receptiviti coverage - 88.70%

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.onLoad <- function(lib, pkg) {
  if (Sys.getenv("RECEPTIVITI_URL") == "") Sys.setenv(RECEPTIVITI_URL = "https://api.receptiviti.com/")
}

#' Receptiviti API
#'
#' The main function to access the \href{https://www.receptiviti.com}{Receptiviti} API.
#'
#' @param text A character vector with text to be processed, path to a directory containing files, or a vector of file paths.
#' If a single path to a directory, each file is collapsed to a single text. If a path to a file or files,
#' each line or row is treated as a separate text, unless \code{collapse_lines} is \code{TRUE}.
#' @param output Path to a \code{.csv} file to write results to. If this already exists, set \code{overwrite} to \code{TRUE}
#' to overwrite it.
#' @param id Vector of unique IDs the same length as \code{text}, to be included in the results.
#' @param text_column,id_column Column name of text/id, if \code{text} is a matrix-like object, or a path to a csv file.
#' @param file_type File extension to search for, if \code{text} is the path to a directory containing files to be read in.
#' @param return_text Logical; if \code{TRUE}, \code{text} is included as the first column of the result.
#' @param frameworks A vector of frameworks to include results from. Texts are always scored with all available framework --
#' this just specifies what to return. Defaults to \code{all}, to return all scored frameworks. Can be set by the
#' \code{receptiviti_frameworks} option (e.g., \code{options(receptiviti_frameworks = c("liwc", "sallee"))}).
#' @param framework_prefix Logical; if \code{FALSE}, will remove the framework prefix from column names, which may result in duplicates.
#' If this is not specified, and 1 framework is selected, or \code{as_list} is \code{TRUE}, will default to remove prefixes.
#' @param as_list Logical; if \code{TRUE}, returns a list with frameworks in separate entries.
#' @param bundle_size Number of texts to include in each request; between 1 and 1,000.
#' @param collapse_lines Logical; if \code{TRUE}, and \code{text} contains paths to files, each file is treated as a single text.
#' @param retry_limit Maximum number of times each request can be retried after hitting a rate limit.
#' @param overwrite Logical; if \code{TRUE}, will overwrite an existing \code{output} file.
#' @param compress Logical; if \code{TRUE}, will save as an \code{xz}-compressed file.
#' @param make_request Logical; if \code{FALSE}, a request is not made. This could be useful if you want to be sure and
#' load from one of the caches, but aren't sure that all results exist there; it will error out if it encounters
#' texts it has no other source for.
#' @param text_as_paths Logical; if \code{TRUE}, ensures \code{text} is treated as a vector of file paths. Otherwise, this will be
#' determined if there are no \code{NA}s in \code{text} and every entry is under 500 characters long.
#' @param cache Path to a directory in which to save unique results for reuse; defaults to \code{Sys.getenv("RECEPTIVITI_CACHE")}.
#' See the Cache section for details.
#' @param cache_overwrite Logical; if \code{TRUE}, will write results to the cache without reading from it. This could be used
#' if you want fresh results to be cached without clearing the cache.
#' @param cache_format Format of the cache database; see \code{\link[arrow]{FileFormat}}.
#' Defaults to \code{Sys.getenv("RECEPTIVITI_CACHE_FORMAT")}.
#' @param clear_cache Logical; if \code{TRUE}, will clear any existing files in the cache. Use \code{cache_overwrite} if
#' you want fresh results without clearing or disabling the cache. Use \code{cache = FALSE} to disable the cache.
#' @param request_cache Logical; if \code{FALSE}, will always make a fresh request, rather than using the response
#' from a previous identical request.
#' @param cores Number of CPU cores to split bundles across, if there are multiple bundles. See the Parallelization section.
#' @param use_future Logical; if \code{TRUE}, uses a \code{future} back-end to process bundles, in which case,
#' parallelization can be controlled with the \code{\link[future]{plan}} function (e.g., \code{plan("multisession")}
#' to use multiple cores); this is required to see progress bars when using multiple cores. See the Parallelization section.
#' @param in_memory Logical; if \code{FALSE}, will write bundles to temporary files, and only load them as they are being requested.
#' @param clear_scratch_cache Logical; if \code{FALSE}, will preserve the bundles written when \code{in_memory} is \code{TRUE}, after
#' the request has been made.
#' @param verbose Logical; if \code{TRUE}, will show status messages.
#' @param key API Key; defaults to \code{Sys.getenv("RECEPTIVITI_KEY")}.
#' @param secret API Secret; defaults to \code{Sys.getenv("RECEPTIVITI_SECRET")}.
#' @param url API endpoint; defaults to \code{Sys.getenv("RECEPTIVITI_URL")}, which defaults to
#' \code{"https://api.receptiviti.com/"}.
#' @param include_headers Logical; if \code{TRUE}, \code{receptiviti_status}'s verbose message will include
