R/read-fwf.R

In sss: Import Files in the Triple-s (Standard Survey Structure) Format

# 
# Author: Andrie
#----------------------------------------------------------------------------------



#' Read fixed-width files quickly.
#'
#' Experimental replacement for [utils::read.fwf] that runs much faster.
#' However, it is much less flexible than `utils::read.fwf`.
#'
#' @param file Character vector: name of file
#' @param widths Numeric vector: column widths. Negative numbers mean "skip this
#'   many columns". Use an NA as the final element if there are likely to be
#'   extra characters at the end of each row after the last one that you're
#'   interested in.
#' @param col.names names for the columns that are NOT skipped
#' @param colClasses can be used to control type conversion; see [read.table()].
#'   It is an optional vector whose names must be part of `col.names`. There is
#'   one extension of the [read.table()] rules: a `colClasses` string starting
#'   `POSIXct` will trigger automatic conversion to POSIXct, using the rest of
#'   the string as the format specifier.
#' @param tz used in auto-conversion to [POSIXct()] when `colClasses` is set
#' @param dec the character to be assumed for decimal points. Passed to
#'   [utils::type.convert()]
#' @param ... ignored
fast.read.fwf <- function (file, widths, col.names = NULL, colClasses = NA,  
                           tz = "", dec = ".", ...){
  
  if(is.null(col.names)) col.names <- paste("V", seq_along(widths), sep = "")
  
  ll <- readLines(file, encoding = "UTF-8")
  nl <- length(ll)
  rw <- lapply(ll, charToRaw)
  
  fields <- vapply(rw, readChar, abs(widths), useBytes = TRUE, 
                   FUN.VALUE = character(length(widths)))
  
  fields <- matrix(fields, nrow = nl, ncol = length(widths), byrow = TRUE)
  
  modColClass <- function(i){
    if (is.na(colClasses[i])) 
      type.convert(fields[, i], as.is = TRUE, dec = dec, 
                   na.strings = character(0L))
    else switch(colClasses[i],
                "factor" = as.factor(fields[, i]),
                "Date" = as.Date(fields[, i], format = "%Y%m%d"),
                "POSIXct" = as.POSIXct(fields[, i]),
                "logical" = as.logical(as.numeric(fields[, i])),
                suppressWarnings(
                  methods::as(fields[, i], colClasses[i])
                )
                
    )
  }
  
  df2 <- lapply(seq_len(ncol(fields)), modColClass)
  df2 <- fastdf(df2)
  names(df2) <- col.names
  df2
}