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#' Prepare access
#'
#' Extract `fileNames` from data file(s) and add them to `access.csv`. The
#' helper \code{\link{validate_file_paths}} can be used to create vectors of
#' valid file paths that can be checked and then passed as `data_path` argument
#' to \code{\link{prep_access}}.
#' @param data_path character vector of either:
#'
#' 1. path(s) to the data file(s).
#' 2. single path to directory containing data file(s).
#' Currently only tabular `.csv` and `.tsv` or `.rds` files are supported.
#' @param access_path path to the `access.csv` file. Defaults to
#' `data/metadata/access.csv`.
#' @param ... parameters passed to `list.files()`. For example, use
#' `recursive = TRUE` to list files in a folder recursively or use `pattern` to
#' filter files for patterns.
#' @return Updates `access.csv` and writes to `access_path`.
#' @export
#' @examples
#' \dontrun{
#' # First create the metadata tempaltes
#' create_spice()
#'
#' # Then begin filling them in from your data files
#' prep_access()
#' }
prep_access <- function(data_path = "data",
access_path = "data/metadata/access.csv",
...) {
# check and load attributes
if(!file.exists(access_path)) {
stop("access file does not exist. Check path or run create_spice?")}
access <- readr::read_csv(access_path, col_types = readr::cols())
# list and validate file paths
file_paths <- validate_file_paths(data_path, ...)
fileNames <- basename(file_paths) %>%
check_fileNames(table = access)
if(length(fileNames) == 0) {
return()
}
fileTypes <- tools::file_ext(fileNames)
access <- tibble::add_row(access,
fileName = fileNames,
name = basename(
tools::file_path_sans_ext(fileNames)
),
contentUrl = NA,
encodingFormat = fileTypes)
readr::write_csv(access, access_path)
message("The following fileNames have been added to the access file: ",
paste(basename(fileNames), collapse = ", "))
}
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