R/list_videocats.R

In tuber: Client for the YouTube API

#' List of Categories That Can be Associated with Videos
#' 
#' @param filter string; Required.
#' named vector of length 1
#' potential names of the entry in the vector: 
#' \code{region_code}: Character. Required. Has to be a ISO 3166-1 alpha-2 code (see \url{https://www.iso.org/obp/ui/#search})
#' \code{category_id}: video category ID
#'
#' @param \dots Additional arguments passed to \code{\link{tuber_GET}}.
#' 
#' @return data.frame with 6 columns: \code{region_code, channelId, title, assignable, etag, id}
#' @export
#' @references \url{https://developers.google.com/youtube/v3/docs/videoCategories/list}
#' 
#' @examples
#' \dontrun{
#' 
#' # Set API token via yt_oauth() first
#' 
#' list_videocats(c(region_code = "JP"))
#' list_videocats() # Will throw an error asking for a valid filter with valid region_code
#' }

list_videocats <- function (filter = NULL, ...) {

  if (!is.character(filter)) {
    stop("Specify by a valid filter with a valid region code.")
  }

  translate_filter   <- c(category_id = "id", region_code = "regionCode")
  yt_filter_name     <- as.vector(translate_filter[match(names(filter),
                                                      names(translate_filter))])
  names(filter)      <- yt_filter_name

  if (sum(is.na(names(filter)) > 0 )) {
    stop("Filter can only have region_code or category_id.")
  }

  querylist <- c(list(part = "snippet"), filter)

  res <- tuber_GET("videoCategories", querylist, ...)

  # Cat total results
  cat("Total Number of Categories:", length(res$items), "\n")

  resdf <- read.table(text = "",
               col.names = c("region_code", "channelId", "title", "assignable",
                             "etag", "id"))

  if (length(res$items) > 0) {

    simple_res  <- lapply(res$items,
                                   function(x) {
                                   c(unlist(x$snippet), etag = x$etag,
                                     id = x$id)
                                   })

    resdf       <- as.data.frame(cbind(region_code = filter["regionCode"],
                                 do.call(rbind, simple_res)))

  } else {

    resdf[1, "region_code"] <- filter["regionCode"]
  }

  resdf
}