R/utils.R

In deeplr: Interface to the 'DeepL' Translation API

#' @importFrom httr modify_url POST content
#' @importFrom tibble tibble
#'
#' @noRd
translate_wh <- function(text, target_lang = "EN", source_lang = NULL, split_sentences = TRUE,
                      preserve_formatting = FALSE, get_detect = FALSE, auth_key = "your_key") {

  # Text prep
  text <- text_check(text)
  if (split_sentences) {
    split_sentences <- "1"
  } else {
    split_sentences <- "0"
  }
  if (preserve_formatting) {
    preserve_formatting <- "1"
  } else {
    preserve_formatting <- "0"
  }

  # DeepL API call
  response <- httr::POST(
    url = "https://api.deepl.com/v2/translate",
    body = list(
      text = text,
      source_lang = source_lang,
      target_lang = target_lang,
      split_sentences = split_sentences,
      preserve_formatting = preserve_formatting
      ),
    httr::add_headers("Authorization" = paste("DeepL-Auth-Key", auth_key))
  )

  # Check for HTTP error
  response_check(response)

  # Extract content
  translations <- httr::content(response)[["translations"]]
  if (get_detect) {

    translation <- tibble::tibble(
      translation = purrr::map_chr(translations, "text"),
      source_lang = purrr::map_chr(translations, "detected_source_language")
    )

  } else {

    translation <- purrr::map_chr(translations, "text")

  }

  # Return
  return(translation)

}

#' @importFrom httr modify_url POST content
#' @importFrom tibble tibble
#'
#' @noRd
translate2_wh <- function(text, target_lang = "EN", source_lang = NULL, split_sentences = TRUE,
                         preserve_formatting = FALSE, get_detect = FALSE, auth_key = "your_key") {

  # Text prep
  text <- text_check(text)
  if (split_sentences) {
    split_sentences <- "1"
  } else {
    split_sentences <- "0"
  }
  if (preserve_formatting) {
    preserve_formatting <- "1"
  } else {
    preserve_formatting <- "0"
  }

  # DeepL API call
  response <- httr::POST(
    url = "https://api-free.deepl.com/v2/translate",
    body = list(
      text = text,
      source_lang = source_lang,
      target_lang = target_lang,
      split_sentences = split_sentences,
      preserve_formatting = preserve_formatting
      ),
    httr::add_headers("Authorization" = paste("DeepL-Auth-Key", auth_key))
  )

  # Check for HTTP error
  response_check(response)

  # Extract content
  translations <- httr::content(response)[["translations"]]
  if (get_detect) {

    translation <- tibble::tibble(
      translation = purrr::map_chr(translations, "text"),
      source_lang = purrr::map_chr(translations, "detected_source_language")
    )

  } else {

    translation <- purrr::map_chr(translations, "text")

  }

  # Return
  return(translation)

}

#' @importFrom utf8 utf8_valid as_utf8
#'
#' @noRd
text_check <- function(text) {

  # Check for text
  if (is.null(text)) stop("Text input is missing.")

  # Coerce non-character vectors to a character vector
  if (!is.character(text)) message("Text input had to be coerced to a character vector.")
  text <- as.character(text)

  # Check if text can be translated to valid UTF-8 string
  if (!utf8::utf8_valid(text)) stop("Text input cannot be translated to a valid UTF-8 string.")
  text <- utf8::as_utf8(text)

  return(text)
}

#' @importFrom httr status_code
#'
#' @noRd
response_check <- function(response) {
  status <- httr::status_code(response)
  if (status == 400) stop("Bad request. Please check error message and your parameters.")
  if (status == 403) stop("Authorization failed. Please supply a valid auth_key parameter.")
  if (status == 404) stop("The requested resource could not be found.")
  if (status == 413) stop("The request size exceeds the limit.")
  if (status == 414) stop("The request URL is too long. You can avoid this error by using a POST request instead of a GET request.")
  if (status == 429) stop("Too many requests. Please wait and resend your request.")
  if (status == 456) stop("Quota exceeded. The character limit has been reached.")
  if (status == 503) stop("Resource currently unavailable. Try again later.")
}

#' @importFrom tokenizers tokenize_sentences
#' @importFrom tibble tibble
#' @importFrom purrr map_chr
#'
#' @noRd
split_text_wh <- function(id, text, max_size_bytes, tokenize) {

  if (tokenize == "sentences") sentences <- tokenizers::tokenize_sentences(text)
  if (tokenize == "words") sentences <- tokenizers::tokenize_words(text)

  cnt <- tibble::tibble(
    sentence = unlist(sentences),
    bytes = nchar(sentence, type = "bytes"),
    bytes_sum = cumsum(bytes),
    batch = ceiling(bytes_sum / max_size_bytes)
    )

  batches <- split(cnt, cnt$batch)

  batches <- tibble::tibble(
    text_id = id,
    segment_id = 1:length(batches),
    segment_text = purrr::map_chr(batches, function(x) paste0(x[["sentence"]], collapse = " "))
    )

  return(batches)

}