REDCapCAST/R/shiny_cast.R

78 lines
1.9 KiB
R

#' Launch the included Shiny-app for database casting and upload
#'
#' @description
#' Wraps shiny::runApp()
#'
#' @param ... Arguments passed to shiny::runApp()
#'
#' @return shiny app
#' @export
#'
#' @examples
#' # shiny_cast()
#'
shiny_cast <- function(...) {
appDir <- system.file("shiny-examples", "casting", package = "REDCapCAST")
if (appDir == "") {
stop("Could not find example directory. Try re-installing `REDCapCAST`.", call. = FALSE)
}
shiny::runApp(appDir = appDir, ...)
}
#' DEPRECATED Helper to import files correctly
#'
#' @param filenames file names
#'
#' @return character vector
#' @export
#'
#' @examples
#' file_extension(list.files(here::here(""))[[2]])[[1]]
#' file_extension(c("file.cd..ks","file"))
file_extension <- function(filenames) {
sub(pattern = "^(.*\\.|[^.]+)(?=[^.]*)", replacement = "",
filenames,
perl = TRUE)
}
#' Flexible file import based on extension
#'
#' @param file file name
#' @param consider.na character vector of strings to consider as NAs
#'
#' @return tibble
#' @export
#'
#' @examples
#' read_input("https://raw.githubusercontent.com/agdamsbo/cognitive.index.lookup/main/data/sample.csv")
read_input <- function(file, consider.na = c("NA", '""', "")) {
ext <- tools::file_ext(file)
tryCatch(
{
if (ext == "csv") {
df <- readr::read_csv(file = file, na = consider.na)
} else if (ext %in% c("xls", "xlsx")) {
df <- openxlsx2::read_xlsx(file = file, na.strings = consider.na)
} else if (ext == "dta") {
df <- haven::read_dta(file = file)
} else if (ext == "ods") {
df <- readODS::read_ods(file = file)
} else {
stop("Input file format has to be on of:
'.csv', '.xls', '.xlsx', '.dta' or '.ods'")
}
},
error = function(e) {
# return a safeError if a parsing error occurs
stop(shiny::safeError(e))
}
)
df
}