.build_suggestions() previously flagged a recipe only when the WHOLE category result had zero rows in a requested year, so a multi-code category where one recipe component was genuinely gapped never fired if any sibling code (same recipe or not) had data that year. Each recipe's own in-category component is now checked individually -- a component fires when it has no rows in a requested (in-scope) year the recipe's own generic join otherwise covers, even when the overall category result looks complete. Decomposes .build_suggestions() into .category_recipe_components/ .recipe_meta/.component_presence/.recipe_coverage/.recipe_component_gapped helpers, drops the now-unused `result` param, and rewrites the header comment to describe the new, deliberately wider scope plus the per-government `covered` guard that still filters recipes with no data at all (ordinary reporting variance vs. a real format-boundary gap). Tests pin the multi-code case the coarse check missed (Cleburne County FY2012: G05 gapped, G04 covers, masked because E04/E05 have data) next to the still-guarded no-recipe-coverage case (F04/F05 both absent), and update the Broward 2019-2020 case to its new, correct expectation (fires for corrections_combined/corrections_other_capital_combined, still silent for corrections_capital_combined) plus a fresh true-full-coverage negative case (Maricopa County).
202 lines
9.1 KiB
R
202 lines
9.1 KiB
R
# R/suggestions.R
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# Recipe-component-driven signposting: when a basis = "harmonized" query for
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# a category asks for a code that is itself a harmonization recipe
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# component, and that specific code has no rows in some requested years
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# while the recipe's own generic join would still fill those years for this
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# government, surface that recipe as a suggestion.
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#
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# This is deliberately keyed off the recipe catalog's component codes, not
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# off harmonization_map rows: no live map row carries a non-blank
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# suggested_recipe_id (the corpus's wide era exposes split families like
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# corrections functions 04+05 ONLY as aggregate rows, which basis =
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# "harmonized" excludes by construction -- there's no NA ruling to hang a
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# suggestion off of, just a leaf-code absence a recipe happens to fill).
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# See docs/phase_r_harmonization_review.md § 0.3.
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#
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# Scope is deliberately narrow in one respect and, as of Phase R3 Task 19c,
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# deliberately WIDE in another: signposting only runs when the caller
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# supplied a `category` (an un-scoped, all-categories query has no single
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# coverage question to answer), but within that category it now checks
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# EACH recipe component that is itself a category member individually,
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# rather than asking whether the whole category *result* has zero rows
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# that year. A recipe fires when one of its own components has zero rows
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# for this government in a requested year the recipe's own generic join
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# (same join .run_recipe() uses, aggregate rows included) otherwise covers
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# -- even if OTHER, unrelated codes in the same category have full data
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# that year and the overall result looks complete. That is a deliberate
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# narrowing of the R2-era false-positive guard: most governments don't use
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# every sibling code in a multi-code category every year, and per-code
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# detection WILL flag some of that as a "gap" even though it's really just
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# a government not having that particular sub-type of spending, not a
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# format-boundary artifact. The remaining guard against ordinary reporting
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# variance is the per-government `covered` check below (a component is
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# only flagged when the recipe's OWN join -- not some unrelated code --
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# actually has something to offer in that year); it no longer tries to
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# avoid noise from sibling *codes*, only from a recipe with genuinely
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# nothing to contribute. The acceptable noise level this trade produces is
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# a product decision, measured (not tuned here) by
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# data-raw/measure_signposting_rate.R and ruled on at Checkpoint R3.
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#' Recipe components that are classified under the requested category --
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#' the codes a category-scoped query actually "requests". A recipe can
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#' have components outside the category (e.g. general_gov_e89_wide's E85
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#' leg has no category assignment); those never trigger on their own, they
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#' just were never part of what this query asked for.
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#' @noRd
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.category_recipe_components <- function(con, category) {
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DBI::dbGetQuery(con, sprintf(
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"SELECT DISTINCT r.recipe_id, r.component_code, r.year_min, r.year_max,
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r.gov_type_scope
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FROM harmonization_recipes r
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JOIN summary_categories sc
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ON sc.item_code = r.component_code AND sc.category IN (%s)",
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.sql_lit_chr(category)
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))
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}
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#' Label + overall year coverage for a set of recipe ids (the suggestion's
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#' `label`/`available_years`).
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#' @noRd
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.recipe_meta <- function(con, candidates) {
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tibble::as_tibble(DBI::dbGetQuery(con, sprintf(
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"SELECT recipe_id, any_value(label) AS label,
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MIN(year_min) AS year_min, MAX(year_max) AS year_max
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FROM harmonization_recipes
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WHERE recipe_id IN (%s)
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GROUP BY recipe_id",
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.sql_lit_chr(candidates)
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)))
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}
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#' Which (recipe_id, component_code, year) triples have at least one
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#' NOT-aggregate row for these governments -- i.e. that specific requested
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#' code itself has data, scoped exactly like .run_recipe()'s join
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#' (component year_min/year_max + gov_type_scope). NOT-aggregate mirrors
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#' what basis = "harmonized" itself excludes: an aggregate-only year is a
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#' gap for that code exactly as it would be in a plain category query.
