Skip to contents

Delete the metadata of records in _targets/meta/meta but keep the return values of targets in _targets/objects/.

Usage

tar_invalidate(names, store = targets::tar_config_get("store"))

Arguments

names

Names of the targets to remove from the metadata list. The object supplied to names should be a tidyselect expression like any_of() or starts_with() from tidyselect itself, or tar_described_as() to select target names based on their descriptions.

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.

Value

NULL (invisibly).

Details

This function forces one or more targets to rerun on the next tar_make(), regardless of the cues and regardless of how those targets are stored. After tar_invalidate(), you will still be able to locate the data files with tar_path_target() and manually salvage them in an emergency. However, tar_load() and tar_read() will not be able to read the data into R, and subsequent calls to tar_make() will attempt to rerun those targets. For patterns recorded in the metadata, all the branches will be invalidated. For patterns no longer in the metadata, branches are left alone.

Storage access

Several functions like tar_make(), tar_read(), tar_load(), tar_meta(), and tar_progress() read or modify the local data store of the pipeline. The local data store is in flux while a pipeline is running, and depending on how distributed computing or cloud computing is set up, not all targets can even reach it. So please do not call these functions from inside a target as part of a running pipeline. The only exception is literate programming target factories in the tarchetypes package such as tar_render() and tar_quarto().

See also

Examples

if (identical(Sys.getenv("TAR_EXAMPLES"), "true")) { # for CRAN
tar_dir({ # tar_dir() runs code from a temp dir for CRAN.
tar_script({
  library(targets)
  library(tarchetypes)
  list(
    tar_target(y1, 1 + 1),
    tar_target(y2, 1 + 1),
    tar_target(z, y1 + y2)
  )
}, ask = FALSE)
tar_make()
tar_invalidate(starts_with("y")) # Only invalidates y1 and y2.
tar_make() # y1 and y2 rerun but return same values, so z is up to date.
})
}