#' the HTTP headers.
#'
#' @returns A \code{data.frame} with columns for \code{text} (if \code{return_text} is \code{TRUE}; the originally entered text),
#' \code{id} (if one was provided), \code{text_hash} (the MD5 hash of the text), and scores from each included framework
#' (e.g., \code{summary.word_count} and \code{liwc.i}). If \code{as_list} is \code{TRUE}, returns a list
#' with a named entry containing such a \code{data.frame} for each framework.
#'
#' @section Cache:
#' By default, results for unique texts are saved in an \href{https://arrow.apache.org}{Arrow} database in the
#' cache location (\code{Sys.getenv("RECEPTIVITI_CACHE")}), and are retrieved with subsequent requests.
#' This ensures that the exact same texts are not re-sent to the API.
#' This does, however, add some processing time and disc space usage.
#'
#' If a cache location is not specified, a default directory (\code{receptiviti_cache}) will be looked for
#' in the system's temporary directory (which is usually the parent of \code{tempdir()}).
#' If this does not exist, you will be asked if it should be created. You can disable this prompt with the
#' \code{receptiviti.cache_prompt} option (\code{options(receptiviti.cache_prompt = FALSE)}).
#'
#' The \code{cache_format} arguments (or the \code{RECEPTIVITI_CACHE_FORMAT} environment variable) can be used to adjust the format of the cache.
#'
#' You can use the cache independently with \code{open_database(Sys.getenv("RECEPTIVITI_CACHE"))}.
#'
#' You can set the \code{cache} argument to \code{FALSE} to prevent the cache from being used, which might make sense if
#' you don't expect to need to reprocess it.
#'
#' You can also set the \code{clear_cache} argument to \code{TRUE} to clear the cache before it is used again, which may be useful
#' if the cache has gotten big, or you know new results will be returned. Even if a cached result exists, it will be
#' reprocessed if it does not have all of the variables of new results, but this depends on there being at least 1 uncached
#' result. If, for instance, you add a framework to your account and want to reprocess a previously processed set of texts,
#' you would need to first clear the cache.
#'
#' Either way, duplicated texts within the same call will only be sent once.
#'
#' The \code{request_cache} argument controls a more temporary cache of each bundle request. This is cleared when the
#' R session ends. You might want to set this to \code{FALSE} if a new framework becomes available on your account
#' and you want to process a set of text you already processed in the current R session without restarting.
#'
#' Another temporary cache is made when \code{in_memory} is \code{FALSE}, which is the default when processing
#' in parallel (when \code{cores} is over \code{1} or \code{use_future} is \code{TRUE}). This contains
#' a file for each unique bundle, which is read by as needed by the parallel workers.
#'
#' @section Parallelization:
#' \code{text}s are split into bundles based on the \code{bundle_size} argument. Each bundle represents
#' a single request to the API, which is why they are limited to 1000 texts and a total size of 10 MB.
#' When there is more than one bundle and either \code{cores} is greater than 1 or \code{use_future} is \code{TRUE} (and you've
#' externally specified a \code{\link[future]{plan}}), bundles are processed by multiple cores.
#'
#' Using \code{future} also allows for progress bars to be specified externally with \code{\link[progressr]{handlers}}; see examples.
#' @examples
#' \dontrun{
#'
#' # check that the API is available, and your credentials work
#' receptiviti_status()
#'
#' # score a single text
#' single <- receptiviti("a text to score")
#'
#' # score multiple texts, and write results to a file
#' multi <- receptiviti(c("first text to score", "second text"), "filename.csv")
#'
#' # score many texts in separate files
#' ## defaults to look for .txt files
#' file_results <- receptiviti("./path/to/txt_folder")
#'
#' ## could be .csv
#' file_results <- receptiviti(
#'   "./path/to/csv_folder",
#'   text_column = "text", file_type = "csv"
#' )
#'
#' # score many texts from a file, with a progress bar
#' ## set up cores and progress bar (only necessary if you want the progress bar)
#' future::plan("multisession")
#' progressr::handlers(global = TRUE)
#' progressr::handlers("progress")
#'
#' ## make request
#' results <- receptiviti(
#'   "./path/to/largefile.csv",
#'   text_column = "text", use_future = TRUE
#' )
#' }
#' @importFrom curl new_handle curl_fetch_memory curl_fetch_disk
#' @importFrom jsonlite toJSON fromJSON read_json
#' @importFrom utils object.size
#' @importFrom digest digest
#' @importFrom parallel detectCores makeCluster clusterExport parLapplyLB parLapply stopCluster
#' @importFrom future.apply future_lapply
#' @importFrom progressr progressor
#' @importFrom arrow read_csv_arrow write_csv_arrow schema string write_dataset open_dataset
#' @importFrom dplyr filter compute collect select
#' @export

