
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infl <- prov$transformations$inflation
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if (isTRUE(infl$applied)) {
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cli::cli_text("Inflation: {infl$index}, base year {infl$base_year}")
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}
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cli::cli_h2("Scope")
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cli::cli_text(
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"Included gov types: {paste(prov$scope$gov_types_included, collapse = ', ')}"
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)
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cli::cli_text(
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"Excluded gov types: {paste(prov$scope$gov_types_excluded, collapse = ', ')}"
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)
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if (nzchar(prov$scope$scope_note %||% "")) {
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cli::cli_text("Note: {prov$scope$scope_note}")
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}
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cli::cli_h2("Data vintage")
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cli::cli_text(
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"Manifest schema v{prov$manifest$schema_version}, pipeline {prov$manifest$pipeline_commit}, built {prov$manifest$built_at}"
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)
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invisible(NULL)
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}
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# One "break-story" line per referenced break_id: "SB109 (2005): <join_advice>".
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# Re-queries series_breaks_pq for the detail (break_year, join_advice) that
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# provenance$series_break_refs deliberately doesn't carry (the schema keeps
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# that field to a plain id array). Falls back to bare ids if no session is
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# available (e.g. explaining a result after cog_close()) rather than
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# erroring cog_explain() over a cosmetic detail.
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#' @noRd
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.series_break_story_lines <- function(break_ids) {
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con <- tryCatch(.ensure_session(), error = function(e) NULL)
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if (is.null(con) || !DBI::dbIsValid(con)) return(break_ids)
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detail <- tryCatch(
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DBI::dbGetQuery(con, sprintf(
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"SELECT break_id, break_year, join_advice FROM series_breaks_pq
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WHERE break_id IN (%s) ORDER BY break_id",
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.sql_lit_chr(break_ids)
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)),
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error = function(e) NULL
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)
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if (is.null(detail) || nrow(detail) == 0L) return(break_ids)
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sprintf("%s (%s): %s", detail$break_id, detail$break_year, detail$join_advice)
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}
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# Expand a 2-digit Census popyear (e.g. 19) to a 4-digit calendar year (2019).
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# F-33 metadata stores popyear as 2 digits; pivot at 70 to handle a future
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# corpus that ever spans pre-1970 vintages, though current scope is 2000+.
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#' @noRd
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.expand_popyear <- function(yy) {
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yy <- as.integer(yy)
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if (length(yy) == 0L || is.na(yy)) return(NA_integer_)
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if (yy >= 100L) return(yy) # already 4-digit
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if (yy < 70L) return(2000L + yy)
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1900L + yy
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}
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