jared
377eed1240
Three pieces:
1. cog_gov_search: name/state/type search over canonical_fips_xwalk
for resolving human-readable place names into canonical_govids.
Accepts USPS abbrev ('FL') or FIPS int (12) for state; integer
0-3 or name ('state','county','city','township') for type. Types
4/5 emit an explanatory cli message and return an empty tibble
(v0.1 corpus excludes them). USPS<->FIPS table hardcoded with
50 states + DC + territories; FIPS 66 = GU (not GA).
2. cog_mirror: downloads manifest-listed files to a local directory
with SHA-256 idempotency (files with matching hash return status
'cached'). Supports HTTP and local-path fixture URLs. Round-trip
test: mirror + re-open against the mirror + query Broward 2020
returns identical results.
3. Scope-aware verbs: .check_govids_in_scope() helper in session.R
queries canonical_fips_xwalk for the requested govids, emits a
cli_inform listing any missing ones, and records the found/missing
sets under provenance$scope. Wired into cog_spending (and
transitively into cog_revenue, cog_geographic_rollup,
cog_peer_compare via their cog_spending calls).
Also: dropped dbplyr from Imports (unused).
Tests: +29 (22 search + 12 mirror - 5 refactored) / 159 total pass.
devtools::check() now clean: 0E / 0W / 0N.
123 lines
4.4 KiB
R
123 lines
4.4 KiB
R
# R/search.R
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#' Search for governments by name, state, and/or type
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#'
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#' Returns rows from `canonical_fips_xwalk` matching the supplied filters.
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#' Intended as the entry point users call to resolve a human-readable place
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#' name into one or more `canonical_govid` values before calling
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#' [cog_spending()] / [cog_revenue()] / etc.
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#'
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#' @param pattern Character regex matched case-insensitively against
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#' `gov_name`. `NULL` (default) means no name filter.
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#' @param state Either a 2-letter USPS abbreviation (e.g. `"FL"`), a FIPS
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#' integer (e.g. `12`), or `NULL`.
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#' @param type Government type: an integer in `0:3` or one of `"state"`,
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#' `"county"`, `"city"`, `"township"`. Passing `4`, `5`,
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#' `"special_district"`, or `"school_district"` emits an explanatory
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#' message and returns an empty tibble (v0.1 corpus excludes those types).
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#' @return Tibble from `canonical_fips_xwalk` sorted by `population_acs`
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#' descending (`NULL`s last).
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#' @export
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cog_gov_search <- function(pattern = NULL, state = NULL, type = NULL) {
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if (!is.null(type) && .is_excluded_type(type)) {
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cli::cli_inform(c(
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i = "v0.1 covers gov_types 0-3 (state/county/city/township) only.",
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i = "Types 4 (special districts) and 5 (school districts) are excluded; see vignette('coverage-scope')."
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))
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return(.empty_xwalk_tibble())
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}
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con <- .ensure_session()
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preds <- character(0)
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if (!is.null(pattern)) {
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if (!is.character(pattern) || length(pattern) != 1L) {
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cli::cli_abort("`pattern` must be a length-1 character string.")
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}
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preds <- c(preds,
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sprintf("regexp_matches(gov_name, %s, 'i')",
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.sql_lit_chr(pattern)))
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}
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if (!is.null(state)) {
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st_fips <- .coerce_state_to_fips(state)
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preds <- c(preds, sprintf("fips_state = %s", .sql_lit_chr(st_fips)))
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}
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if (!is.null(type)) {
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int_type <- .coerce_type(type)
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preds <- c(preds, sprintf("govs_type = %d", int_type))
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}
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where <- if (length(preds) == 0L) "" else paste("WHERE", paste(preds, collapse = " AND "))
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sql <- paste(
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"SELECT * FROM canonical_fips_xwalk",
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where,
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"ORDER BY population_acs DESC NULLS LAST"
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)
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tibble::as_tibble(DBI::dbGetQuery(con, sql))
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}
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#' @noRd
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.empty_xwalk_tibble <- function() {
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tibble::tibble(
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canonical_govid = character(0), gov_name = character(0),
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govs_type = integer(0), type_label = character(0),
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fips_state = character(0), fips_county = character(0),
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fips_place = character(0), first_year = integer(0),
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last_year = integer(0), population_acs = integer(0),
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confidence = character(0)
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)
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}
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#' @noRd
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.is_excluded_type <- function(type) {
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excluded <- c("4", "5", "special_district", "school_district")
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as.character(type) %in% excluded
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}
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#' @noRd
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.coerce_type <- function(type) {
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if (is.numeric(type) ||
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(is.character(type) && length(type) == 1L && grepl("^[0-9]+$", type))) {
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n <- as.integer(type)
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if (!n %in% 0:3) {
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cli::cli_abort("type must be 0, 1, 2, or 3 (v0.1 scope).")
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}
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return(n)
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}
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map <- c(state = 0L, county = 1L, city = 2L, township = 3L)
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key <- as.character(type)
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if (!key %in% names(map)) cli::cli_abort("Unknown type: {type}.")
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map[[key]]
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}
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#' @noRd
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.coerce_state_to_fips <- function(state) {
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if (is.numeric(state) ||
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(is.character(state) && length(state) == 1L && grepl("^[0-9]+$", state))) {
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return(sprintf("%02d", as.integer(state)))
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}
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if (!is.character(state) || length(state) != 1L) {
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cli::cli_abort("`state` must be a 2-letter USPS abbrev or a FIPS integer.")
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}
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fips <- .state_abbrev_to_fips[[toupper(state)]]
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if (is.null(fips)) {
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cli::cli_abort("Unknown state abbreviation: {state}.")
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}
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fips
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}
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# USPS state / territory abbreviation -> 2-digit FIPS code.
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# Includes 50 states + DC + territories. Note FIPS 66 = GU (not GA).
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#' @noRd
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.state_abbrev_to_fips <- c(
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AL = "01", AK = "02", AZ = "04", AR = "05", CA = "06", CO = "08",
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CT = "09", DE = "10", DC = "11", FL = "12", GA = "13", HI = "15",
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ID = "16", IL = "17", IN = "18", IA = "19", KS = "20", KY = "21",
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LA = "22", ME = "23", MD = "24", MA = "25", MI = "26", MN = "27",
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MS = "28", MO = "29", MT = "30", NE = "31", NV = "32", NH = "33",
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NJ = "34", NM = "35", NY = "36", NC = "37", ND = "38", OH = "39",
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OK = "40", OR = "41", PA = "42", RI = "44", SC = "45", SD = "46",
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TN = "47", TX = "48", UT = "49", VT = "50", VA = "51", WA = "53",
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WV = "54", WI = "55", WY = "56",
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AS = "60", GU = "66", MP = "69", PR = "72", VI = "78"
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)
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