receptiviti <- function(text, output = NULL, id = NULL, text_column = NULL, id_column = NULL, file_type = "txt", return_text = FALSE,
                        frameworks = getOption("receptiviti_frameworks", "all"), framework_prefix = TRUE, as_list = FALSE,
                        bundle_size = 1000, collapse_lines = FALSE, retry_limit = 10, clear_cache = FALSE, clear_scratch_cache = TRUE,
                        request_cache = TRUE, cores = detectCores() - 1, use_future = FALSE, in_memory = TRUE, verbose = FALSE,
                        overwrite = FALSE, compress = FALSE, make_request = TRUE, text_as_paths = FALSE, cache = Sys.getenv("RECEPTIVITI_CACHE"),
                        cache_overwrite = FALSE, cache_format = Sys.getenv("RECEPTIVITI_CACHE_FORMAT", "parquet"),
                        key = Sys.getenv("RECEPTIVITI_KEY"), secret = Sys.getenv("RECEPTIVITI_SECRET"), url = Sys.getenv("RECEPTIVITI_URL")) {
  # check input
  final_res <- text_hash <- bin <- NULL
  if (!is.null(output)) {
    if (!file.exists(output) && file.exists(paste0(output, ".xz"))) output <- paste0(output, ".xz")
    if (!overwrite && file.exists(output)) stop("output file already exists; use overwrite = TRUE to overwrite it", call. = FALSE)
  }
  if (cache == "") {
    temp <- dirname(tempdir())
    if (basename(temp) == "working_dir") temp <- dirname(dirname(temp))
    cache <- paste0(temp, "/receptiviti_cache")
    if (!dir.exists(cache)) {
      if (interactive() && !isFALSE(getOption("receptiviti.cache_prompt")) &&
        grepl("^(?:[Yy1]|$)", readline("Do you want to establish a default cache? [Y/n] "))) {
        dir.create(cache, FALSE)
      } else {
        options(receptiviti.cache_prompt = FALSE)
        cache <- ""
      }
    }
  }
  st <- proc.time()[[3]]
  if (is.null(final_res)) {
    if (missing(text)) stop("enter text as the first argument", call. = FALSE)
    if (text_as_paths) {
      if (anyNA(text)) stop("NAs are not allowed in text when being treated as file paths", call. = FALSE)
      if (!all(file.exists(text))) stop("not all of the files in text exist", call. = FALSE)
    }
    read_in <- FALSE
    if (text_as_paths || (is.character(text) && !anyNA(text) && all(nchar(text) < 500))) {
      if (length(text) == 1 && dir.exists(text)) {
        if (verbose) message("reading in texts from directory: ", text, " (", round(proc.time()[[3]] - st, 4), ")")
        text_as_paths <- TRUE
        text <- list.files(text, file_type, full.names = TRUE)
      } else if (text_as_paths || all(file.exists(text))) {
        text_as_paths <- FALSE
        if (verbose) message("reading in texts from file list (", round(proc.time()[[3]] - st, 4), ")")
        if (missing(id_column)) names(text) <- if (length(id) != length(text)) text else id
        if (all(grepl(".csv", text, fixed = TRUE))) {
          if (is.null(text_column)) stop("text appears to point to csv files, but text_column was not specified", call. = FALSE)
          read_in <- TRUE
          text <- unlist(lapply(text, function(f) {
            if (file.exists(f)) {
              d <- read_csv_arrow(f)
              d <- if (!is.null(id_column) && id_column %in% colnames(d)) {
                structure(d[, text_column, drop = TRUE], names = d[, id_column, drop = TRUE])
              } else {
                d[, text_column, drop = TRUE]
              }
              if (collapse_lines) d <- paste(d, collapse = " ")
              d
            } else {
              f
            }
          }))
        } else {
          text <- unlist(lapply(text, function(f) {
            if (file.exists(f)) {
              d <- readLines(f, warn = FALSE, skipNul = TRUE)
              if (collapse_lines) d <- paste(d, collapse = " ")
              d
            } else {
              f
            }
          }))
        }
        if (!collapse_lines) id <- names(text)
      }
    }
    if (is.null(dim(text))) {
      if (!read_in) {
        if (!text_as_paths && !is.null(text_column)) stop("text_column is specified, but text has no columns", call. = FALSE)
        if (!is.null(id_column)) stop("id_column is specified, but text has no columns", call. = FALSE)
      }
    } else {
      if (length(id) == 1 && id %in% colnames(text)) id_column <- id
      if (!is.null(id_column)) {
        if (id_column %in% colnames(text)) {
          id <- text[, id_column, drop = TRUE]
        } else {
          stop("id_column not found in text", call. = FALSE)
        }
      }
      if (!is.null(text_column)) {
        if (text_column %in% colnames(text)) {
          text <- text[, text_column, drop = TRUE]
        } else {
          if (!text_as_paths) stop("text_column not found in text", call. = FALSE)
        }
      }
      if (!is.null(dim(text))) {
        if (ncol(text) == 1) {
          text <- text[, 1, drop = TRUE]
        } else {
          stop("text has dimensions, but no text_column column", call. = FALSE)
        }
      }
    }
    if (!is.character(text)) text <- as.character(text)
    if (length(id) && !is.character(id)) id <- as.character(id)
    provided_id <- FALSE
    if (length(id)) {
      if (length(id) != length(text)) stop("id is not the same length as text", call. = FALSE)
      if (anyDuplicated(id)) stop("id contains duplicate values", call. = FALSE)
      provided_id <- TRUE
    } else {
      id <- paste0("t", seq_along(text))
    }
    if (!is.numeric(retry_limit)) retry_limit <- 0
    url <- paste0(sub("(?:/v\\d+)?/+$", "", url), "/v1/")

