tar_load: Load the values of targets.
In targets: Dynamic Function-Oriented 'Make'-Like Declarative Pipelines

tar_load

R Documentation

Load the values of targets.

Description

Load the return values of targets into the current environment (or the environment of your choosing). For a typical target, the return value lives in a file in ⁠_targets/objects/⁠. For dynamic files (i.e. format = "file") the paths loaded in place of the values. tar_load_everything() is shorthand for tar_load(everything()) to load all targets.

tar_load() uses non-standard evaluation in the names argument (example: tar_load(names = everything())), whereas tar_load_raw() uses standard evaluation for names (example: tar_load_raw(names = quote(everything()))).

Usage

tar_load(
  names,
  branches = NULL,
  meta = targets::tar_meta(targets_only = TRUE, store = store),
  strict = TRUE,
  silent = FALSE,
  envir = parent.frame(),
  store = targets::tar_config_get("store")
)

tar_load_raw(
  names,
  branches = NULL,
  meta = tar_meta(store = store),
  strict = TRUE,
  silent = FALSE,
  envir = parent.frame(),
  store = targets::tar_config_get("store")
)

Arguments

`names`	Names of the targets to load. `tar_load()` uses non-standard evaluation in the `names` argument (example: `tar_load(names = everything())`), whereas `tar_load_raw()` uses standard evaluation for `names` (example: `tar_load_raw(names = quote(everything()))`). 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.
`branches`	Integer of indices of the branches to load for any targets that are patterns.
`meta`	Data frame of target metadata from `tar_meta()`.
`strict`	Logical of length 1, whether to error out if one of the selected targets is in the metadata but cannot be loaded. Set to `FALSE` to just load the targets in the metadata that can be loaded and skip the others.
`silent`	Logical of length 1. Only relevant when `strict` is `FALSE`. If `silent` is `FALSE` and `strict` is `FALSE`, then a message will be printed if a target is in the metadata but cannot be loaded. However, load failures will not stop other targets from being loaded.
`envir`	R environment in which to load target return values.
`store`	Character of length 1, directory path to the data store of the pipeline.

Value

Nothing.

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().

Cloud target data versioning

Some buckets in Amazon S3 or Google Cloud Storage are "versioned", which means they track historical versions of each data object. If you use targets with cloud storage (https://books.ropensci.org/targets/cloud-storage.html) and versioning is turned on, then targets will record each version of each target in its metadata.

Functions like tar_read() and tar_load() load the version recorded in the local metadata, which may not be the same as the "current" version of the object in the bucket. Likewise, functions tar_delete() and tar_destroy() only remove the version ID of each target as recorded in the local metadata.

If you want to interact with the latest version of an object instead of the version ID recorded in the local metadata, then you will need to delete the object from the metadata.

Make sure your local copy of the metadata is current and up to date. You may need to run tar_meta_download() or tar_meta_sync() first.
Run tar_unversion() to remove the recorded version IDs of your targets in the local metadata.
With the version IDs gone from the local metadata, functions like tar_read() and tar_destroy() will use the latest version of each target data object.
Optional: to back up the local metadata file with the version IDs deleted, use tar_meta_upload().

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()
ls() # Does not have "y1", "y2", or "z".
tar_load(starts_with("y"))
ls() # Has "y1" and "y2" but not "z".
tar_load_raw(quote(any_of("z")))
ls() # Has "y1", "y2", and "z".
})
}

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