simply_read_csv: Read a CSV as All Text
In meerapatelmd/broca: Helpers for Reading and Writing Data

Read a CSV with all columns defaulted to "character" data types to prevent parsing failures by read_csv.

simply_read_csv(
  file,
  col_names = TRUE,
  col_types = readr::cols(.default = "c"),
  locale = readr::default_locale(),
  na = "NA",
  quoted_na = TRUE,
  quote = "\"",
  comment = "",
  trim_ws = TRUE,
  skip = 0,
  n_max = Inf,
  guess_max = min(1000, n_max),
  progress = show_progress(),
  skip_empty_rows = TRUE,
  log = "DEPRECATED",
  log_details = ""
)

`file`	Either a path to a file, a connection, or literal data (either a single string or a raw vector). Files ending in `.gz`, `.bz2`, `.xz`, or `.zip` will be automatically uncompressed. Files starting with `http://`, `https://`, `ftp://`, or `ftps://` will be automatically downloaded. Remote gz files can also be automatically downloaded and decompressed. Literal data is most useful for examples and tests. To be recognised as a path, it must be wrapped with `I()`, be a string containing at least one new line, or be a vector containing at least one string with a new line. Using a value of `clipboard()` will read from the system clipboard.
`col_names`	Either `TRUE`, `FALSE` or a character vector of column names. If `TRUE`, the first row of the input will be used as the column names, and will not be included in the data frame. If `FALSE`, column names will be generated automatically: X1, X2, X3 etc. If `col_names` is a character vector, the values will be used as the names of the columns, and the first row of the input will be read into the first row of the output data frame. Missing (`NA`) column names will generate a warning, and be filled in with dummy names `X1`, `X2` etc. Duplicate column names will generate a warning and be made unique, see `name_repair` to control how this is done.
`col_types`	One of `NULL`, a `cols()` specification, or a string. See `vignette("readr")` for more details. If `NULL`, all column types will be imputed from the first 1000 rows on the input. This is convenient (and fast), but not robust. If the imputation fails, you'll need to increase the `guess_max` or supply the correct types yourself. Column specifications created by `list()` or `cols()` must contain one column specification for each column. If you only want to read a subset of the columns, use `cols_only()`. 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).
`locale`	The locale controls defaults that vary from place to place. The default locale is US-centric (like R), but you can use `locale()` to create your own locale that controls things like the default time zone, encoding, decimal mark, big mark, and day/month names.
`na`	Character vector of strings to interpret as missing values. Set this option to `character()` to indicate no missing values.
`quoted_na`	Should missing values inside quotes be treated as missing values (the default) or strings.
`quote`	Single character used to quote strings.
`comment`	A string used to identify comments. Any text after the comment characters will be silently ignored.
`trim_ws`	Should leading and trailing whitespace (ASCII spaces and tabs) be trimmed from each field before parsing it?
`skip`	Number of lines to skip before reading data. If `comment` is supplied any commented lines are ignored after skipping.
`n_max`	Maximum number of lines to read.
`guess_max`	Maximum number of lines to use for guessing column types.
`progress`	Display a progress bar? By default it will only display in an interactive session and not while knitting a document. The automatic progress bar can be disabled by setting option `readr.show_progress` to `FALSE`.
`skip_empty_rows`	Should blank rows be ignored altogether? i.e. If this option is `TRUE` then blank rows will not be represented at all. If it is `FALSE` then they will be represented by `NA` values in all the columns.