    # ping API
    if (make_request) {
      if (verbose) message("pinging API (", round(proc.time()[[3]] - st, 4), ")")
      ping <- receptiviti_status(url, key, secret, verbose = FALSE)
      if (ping$status_code != 200) stop(ping$status_message, call. = FALSE)
    }

    # prepare text
    if (verbose) message("preparing text (", round(proc.time()[[3]] - st, 4), ")")
    data <- data.frame(text = text, id = id, stringsAsFactors = FALSE)
    text <- data[!is.na(data$text) & data$text != "" & !duplicated(data$text), ]
    if (!nrow(text)) stop("no valid texts to process", call. = FALSE)
    if (!is.numeric(bundle_size)) bundle_size <- 1000
    n <- ceiling(nrow(text) / min(1000, max(1, bundle_size)))
    bundles <- split(text, sort(rep_len(seq_len(n), nrow(text))))
    size_fun <- if (text_as_paths) function(b) sum(file.size(b$text)) else object.size
    for (i in seq_along(bundles)) {
      size <- size_fun(bundles[[i]])
      if (size > 1e7) {
        sizes <- vapply(seq_len(nrow(bundles[[i]])), function(r) as.numeric(size_fun(bundles[[i]][r, ])), 0)
        if (any(sizes > 1e7)) stop("one of your texts is over the individual size limit (10 MB)", call. = FALSE)
        bins <- rep(1, length(sizes))
        bin_size <- 0
        bi <- 1
        for (ti in seq_along(bins)) {
          bin_size <- bin_size + sizes[ti]
          if (bin_size > 1e7) {
            bin_size <- sizes[ti]
            bi <- bi + 1
          }
          bins[ti] <- bi
        }
        bundles <- c(bundles[-i], unname(split(bundles[[i]], paste0(i, ".", bins))))
      }
    }
    n <- length(bundles)
    bundle_ref <- if (n == 1) "bundle" else "bundles"
    if (verbose) message("prepared text in ", n, " ", bundle_ref, " (", round(proc.time()[[3]] - st, 4), ")")

