if (FALSE) {
isolate_example("contain side effects", {
# The `file_out()` and `file_in()` functions
# just takes in strings and returns them.
file_out("summaries.txt")
# 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"))
)
plan
# drake knows "\"mtcars.csv\"" is the first target
# and a dependency of `contents`. See for yourself:
make(plan)
file.exists("mtcars.csv")
# 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))
)
)
plan
# 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 = {
dir.create(file_out("dir"))
write.csv(mtcars, "dir/mtcars.csv")
},
contents = read.csv(file.path(file_in("dir"), "mtcars.csv"))
)
plan
make(plan)
file.exists("dir/mtcars.csv")
# See the connections that the file relationships create:
if (requireNamespace("visNetwork", quietly = TRUE)) {
vis_drake_graph(plan)
}
})
}
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