#' Retrieve ILINet Surveillance Data
#'
#' The CDC FluView Portal provides in-season and past seasons' national, regional,
#' and state-level outpatient illness and viral surveillance data from both
#' ILINet (Influenza-like Illness Surveillance Network) and WHO/NREVSS
#' (National Respiratory and Enteric Virus Surveillance System).
#'
#' This function retrieves current and historical ILINet surveillance data for
#' the identified region.
#'
#' @md
#' @param region one of "`national`", "`hhs`", "`census`", or "`state`"
#' @param years a vector of years to retrieve data for (i.e. `2014` for CDC
#'        flu season 2014-2015). CDC has data for this API going back to 1997.
#'        Default value (`NULL`) means retrieve **all** years. NOTE: if you
#'        happen to specify a 2-digit season value (i.e. `57` == 2017-2018)
#'        the function is smart enough to retrieve by season ID vs convert that
#'        to a year.
#' @references
#' - [CDC FluView Portal](https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html)
#' - [ILINet Portal](https://wwwn.cdc.gov/ilinet/) (Login required)
#' - [WHO/NREVSS](https://www.cdc.gov/surveillance/nrevss/index.html)
#' @export
#' @examples
#' national_ili <- ilinet("national", years = 2017)
#' \dontrun{
#' hhs_ili <- ilinet("hhs")
#' census_ili <- ilinet("census")
#' state_ili <- ilinet("state")
#'
#' library(purrr)
#' map_df(
#'   c("national", "hhs", "census", "state"),
#'   ~ ilinet(.x)
#' )
#' }
ilinet <- function(region = c("national", "hhs", "census", "state"), years = NULL) {

  #region="national"; years=1997:2018

  region <- match.arg(tolower(region), c("national", "hhs", "census", "state"))

  meta <- jsonlite::fromJSON("https://gis.cdc.gov/grasp/flu2/GetPhase02InitApp?appVersion=Public")

  list(
    AppVersion = "Public",
    DatasourceDT = list(list(ID = 1, Name = "ILINet")),
    RegionTypeId = .region_map[region]
  ) -> params

  params$SubRegionsDT <- switch(region,
    national = {
      list(list(ID = 0, Name = ""))
    },
    hhs = {
      lapply(1:10, function(i) list(ID = i, Name = as.character(i)))
    },
    census = {
      lapply(1:9, function(i) list(ID = i, Name = as.character(i)))
    },
    state = {
      lapply(1:59, function(i) list(ID = i, Name = as.character(i)))
    }
  )

  available_seasons <- sort(meta$seasons$seasonid)

  if (is.null(years)) { # ALL YEARS
    years <- available_seasons
  } else { # specified years or seasons or a mix

    years <- as.numeric(years)
    years <- ifelse(years > 1996, years - 1960, years)
    years <- sort(unique(years))
    years <- years[years %in% available_seasons]

    if (length(years) == 0) {
      years <- rev(sort(meta$seasons$seasonid))[1]
      curr_season_descr <- meta$seasons[meta$seasons$seasonid == years, "description"]
      message(sprintf(
        "No valid years specified, defaulting to this flu season => ID: %s [%s]",
        years, curr_season_descr
      ))
    }
  }

  params$SeasonsDT <- lapply(years, function(i) list(ID = i, Name = as.character(i)))

  tf <- tempfile(fileext = ".zip")
  td <- tempdir()

  on.exit(unlink(tf), TRUE)

  httr::POST(
    url = "https://gis.cdc.gov/grasp/flu2/PostPhase02DataDownload",
    httr::user_agent(.cdcfluview_ua),
    httr::add_headers(
      Origin = "https://gis.cdc.gov",
      Accept = "application/json, text/plain, */*",
      Referer = "https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html"
    ),
    encode = "json",
    body = params,
    # httr::verbose(),
    httr::write_disk(tf)
  ) -> res

  httr::stop_for_status(res)

  nm <- unzip(tf, overwrite = TRUE, exdir = td)

  xdf <- read.csv(nm, skip = 1, stringsAsFactors = FALSE)
  xdf <- .mcga(xdf)

  xdf$weighted_ili <- to_num(xdf$weighted_ili)
  xdf$unweighted_ili <- to_num(xdf$unweighted_ili)
  xdf$age_0_4 <- to_num(xdf$age_0_4)
  xdf$age_25_49 <- to_num(xdf$age_25_49)
  xdf$age_25_64 <- to_num(xdf$age_25_64)
  xdf$age_5_24 <- to_num(xdf$age_5_24)
  xdf$age_50_64 <- to_num(xdf$age_50_64)
  xdf$age_65 <- to_num(xdf$age_65)
  xdf$ilitotal <- to_num(xdf$ilitotal)
  xdf$num_of_providers <- to_num(xdf$num_of_providers)
  xdf$total_patients <- to_num(xdf$total_patients)
  xdf$week_start <- MMWRweek::MMWRweek2Date(xdf$year, xdf$week)

  if (region == "national") xdf$region <- "National"
  if (region == "hhs") xdf$region <- factor(xdf$region, levels = sprintf("Region %s", 1:10))

  class(xdf) <- c("tbl_df", "tbl", "data.frame")

  arrange(suppressMessages(readr::type_convert(xdf)), week_start)

}