    # prepare cache
    if (is.character(cache)) {
      temp <- paste0(normalizePath(cache, "/", FALSE), "/")
      cache <- TRUE
      if (clear_cache) unlink(temp, recursive = TRUE)
      dir.create(temp, FALSE)
    } else {
      temp <- NULL
      cache <- FALSE
    }

    check_cache <- cache && !cache_overwrite
    endpoint <- paste0(url, "framework/bulk")
    auth <- paste0(key, ":", secret)
    if (missing(in_memory) && (use_future || cores > 1) && n > cores) in_memory <- FALSE
    request_scratch <- NULL
    if (!in_memory) {
      if (verbose) message("writing ", bundle_ref, " to disc (", round(proc.time()[[3]] - st, 4), ")")
      request_scratch <- paste0(tempdir(), "/receptiviti_request_scratch/")
      dir.create(request_scratch, FALSE)
      if (clear_scratch_cache) on.exit(unlink(request_scratch, recursive = TRUE))
      bundles <- vapply(bundles, function(b) {
        scratch_bundle <- paste0(request_scratch, digest(b), ".rds")
        if (!file.exists(scratch_bundle)) saveRDS(b, scratch_bundle, compress = FALSE)
        scratch_bundle
      }, "", USE.NAMES = FALSE)
    }

    doprocess <- function(bundles, cores, future) {
      env <- parent.frame()
      if (future) {
        eval(expression(future.apply::future_lapply(bundles, process)), envir = env)
      } else {
        cl <- parallel::makeCluster(cores)
        parallel::clusterExport(cl, ls(envir = env), env)
        on.exit(parallel::stopCluster(cl))
        (if (length(bundles) > cores * 2) parallel::parLapplyLB else parallel::parLapply)(cl, bundles, process)
      }
    }

    request <- function(body, bin, ids, attempt = retry_limit) {
      unpack <- function(d) {
        if (is.list(d)) as.data.frame(lapply(d, unpack), optional = TRUE) else d
      }
      json <- jsonlite::toJSON(body, auto_unbox = TRUE)
      temp_file <- paste0(tempdir(), "/", digest::digest(json, serialize = FALSE), ".json")
      if (!request_cache) unlink(temp_file)
      res <- NULL
      if (!file.exists(temp_file)) {
        if (make_request) {
          handler <- curl::new_handle(
            httpauth = 1, userpwd = auth,
            copypostfields = jsonlite::toJSON(unname(body), auto_unbox = TRUE)
          )
          res <- curl::curl_fetch_disk(endpoint, temp_file, handler)
        } else {
          stop("make_request is FALSE, but there are texts with no cached results", call. = FALSE)
        }
      }
      result <- if (file.exists(temp_file)) {
        jsonlite::read_json(temp_file, simplifyVector = TRUE)
      } else {
        list(message = rawToChar(res$content))
      }
      if (!is.null(result$results)) {
        result <- result$results
        if ("error" %in% names(result)) {
          su <- !is.na(result$error$code)
          errors <- result[su & !duplicated(result$error$code), "error"]
          warning(
            if (sum(su) > 1) "some texts were invalid: " else "a text was invalid: ",
            paste(
              do.call(paste0, data.frame("(", errors$code, ") ", errors$message, stringsAsFactors = FALSE)),
              collapse = "; "
            ),
            call. = FALSE
          )
        }
        result <- unpack(result[!names(result) %in% c("response_id", "language", "version", "error")])
        if (!is.null(result) && nrow(result)) {
          colnames(result)[1] <- "text_hash"
          cbind(id = ids, bin = bin, result)
        }
      } else {
        if (substr(result$message, 1, 1) == "{") result <- jsonlite::fromJSON(result$message)
        if (!is.null(result$code) && result$code == 1420 && attempt > 0) {
          unlink(temp_file)
          wait_time <- as.numeric(regmatches(result$message, regexec("[0-9]+(?:\\.[0-9]+)?", result$message)))
          Sys.sleep(if (is.na(wait_time)) 1 else wait_time / 1e3)
          request(body, bin, ids, attempt - 1)
        } else {
          stop(paste0(if (length(result$code)) {
            paste0(
              if (is.null(res$status_code)) 200 else res$status_code, " (", result$code, "): "
            )
          }, result$message), call. = FALSE)
        }
      }
    }

