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file_out() marks individual files (and whole directories) that your targets create.





Character vector, paths to files and directories. Use .id_chr to refer to the current target by name. .id_chr is not limited to use in file_in() and file_out().


A character vector of declared output file or directory paths.


drake_plan() understands special keyword functions for your commands. With the exception of target(), each one is a proper function with its own help file.

  • target(): give the target more than just a command. Using target(), you can apply a transformation (examples:, # nolint supply a trigger (, # nolint or set any number of custom columns.

  • file_in(): declare an input file dependency.

  • file_out(): declare an output file to be produced when the target is built.

  • knitr_in(): declare a knitr file dependency such as an R Markdown (*.Rmd) or R LaTeX (*.Rnw) file.

  • ignore(): force drake to entirely ignore a piece of code: do not track it for changes and do not analyze it for dependencies.

  • no_deps(): tell drake to not track the dependencies of a piece of code. drake still tracks the code itself for changes.

  • id_chr(): Get the name of the current target.

  • drake_envir(): get the environment where drake builds targets. Intended for advanced custom memory management.


if (FALSE) {
isolate_example("contain side effects", {
# The `file_out()` and `file_in()` functions
# just takes in strings and returns them.
# Their main purpose is to orchestrate your custom files
# in your workflow plan data frame.
plan <- drake_plan(
  out = write.csv(mtcars, file_out("mtcars.csv")),
  contents = read.csv(file_in("mtcars.csv"))
# drake knows "\"mtcars.csv\"" is the first target
# and a dependency of `contents`. See for yourself:


 # You may use `.id_chr` inside `file_out()` and `file_in()`
 # to refer  to the current target. This works inside `map()`,
 # `combine()`, `split()`, and `cross()`.

plan <- drake::drake_plan(
  data = target(
    write.csv(data, file_out(paste0(.id_chr, ".csv"))),
    transform = map(data = c(airquality, mtcars))


# You can also work with entire directories this way.
# However, in `file_out("your_directory")`, the directory
# becomes an entire unit. Thus, `file_in("your_directory")`
# is more appropriate for subsequent steps than
# `file_in("your_directory/file_inside.txt")`.
plan <- drake_plan(
  out = {
    write.csv(mtcars, "dir/mtcars.csv")
  contents = read.csv(file.path(file_in("dir"), "mtcars.csv"))


# See the connections that the file relationships create:
if (requireNamespace("visNetwork", quietly = TRUE)) {