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#' @noRd
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.component_presence <- function(con, candidates, govid, years_lit) {
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DBI::dbGetQuery(con, sprintf(
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"SELECT DISTINCT r.recipe_id, r.component_code, l.year
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FROM long l
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JOIN harmonization_recipes r
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ON l.item_code = r.component_code
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AND l.year BETWEEN r.year_min AND r.year_max
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AND (r.gov_type_scope = 'all'
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OR (r.gov_type_scope = 'state' AND l.type = 0)
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OR (r.gov_type_scope = 'local' AND l.type BETWEEN 1 AND 3))
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WHERE NOT l.is_aggregate
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AND r.recipe_id IN (%s)
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AND l.canonical_govid IN (%s)
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AND l.year IN (%s)",
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.sql_lit_chr(candidates), .sql_lit_chr(govid), years_lit
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))
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}
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#' Which (recipe_id, year) pairs the recipe's own generic join actually
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#' covers for these governments -- the same join .run_recipe() uses
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#' (component year_min/year_max + gov_type_scope, no is_aggregate filter),
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#' just checking existence instead of summing. This is the per-government,
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#' whole-recipe guard against ordinary reporting variance: unlike
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#' .component_presence(), it is aggregate-inclusive and unioned across ALL
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#' of a recipe's components, not just the one requested code being tested,
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#' so a recipe with genuinely nothing to offer (no component, aggregate or
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#' leaf, has ever reported) never fires.
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#' @noRd
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.recipe_coverage <- function(con, candidates, govid, years_lit) {
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DBI::dbGetQuery(con, sprintf(
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"SELECT DISTINCT r.recipe_id, l.year
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FROM long l
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JOIN harmonization_recipes r
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ON l.item_code = r.component_code
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AND l.year BETWEEN r.year_min AND r.year_max
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AND (r.gov_type_scope = 'all'
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OR (r.gov_type_scope = 'state' AND l.type = 0)
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OR (r.gov_type_scope = 'local' AND l.type BETWEEN 1 AND 3))
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WHERE r.recipe_id IN (%s)
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AND l.canonical_govid IN (%s)
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AND l.year IN (%s)",
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.sql_lit_chr(candidates), .sql_lit_chr(govid), years_lit
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))
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}
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#' TRUE if recipe `rid` has at least one requested component with an
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#' in-scope requested year that has no data (`present`), in a year the
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#' recipe's own generic join is otherwise fillable (`covered`) -- the
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#' per-code gap the R2 whole-result check couldn't see.
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#' @noRd
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.recipe_component_gapped <- function(rid, requested, present, covered, years) {
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covered_years <- covered$year[covered$recipe_id == rid]
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if (length(covered_years) == 0L) return(FALSE)
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comps <- requested[requested$recipe_id == rid, , drop = FALSE]
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for (i in seq_len(nrow(comps))) {
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in_scope <- years[years >= comps$year_min[i] & years <= comps$year_max[i]]
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if (length(in_scope) == 0L) next
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has_data <- present$year[
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present$recipe_id == rid & present$component_code == comps$component_code[i]
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]
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gap_years <- setdiff(in_scope, has_data)
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if (any(gap_years %in% covered_years)) return(TRUE)
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}
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FALSE
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}
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#' Build the `prov$suggestions` list for a (non-recipe) basis = "harmonized"
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#' verb call: recipes whose generic join would fill a real per-code gap for
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#' the requested category.
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#'
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#' @param con Active DuckDB connection.
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#' @param govid Character vector of canonical_govid values (the verb's raw
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#' `govid`).
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#' @param years Integer vector of requested years.
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#' @param category `category` argument as passed to the verb (character
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#' vector or `NULL`; suggestions are only computed when non-NULL).
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#' @param basis The *resolved* basis (`"harmonized"` or `"raw"`).
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#' @return List of `list(recipe_id, label, available_years, hint)`, possibly
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#' empty.
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#' @noRd
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.build_suggestions <- function(con, govid, years, category, basis) {
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if (!identical(basis, "harmonized") || is.null(category)) return(list())
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requested <- .category_recipe_components(con, category)
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if (nrow(requested) == 0L) return(list())
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candidates <- unique(requested$recipe_id)
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years_int <- as.integer(years)
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years_lit <- paste(years_int, collapse = ",")
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meta <- .recipe_meta(con, candidates)
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present <- .component_presence(con, candidates, govid, years_lit)
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covered <- .recipe_coverage(con, candidates, govid, years_lit)
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suggestions <- list()
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for (rid in candidates) {
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if (!.recipe_component_gapped(rid, requested, present, covered, years_int)) next
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m <- meta[meta$recipe_id == rid, ]
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suggestions[[length(suggestions) + 1L]] <- list(
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recipe_id = rid,
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label = m$label[[1]],
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available_years = c(as.integer(m$year_min), as.integer(m$year_max)),
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hint = sprintf("re-run with recipe = '%s'", rid)
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)
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}
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suggestions
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}
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#' Emit the single cli::cli_inform() message summarizing all suggestions
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#' for a verb call (the brief's "one message", not one per suggestion).
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#' Bullet text is pre-formatted plain text (no cli/glue `{}` markup) since
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#' recipe ids/labels are untrusted-ish data values, not literal call-site
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#' expressions.
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#' @noRd
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.inform_suggestions <- function(suggestions) {
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bullets <- vapply(suggestions, function(s) {
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sprintf("%s (%d-%d): %s", s$recipe_id,
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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_inform(c(
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i = "Coverage gap detected for the requested years; a harmonization recipe may fill it:",
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stats::setNames(bullets, rep("*", length(bullets)))
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))
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}
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