    process <- function(bundle) {
      opts <- getOption("stringsAsFactors")
      options("stringsAsFactors" = FALSE)
      on.exit(options("stringsAsFactors" = opts))
      if (is.character(bundle)) bundle <- readRDS(bundle)
      text <- bundle$text
      bin <- NULL
      if (text_as_paths) {
        if (all(grepl("\\.csv", text))) {
          if (is.null(text_column)) stop("files appear to be csv, but no text_column was specified", call. = FALSE)
          text <- vapply(text, function(f) paste(arrow::read_csv_arrow(f)[, text_column], collapse = " "), "")
        } else {
          text <- vapply(text, function(f) paste(readLines(f, warn = FALSE, skipNul = TRUE), collapse = " "), "")
        }
      }
      bundle$hashes <- vapply(text, digest::digest, "", serialize = FALSE)
      initial <- paste0("h", substr(bundle$hashes, 1, 1))
      set <- !is.na(text) & text != "" & text != "logical(0)" & !duplicated(bundle$hashes)
      res_cached <- res_fresh <- NULL
      if (check_cache && dir.exists(paste0(temp, "bin=h"))) {
        db <- arrow::open_dataset(temp, partitioning = arrow::schema(bin = arrow::string()), format = cache_format)
        cached <- if (!is.null(db$schema$GetFieldByName("text_hash"))) {
          tryCatch(
            dplyr::compute(dplyr::filter(db, bin %in% unique(initial), text_hash %in% bundle$hashes)),
            error = function(e) matrix(integer(), 0)
          )
        } else {
          matrix(integer(), 0)
        }
        if (nrow(cached)) {
          cached <- as.data.frame(cached$to_data_frame())
          if (anyDuplicated(cached$text_hash)) cached <- cached[!duplicated(cached$text_hash), ]
          rownames(cached) <- cached$text_hash
          cached_set <- bundle$hashes %in% cached$text_hash
          set[cached_set] <- FALSE
          res_cached <- cbind(id = bundle[cached_set, "id"], cached[bundle[cached_set, "hashes"], ])
        }
      }
      if (any(set)) {
        set <- which(set)
        res_fresh <- request(lapply(
          set, function(i) list(content = text[[i]], request_id = bundle[i, "hashes"])
        ), initial[set], bundle[set, "id"])
        if (check_cache && !is.null(res_cached) && !all(colnames(res_cached) %in% colnames(res_fresh))) {
          res_cached <- NULL
          res_fresh <- rbind(
            res_fresh,
            request(lapply(
              cached_set, function(i) list(content = text[[i]], request_id = bundle[i, "hashes"])
            ), initial[cached_set], bundle[cached_set, "ids"])
          )
        }
      }
      res <- rbind(res_cached, res_fresh)
      missing_ids <- !bundle$id %in% res$id
      if (any(missing_ids)) {
        varnames <- colnames(res)[colnames(res) != "id"]
        res <- rbind(res, cbind(
          id = bundle[missing_ids, "id"],
          as.data.frame(matrix(NA, sum(missing_ids), length(varnames), dimnames = list(NULL, varnames)))
        ))
      }
      prog()
      res
    }

    # make request(s)
    cores <- if (is.numeric(cores)) max(1, min(length(bundles), cores)) else 1
    call_env <- new.env(parent = globalenv())
    prog <- progressor(along = bundles)
    environment(doprocess) <- call_env
    environment(request) <- call_env
    environment(process) <- call_env
    for (name in c(
      "doprocess", "request", "process", "text_column", "prog", "make_request", "check_cache", "endpoint",
      "temp", "use_future", "cores", "bundles", "cache_format", "request_cache", "auth",
      "text_as_paths", "retry_limit"
    )) {
      call_env[[name]] <- get(name)
    }
    results <- if (use_future || cores > 1) {
      if (verbose) {
        message(
          "processing ", bundle_ref, " using ", if (use_future) "future backend" else paste(cores, "cores"),
          " (", round(proc.time()[[3]] - st, 4), ")"
        )
      }
      eval(expression(doprocess(bundles, cores, use_future)), envir = call_env)
    } else {
      if (verbose) message("processing ", bundle_ref, " sequentially (", round(proc.time()[[3]] - st, 4), ")")
      lapply(bundles, process)
    }
    if (verbose) message("done retrieving; preparing final results (", round(proc.time()[[3]] - st, 4), ")")
    final_res <- do.call(rbind, results)

