tar_workspace: Load a saved workspace and seed for debugging.

In targets: Dynamic Function-Oriented 'Make'-Like Declarative Pipelines

Load a saved workspace and seed for debugging.

Description

Load the packages, environment, and random number generator seed of a target.

Usage

tar_workspace(
  name,
  envir = parent.frame(),
  packages = TRUE,
  source = TRUE,
  script = targets::tar_config_get("script"),
  store = targets::tar_config_get("store")
)

Arguments

name	Symbol, name of the target whose workspace to read.
envir	Environment in which to put the objects.
packages	Logical, whether to load the required packages of the target.
source	Logical, whether to run ⁠_targets.R⁠ to load user-defined global object dependencies into envir. If TRUE, then envir should either be the global environment or inherit from the global environment.
script	Character of length 1, path to the target script file. Defaults to tar_config_get("script"), which in turn defaults to ⁠_targets.R⁠. When you set this argument, the value of tar_config_get("script") is temporarily changed for the current function call. See tar_script(), tar_config_get(), and tar_config_set() for details about the target script file and how to set it persistently for a project.
store	Character of length 1, path to the targets data store. Defaults to tar_config_get("store"), which in turn defaults to ⁠_targets/⁠. When you set this argument, the value of tar_config_get("store") is temporarily changed for the current function call. See tar_config_get() and tar_config_set() for details about how to set the data store path persistently for a project.

Details

If you activate workspaces through the workspaces argument of tar_option_set(), then under the circumstances you specify, targets will save a special workspace file to a location in in ⁠_targets/workspaces/⁠. The workspace file is a compact reference that allows tar_workspace() to load the target's dependencies and random number generator seed as long as the data objects are still in the data store (usually files in ⁠_targets/objects/⁠). When you are done debugging, you can remove the workspace files using tar_destroy(destroy = "workspaces").

Value

This function returns NULL, but it does load the target's required packages, as well as multiple objects into the environment (envir argument) in order to replicate the workspace where the error happened. These objects include the global objects at the time tar_make() was called and the dependency targets. The random number generator seed for the target is also assigned with tar_seed_set().

See Also

Other debug: tar_load_globals(), tar_traceback(), tar_workspaces()

Examples

if (identical(Sys.getenv("TAR_EXAMPLES"), "true")) { # for CRAN
tar_dir({ # tar_dir() runs code from a temp dir for CRAN.
tmp <- sample(1)
tar_script({
  library(targets)
  library(tarchetypes)
  tar_option_set(workspace_on_error = TRUE)
  list(
    tar_target(x, "loaded"),
    tar_target(y, stop(x))
  )
}, ask = FALSE)
# The following code throws an error for demonstration purposes.
try(tar_make())
exists("x") # Should be FALSE.
tail(.Random.seed) # for comparison to the RNG state after tar_workspace(y)
tar_workspace(y)
exists("x") # Should be TRUE.
print(x) # "loaded"
# Should be different: tar_workspace() runs
# tar_seed_set(tar_meta(y, seed)$seed)
tail(.Random.seed)
})
}

targets documentation built on Oct. 3, 2024, 1:11 a.m.