Turn a script into a function.

code_to_function() is a quick (and very dirty) way to retrofit drake to an existing script-based project. It parses individual \*.R/\*.RMD files into functions so they can be added into the drake workflow.

Usage

code_to_function(path, envir = parent.frame())

Arguments

path

Character vector, path to script.

envir

Environment of the created function.

Value

A function to be input into the drake plan

Details

Most data science workflows consist of imperative scripts. drake, on the other hand, assumes you write functions. code_to_function() allows for pre-existing workflows to incorporate drake as a workflow management tool seamlessly for cases where re-factoring is unfeasible. So drake can monitor dependencies, the targets are passed as arguments of the dependent functions.

See also

file_in(), file_out(), knitr_in(), ignore(), no_deps(), code_to_plan(), plan_to_code(), plan_to_notebook()

Examples

if (FALSE) { # \dontrun{
isolate_example("contain side effects", {
if (requireNamespace("ggplot2", quietly = TRUE)) {
# The `code_to_function()` function creates a function that makes it
# available for drake to process as part of the workflow.
# The main purpose is to allow pre-existing workflows to incorporate drake
# into the workflow seamlessly for cases where re-factoring is unfeasible.
#

script1 <- tempfile()
script2 <- tempfile()
script3 <- tempfile()
script4 <- tempfile()

writeLines(c(
  "data <- mtcars",
  "data$make <- do.call('c',",
  "lapply(strsplit(rownames(data), split=\" \"), `[`, 1))",
  "saveRDS(data, \"mtcars_alt.RDS\")"
 ),
  script1
)

writeLines(c(
  "data <- readRDS(\"mtcars_alt.RDS\")",
  "mtcars_lm <- lm(mpg~cyl+disp+vs+gear+make,data=data)",
  "saveRDS(mtcars_lm, \"mtcars_lm.RDS\")"
  ),
  script2
)
writeLines(c(
  "mtcars_lm <- readRDS(\"mtcars_lm.RDS\")",
  "lm_summary <- summary(mtcars_lm)",
  "saveRDS(lm_summary, \"mtcars_lm_summary.RDS\")"
  ),
  script3
)
writeLines(c(
  "data<-readRDS(\"mtcars_alt.RDS\")",
  "gg <- ggplot2::ggplot(data)+",
  "ggplot2::geom_point(ggplot2::aes(",
  "x=disp, y=mpg, shape=as.factor(vs), color=make))",
  "ggplot2::ggsave(\"mtcars_plot.png\", gg)"
 ),
  script4
)


do_munge <- code_to_function(script1)
do_analysis <- code_to_function(script2)
do_summarize <- code_to_function(script3)
do_vis <- code_to_function(script4)

plan <- drake_plan(
  munged   = do_munge(),
  analysis = do_analysis(munged),
  summary  = do_summarize(analysis),
  plot     = do_vis(munged)
 )

plan
# drake knows  "script1" is the first script to be evaluated and ran,
# because it has no dependencies on other code and a dependency of
# `analysis`. See for yourself:

make(plan)

# See the connections that the sourced scripts create:
if (requireNamespace("visNetwork", quietly = TRUE)) {
  vis_drake_graph(plan)
}
}
})
} # }