    # update cache
    if (!is.null(temp)) {
      if (verbose) message("checking cache (", round(proc.time()[[3]] - st, 4), ")")
      initialized <- dir.exists(paste0(temp, "bin=h"))
      if (initialized) {
        db <- arrow::open_dataset(temp, partitioning = arrow::schema(bin = arrow::string()), format = cache_format)
        if (db$num_cols != (ncol(final_res) - 1)) {
          if (verbose) message("clearing existing cache since columns did not align (", round(proc.time()[[3]] - st, 4), ")")
          if (clear_cache) unlink(temp, recursive = TRUE)
          dir.create(temp, FALSE)
          initialized <- FALSE
        }
      }
      if (!initialized) {
        initial <- final_res[1, -1]
        initial$text_hash <- ""
        initial$bin <- "h"
        initial[, !colnames(initial) %in% c(
          "bin", "text_hash", "summary.word_count", "summary.sentence_count"
        )] <- .1
        initial <- rbind(initial, final_res[, -1])
        if (verbose) {
          message(
            "initializing cache with ", nrow(final_res), " result",
            if (nrow(final_res) > 1) "s", " (", round(proc.time()[[3]] - st, 4), ")"
          )
        }
        arrow::write_dataset(initial, temp, partitioning = "bin", format = cache_format)
      } else {
        fresh <- final_res[!duplicated(final_res$text_hash), -1]
        cached <- dplyr::filter(db, bin %in% unique(fresh$bin), text_hash %in% fresh$text_hash)
        if (!nrow(cached) || nrow(cached) != nrow(fresh)) {
          uncached_hashes <- if (nrow(cached)) {
            !fresh$text_hash %in% dplyr::collect(dplyr::select(cached, text_hash))[, 1]
          } else {
            rep(TRUE, nrow(fresh))
          }
          if (any(uncached_hashes)) {
            if (verbose) {
              message(
                "updating cache with ", sum(uncached_hashes), " result",
                if (sum(uncached_hashes) > 1) "s", " (", round(proc.time()[[3]] - st, 4), ")"
              )
            }
            arrow::write_dataset(fresh[uncached_hashes, ], temp, partitioning = "bin", format = cache_format)
          }
        }
      }
    }

    # prepare final results
    if (verbose) message("preparing output (", round(proc.time()[[3]] - st, 4), ")")
    rownames(final_res) <- final_res$id
    rownames(data) <- data$id
    data$text_hash <- structure(final_res$text_hash, names = data[final_res$id, "text"])[data$text]
    final_res <- cbind(
      data[, c(if (return_text) "text", if (provided_id) "id", "text_hash"), drop = FALSE],
      final_res[
        structure(final_res$id, names = final_res$text_hash)[data$text_hash],
        !colnames(final_res) %in% c("id", "bin", "text_hash", "custom")
      ]
    )
    row.names(final_res) <- NULL
    if (!is.null(output)) {
      if (!grepl(".csv", output, fixed = TRUE)) output <- paste0(output, ".csv")
      if (compress && !grepl(".xz", output, fixed = TRUE)) output <- paste0(output, ".xz")
      if (grepl(".xz", output, fixed = TRUE)) compress <- TRUE
      if (verbose) message("writing results to file: ", output, " (", round(proc.time()[[3]] - st, 4), ")")
      dir.create(dirname(output), FALSE, TRUE)
      if (overwrite) unlink(output)
      if (compress) output <- xzfile(output)
      write_csv_arrow(final_res, file = output)
    }
  }
  if (is.character(frameworks) && frameworks[1] != "all") {
    if (verbose) message("selecting frameworks (", round(proc.time()[[3]] - st, 4), ")")
    vars <- colnames(final_res)
    sel <- grepl(paste0("^(?:", paste(tolower(frameworks), collapse = "|"), ")"), vars)
    if (any(sel)) {
      if (missing(framework_prefix) && (length(frameworks) == 1 && frameworks != "all")) framework_prefix <- FALSE
      sel <- unique(c("text", "id", "text_hash", vars[sel]))
      sel <- sel[sel %in% vars]
      final_res <- final_res[, sel]
    } else {
      warning("frameworks did not match any columns -- returning all", call. = FALSE)
    }
  }
  if (as_list) {
    if (missing(framework_prefix)) framework_prefix <- FALSE
    inall <- c("text", "id", "text_hash")
    cols <- colnames(final_res)
    inall <- inall[inall %in% cols]
    pre <- sub("\\..*$", "", cols)
    pre <- unique(pre[!pre %in% inall])
    final_res <- lapply(structure(pre, names = pre), function(f) {
      res <- final_res[, c(inall, grep(paste0("^", f), cols, value = TRUE))]
      if (!framework_prefix) colnames(res) <- sub("^.+\\.", "", colnames(res))
      res
    })
  } else if (!framework_prefix) colnames(final_res) <- sub("^.+\\.", "", colnames(final_res))
  if (verbose) message("done (", round(proc.time()[[3]] - st, 4), ")")
  invisible(final_res)
}

