tar_destroy: Destroy the data store.

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

Destroy the data store.

Description

Destroy the data store written by the pipeline.

Usage

tar_destroy(
  destroy = c("all", "cloud", "local", "meta", "process", "progress", "objects",
    "scratch", "workspaces", "user"),
  ask = NULL,
  store = targets::tar_config_get("store")
)

Arguments

destroy	Character of length 1, what to destroy. Choices: "all": destroy the entire data store (default: _targets/) including cloud data. "cloud": just try to delete cloud data, e.g. target data from targets with tar_target(..., repository = "aws"). "local": all the local files in the data store but nothing on the cloud. "meta": just delete the metadata file at meta/meta in the data store, which invalidates all the targets but keeps the data. "process": just delete the progress data file at meta/process in the data store, which resets the metadata of the main process. "progress": just delete the progress data file at meta/progress in the data store, which resets the progress tracking info. "objects": delete all the target return values in objects/ in the data store but keep progress and metadata. Dynamic files are not deleted this way. "scratch": temporary files saved during tar_make() that should automatically get deleted except if R crashed. "workspaces": compressed lightweight files in workspaces/ in the data store with the saved workspaces of targets. See tar_workspace() for details. "user": custom user-supplied files in the user/ folder in the data store.
ask	Logical of length 1, whether to pause with a menu prompt before deleting files. To disable this menu, set the TAR_ASK environment variable to "false". usethis::edit_r_environ() can help set environment variables.
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

The data store is a folder created by tar_make() (or tar_make_future() or tar_make_clustermq()). The details of the data store are explained at https://books.ropensci.org/targets/data.html#local-data-store. The data store folder contains the output data and metadata of the targets in the pipeline. Usually, the data store is a folder called _targets/ (see tar_config_set() to customize), and it may link to data on the cloud if you used AWS or GCP buckets. By default, tar_destroy() deletes the entire _targets/ folder (or wherever the data store is located), including custom user-supplied files in _targets/user/, as well as any cloud data that the pipeline uploaded. See the destroy argument to customize this behavior and only delete part of the data store, and see functions like tar_invalidate(), tar_delete(), and tar_prune() to remove information pertaining to some but not all targets in the pipeline. After calling tar_destroy() with default arguments, the entire data store is gone, which means all the output data from previous runs of the pipeline is gone (except for input/output files tracked with tar_target(..., format = "file")). The next run of the pipeline will start from scratch, and it will not skip any targets.

Value

NULL (invisibly).

See Also

Other clean: tar_delete(), tar_invalidate(), tar_prune()

Examples

if (identical(Sys.getenv("TAR_EXAMPLES"), "true")) {
tar_dir({ # tar_dir() runs code from a temporary directory.
tar_script(list(tar_target(x, 1 + 1)), ask = FALSE)
tar_make() # Creates the _targets/ data store.
tar_destroy()
print(file.exists("_targets")) # Should be FALSE.
})
}

targets documentation built on Jan. 6, 2023, 5:16 p.m.