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parse.R provides two lightweight utilities for getting raw data into the pipeline. lsData() discovers CSV files in the raw data directory and returns a named list of paths, while readData() loads a single file into a tidy data frame. Together they feed the first two targets in _targets.R.

​
lsData()

lsData <- function(path = "data/raw", ...) {
  #' List Data
  #'
  #' List all data file within `path` directory
  #'
  #' @param path A path of raw data directory, set to "data/raw" by default
  #' @return A list of complete relative path of each dataset

  filepath <- list.files(path, full.name = TRUE, recursive = TRUE, ...) %>%
    set_names(gsub(x = ., ".*_|\\w+/|\\.\\w*", ""))

  return(filepath)
}

​
Parameters

​
path
character
default:"\"data/raw\""
Path to the raw data directory. Passed directly to list.files() as the first argument.
​
...
any
Additional arguments passed to list.files(). Use pattern to filter files by extension or name.

​
Returns

A named character vector of full relative file paths. Names are derived from each filename by stripping the leading directory path and file extension using gsub(x = ., ".*_|\\w+/|\\.\\w*", ""). For example, a file at data/raw/data.csv gets the name "data".

​
Usage

raws <- lsData(pattern = "*csv")
# Returns named list: list("data" = "data/raw/data.csv")
In _targets.R: 
raws <- lsData(pattern = "*csv")
lsData() is called at the top level of _targets.R — outside the list() of targets — so the file paths are resolved at pipeline definition time.

​
readData()

readData <- function(fpath, ...) {
  #' Read Data Frame
  #'
  #' Read external tabular data as a tidy data frame
  #'
  #' @param fpath Path name of the file to parse
  #' @inheritDotParams readr::read_csv
  #' @return A tidy data frame

  tbl <- readr::read_csv(fpath, ...)

  return(tbl)
}

​
Parameters

​
fpath
character
required
Full path to the CSV file to read. Typically one of the values from lsData().
​
...
any
Additional arguments passed to readr::read_csv(). Use these to control column type guessing, locale, encoding, or to skip rows.

​
Returns

A tibble (tidy data frame) with columns inferred from the CSV header row. Column types are guessed by readr using the first 1000 rows by default.

​
Usage

tbl <- readData("data/raw/data.csv")
In _targets.R: 
tar_target(tbl, readData(fpath))
fpath is defined in the preceding tar_target(fpath, raws[["data"]], format = "file") target, which tells targets to track the file for changes.
readData() delegates entirely to readr::read_csv(), which handles a variety of CSV encodings and performs automatic type inference. If a column is being read as the wrong type, pass explicit col_types via ....

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