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#' Download TIGER shapes for congressional districts
#'
#' @templateVar state TRUE
#' @templateVar year TRUE
#' @template template
#'
#' @return sf data.frame
#' @export
#'
#' @concept districts
#'
#' @examples
#' \donttest{ # takes > 5 seconds
#' # Wrapped in try due to false positive 304 errors
#' \donttest{try(tt_congressional_districts())} # downloads slow on CRAN
#' }
tt_congressional_districts <- function(state, year = 2022) {
years_okay(year, 2011:2022)
cong <- switch(
as.character(year),
"2022" = "116", "2020" = "116", "2019" = "116", "2018" = "116",
"2017" = "115", "2016" = "115", "2015" = "114", "2014" = "114",
"2013" = "113", "2012" = "112", "2011" = "112"
)
cli::cli_inform("Downloading congressional districts for Congress {.val {cong}}.")
zip_url <- glue::glue("{base_url(year)}/CD/tl_{year}_us_cd{cong}.zip")
target <- paste0("tl_", year, "_us_cd", cong, ".shp")
shp <- tt_download_read(url = zip_url, target_file = target)
if (!missing(state)) {
shp <- shp[shp$STATEFP %in% state_lookup(state), ]
}
adj_class(shp)
}
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