Call this function inside the commands in your plan to get the environment where drake builds targets. Advanced users can use it to strategically remove targets from memory while make() is running.

drake_envir(which = c("targets", "dynamic", "subtargets", "imports"))

Arguments

which

Character of length 1, which environment to select. See the details of this help file.

Value

The environment where drake builds targets.

Details

drake manages in-memory targets in 4 environments: one with sub-targets, one with whole dynamic targets, one with static targets, and one with imported global objects and functions. This last environment is usually the environment from which you call make(). Select the appropriate environment for your use case with the which argument of drake_envir().

Keywords

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: https://books.ropensci.org/drake/plans.html#large-plans), # nolint supply a trigger (https://books.ropensci.org/drake/triggers.html), # 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.

See also

Examples

if (FALSE) { isolate_example("contain side effects", { plan <- drake_plan( large_data_1 = sample.int(1e4), large_data_2 = sample.int(1e4), subset = c(large_data_1[seq_len(10)], large_data_2[seq_len(10)]), summary = { print(ls(envir = parent.env(drake_envir()))) # We don't need the large_data_* targets in memory anymore. rm(large_data_1, large_data_2, envir = drake_envir("targets")) print(ls(envir = drake_envir("targets"))) mean(subset) } ) make(plan, cache = storr::storr_environment(), session_info = FALSE) }) }