stRoke/R/read_redcap_tables.R

#' Download REDCap data
#' 
#' Wrapper function for using REDCapR::redcap_read and REDCapRITS::REDCap_split 
#' including some clean-up. Works with longitudinal projects with repeating 
#' instruments.
#' @param uri REDCap database uri
#' @param token API token
#' @param records records to download
#' @param fields fields to download
#' @param events events to download
#' @param forms forms to download
#' @param generics vector of auto-generated generic variable names to 
#' ignore when discarding empty rows
#'
#' @return list of instruments
#' @export 
#'
#' @examples
#' # Examples will be provided later
read_redcap_tables <- function(uri,
                               token,
                               records = NULL,
                               fields = NULL,
                               events = NULL,
                               forms = NULL,
                               generics = c(
                                 "record_id",
                                 "redcap_event_name",
                                 "redcap_repeat_instrument",
                                 "redcap_repeat_instance"
                               )) {
  # Notes to self: Based on the metadata, this functionality could be 
  # introduced without using the REDCapRITS package.. To be tried..
  
  d <- REDCapR::redcap_read (
    redcap_uri = uri,
    token = token,
    fields = fields,
    events = events,
    forms = forms,
    records = records
  )
  
  m <-
    REDCapR::redcap_metadata_read (redcap_uri = uri, token = token)
  
  if (requireNamespace("REDCapRITS", quietly = TRUE)) {
    l <- REDCapRITS::REDCap_split(d$data,
                                  m$data[m$data$field_name %in% names(d$data),],
                                  forms = "all")
  } else {
    cli::cli_abort(
      c(
        "x" = "The package REDCapRITS is not installed.",
        "i" = "Please install REDCapRITS by running
        \"remotes::install_github('agdamsbo/REDCapRITS')\"."
      )
    )
  }
  
  lapply(l, function(i) {
    if (ncol(i) > 2) {
      s <- data.frame(i[, !colnames(i) %in% generics])
      i[!apply(is.na(s), MARGIN = 1, FUN = all),]
    } else {
      i
    }
  })
  
}