# R/search.R

#' Search for governments by name, state, and/or type
#'
#' Returns rows from `canonical_fips_xwalk` matching the supplied filters.
#' Intended as the entry point users call to resolve a human-readable place
#' name into one or more `canonical_govid` values before calling
#' [cog_spending()] / [cog_revenue()] / etc.
#'
#' @param name Character regex matched case-insensitively against
#'   `gov_name`. `NULL` (default) means no name filter.
#' @param state Either a 2-letter USPS abbreviation (e.g. `"FL"`), a FIPS
#'   integer (e.g. `12`), or `NULL`.
#' @param type Government type: an integer in `0:3` or one of `"state"`,
#'   `"county"`, `"city"`, `"township"`. Passing `4`, `5`,
#'   `"special_district"`, or `"school_district"` emits an explanatory
#'   message and returns an empty tibble (v0.1 corpus excludes those types).
#' @return Tibble from `canonical_fips_xwalk` sorted by `population_acs`
#'   descending (`NULL`s last).
#' @export
cog_gov_search <- function(name = NULL, state = NULL, type = NULL) {
  if (!is.null(type) && .is_excluded_type(type)) {
    cli::cli_inform(c(
      i = "v0.1 covers gov_types 0-3 (state/county/city/township) only.",
      i = "Types 4 (special districts) and 5 (school districts) are excluded; see vignette('coverage-scope')."
    ))
    return(.empty_xwalk_tibble())
  }
  con <- .ensure_session()

  preds <- character(0)
  if (!is.null(name)) {
    if (!is.character(name) || length(name) != 1L) {
      cli::cli_abort("`name` must be a length-1 character string.")
    }
    preds <- c(preds,
               sprintf("regexp_matches(gov_name, %s, 'i')",
                       .sql_lit_chr(name)))
  }
  if (!is.null(state)) {
    st_fips <- .coerce_state_to_fips(state)
    preds <- c(preds, sprintf("fips_state = %s", .sql_lit_chr(st_fips)))
  }
  if (!is.null(type)) {
    int_type <- .coerce_type(type)
    preds <- c(preds, sprintf("govs_type = %d", int_type))
  }

  where <- if (length(preds) == 0L) "" else paste("WHERE", paste(preds, collapse = " AND "))
  sql <- paste(
    "SELECT * FROM canonical_fips_xwalk",
    where,
    "ORDER BY population_acs DESC NULLS LAST"
  )
  tibble::as_tibble(DBI::dbGetQuery(con, sql))
}

#' @noRd
.empty_xwalk_tibble <- function() {
  tibble::tibble(
    canonical_govid = character(0), gov_name = character(0),
    govs_type = integer(0), type_label = character(0),
    fips_state = character(0), fips_county = character(0),
    fips_place = character(0), first_year = integer(0),
    last_year = integer(0), population_acs = integer(0),
    confidence = character(0)
  )
}

#' @noRd
.is_excluded_type <- function(type) {
  excluded <- c("4", "5", "special_district", "school_district")
  as.character(type) %in% excluded
}

#' @noRd
.coerce_type <- function(type) {
  if (is.numeric(type) ||
      (is.character(type) && length(type) == 1L && grepl("^[0-9]+$", type))) {
    n <- as.integer(type)
    if (!n %in% 0:3) {
      cli::cli_abort("type must be 0, 1, 2, or 3 (v0.1 scope).")
    }
    return(n)
  }
  map <- c(state = 0L, county = 1L, city = 2L, township = 3L)
  key <- as.character(type)
  if (!key %in% names(map)) cli::cli_abort("Unknown type: {type}.")
  map[[key]]
}

#' @noRd
.coerce_state_to_fips <- function(state) {
  if (is.numeric(state) ||
      (is.character(state) && length(state) == 1L && grepl("^[0-9]+$", state))) {
    return(sprintf("%02d", as.integer(state)))
  }
  if (!is.character(state) || length(state) != 1L) {
    cli::cli_abort("`state` must be a 2-letter USPS abbrev or a FIPS integer.")
  }
  fips <- .state_abbrev_to_fips[[toupper(state)]]
  if (is.null(fips)) {
    cli::cli_abort("Unknown state abbreviation: {state}.")
  }
  fips
}

# USPS state / territory abbreviation -> 2-digit FIPS code.
# Includes 50 states + DC + territories. Note FIPS 66 = GU (not GA).
#' @noRd
.state_abbrev_to_fips <- c(
  AL = "01", AK = "02", AZ = "04", AR = "05", CA = "06", CO = "08",
  CT = "09", DE = "10", DC = "11", FL = "12", GA = "13", HI = "15",
  ID = "16", IL = "17", IN = "18", IA = "19", KS = "20", KY = "21",
  LA = "22", ME = "23", MD = "24", MA = "25", MI = "26", MN = "27",
  MS = "28", MO = "29", MT = "30", NE = "31", NV = "32", NH = "33",
  NJ = "34", NM = "35", NY = "36", NC = "37", ND = "38", OH = "39",
  OK = "40", OR = "41", PA = "42", RI = "44", SC = "45", SD = "46",
  TN = "47", TX = "48", UT = "49", VT = "50", VA = "51", WA = "53",
  WV = "54", WI = "55", WY = "56",
  AS = "60", GU = "66", MP = "69", PR = "72", VI = "78"
)