Expose col_types from readr (#160)

R/CsvHelper.R

@@ -27,13 +27,43 @@
 #' @param file  The .csv file to read.
 #' @param warnOnCaseMismatch  When TRUE, raise a warning if column headings
 #' in the .csv are not in snake_case format
-#'
+#' 
+#' @param colTypes Corresponds to the `col_types` in the `readr::read_csv` function.
+#'   One of `NULL`, a [readr::cols()] specification, or
+#'   a string. See `vignette("readr")` for more details.
+#'
+#'    If `NULL`, all column types will be inferred from `guess_max` rows of the
+#'    input, interspersed throughout the file. This is convenient (and fast),
+#'    but not robust. If the guessed types are wrong, you'll need to increase
+#'    `guess_max` or supply the correct types yourself.
+#'
+#'    Column specifications created by [list()] or [cols()] must contain
+#'    one column specification for each column. 
+#'
+#'    Alternatively, you can use a compact string representation where each
+#'    character represents one column:
+#'    - c = character
+#'    - i = integer
+#'    - n = number
+#'    - d = double
+#'    - l = logical
+#'    - f = factor
+#'    - D = date
+#'    - T = date time
+#'    - t = time
+#'    - ? = guess
+#'    - _ or - = skip
+#'
+#'    By default, reading a file without a column specification will print a
+#'    message showing what `readr` guessed they were. To remove this message,
+#'    set `show_col_types = FALSE` or set `options(readr.show_col_types = FALSE)`.
+#'  
 #' @return
 #' A tibble with the .csv contents
 #'
 #' @export
-readCsv <- function(file, warnOnCaseMismatch = TRUE) {
-  fileContents <- .readCsv(file = file)
+readCsv <- function(file, warnOnCaseMismatch = TRUE, colTypes = readr::cols()) {
+  fileContents <- .readCsv(file = file, colTypes = colTypes)
   columnNames <- colnames(fileContents)
   columnNamesInSnakeCaseFormat <- isSnakeCase(columnNames)
   if (!all(columnNamesInSnakeCaseFormat) && warnOnCaseMismatch) {
@@ -58,10 +88,10 @@ readCsv <- function(file, warnOnCaseMismatch = TRUE) {
 #'
 #' @noRd
 #' @keywords internal
-.readCsv <- function(file) {
+.readCsv <- function(file, colTypes = readr::cols()) {
   invisible(readr::read_csv(
     file = file,
-    col_types = readr::cols(),
+    col_types = colTypes,
     lazy = FALSE
   ))
 }