#' @rdname receptiviti
#' @export

receptiviti_status <- function(url = Sys.getenv("RECEPTIVITI_URL"), key = Sys.getenv("RECEPTIVITI_KEY"),
                               secret = Sys.getenv("RECEPTIVITI_SECRET"), verbose = TRUE, include_headers = FALSE) {
  if (key == "") stop("specify your key, or set it to the RECEPTIVITI_KEY environment variable", call. = FALSE)
  if (secret == "") stop("specify your secret, or set it to the RECEPTIVITI_SECRET environment variable", call. = FALSE)
  handler <- new_handle(httpauth = 1, userpwd = paste0(key, ":", secret))
  url <- paste0(sub("(?:/v\\d+)?/+$", "", url), "/v1/ping")
  ping <- curl_fetch_memory(url, handler)
  ping$content <- list(message = rawToChar(ping$content))
  if (substr(ping$content, 1, 1) == "{") ping$content <- fromJSON(ping$content$message)
  ok <- ping$status_code == 200 && !length(ping$content$code)
  ping$status_message <- if (ok) {
    ping$content$pong
  } else {
    paste0(
      if (length(ping$content$code)) paste0(ping$status_code, " (", ping$content$code, "): "),
      if (nchar(ping$content$message) > 500 || grepl("<", ping$content$message, fixed = TRUE)) {
        ping$status_code
      } else {
        ping$content$message
      }
    )
  }
  if (verbose) {
    message("Status: ", if (ok) "OK" else "ERROR", "\nMessage: ", ping$status_message)
    if (include_headers) {
      ping$headers <- strsplit(rawToChar(ping$headers), "[\r\n]+", perl = TRUE)[[1]]
      json <- regexec("\\{.+\\}", ping$headers)
      for (i in seq_along(json)) {
        if (json[[i]] != -1) {
          regmatches(ping$headers[[i]], json[[i]]) <- paste(" ", strsplit(toJSON(
            fromJSON(regmatches(ping$headers[[i]], json[[i]])),
            auto_unbox = TRUE, pretty = TRUE
          ), "\n")[[1]], collapse = "\n")
        }
      }
      message(paste0("\n", paste(" ", ping$headers, collapse = "\n")))
    }
  }
  invisible(ping)
}

1		#' @rdname receptiviti
2		#' @export
3
4		receptiviti_status <- function(url = Sys.getenv("RECEPTIVITI_URL"), key = Sys.getenv("RECEPTIVITI_KEY"),
5		secret = Sys.getenv("RECEPTIVITI_SECRET"), verbose = TRUE, include_headers = FALSE) {
6	2x	if (key == "") stop("specify your key, or set it to the RECEPTIVITI_KEY environment variable", call. = FALSE)
7	2x	if (secret == "") stop("specify your secret, or set it to the RECEPTIVITI_SECRET environment variable", call. = FALSE)
8	39x	handler <- new_handle(httpauth = 1, userpwd = paste0(key, ":", secret))
9	39x	url <- paste0(sub("(?:/v\\d+)?/+$", "", url), "/v1/ping")
10	39x	ping <- curl_fetch_memory(url, handler)
11	39x	ping$content <- list(message = rawToChar(ping$content))
12	38x	if (substr(ping$content, 1, 1) == "{") ping$content <- fromJSON(ping$content$message)
13	39x	ok <- ping$status_code == 200 && !length(ping$content$code)
14	39x	ping$status_message <- if (ok) {
15	36x	ping$content$pong
16		} else {
17	3x	paste0(
18	3x	if (length(ping$content$code)) paste0(ping$status_code, " (", ping$content$code, "): "),
19	3x	if (nchar(ping$content$message) > 500 \|\| grepl("<", ping$content$message, fixed = TRUE)) {
20	1x	ping$status_code
21		} else {
22	2x	ping$content$message
23		}
24		)
25		}
26	39x	if (verbose) {
27	3x	message("Status: ", if (ok) "OK" else "ERROR", "\nMessage: ", ping$status_message)
28	3x	if (include_headers) {
29	1x	ping$headers <- strsplit(rawToChar(ping$headers), "[\r\n]+", perl = TRUE)[[1]]
30	1x	json <- regexec("\\{.+\\}", ping$headers)
31	1x	for (i in seq_along(json)) {
32	10x	if (json[[i]] != -1) {
33	2x	regmatches(ping$headers[[i]], json[[i]]) <- paste(" ", strsplit(toJSON(
34	2x	fromJSON(regmatches(ping$headers[[i]], json[[i]])),
35	2x	auto_unbox = TRUE, pretty = TRUE
36	2x	), "\n")[[1]], collapse = "\n")
37		}
38		}
39	1x	message(paste0("\n", paste(" ", ping$headers, collapse = "\n")))
40		}
41		}
42	39x	invisible(ping)
43		}