tar_read: Read a target's value from storage.
In targets: Dynamic Function-Oriented 'Make'-Like Declarative Pipelines

tar_read

R Documentation

Read a target's value from storage.

Description

Read a target's return value from its file in ⁠_targets/objects/⁠. For file targets (i.e. format = "file") the paths are returned.

tar_read() expects an unevaluated symbol for the name argument, whereas tar_read_raw() expects a character string.

Usage

tar_read(
  name,
  branches = NULL,
  meta = tar_meta(store = store),
  store = targets::tar_config_get("store")
)

tar_read_raw(
  name,
  branches = NULL,
  meta = tar_meta(store = store),
  store = targets::tar_config_get("store")
)

Arguments

`name`	Name of the target to read. `tar_read()` expects an unevaluated symbol for the `name` argument, whereas `tar_read_raw()` expects a character string.
`branches`	Integer of indices of the branches to load if the target is a pattern.
`meta`	Data frame of metadata from `tar_meta()`. `tar_read()` with the default arguments can be inefficient for large pipelines because all the metadata is stored in a single file. However, if you call `tar_meta()` beforehand and supply it to the `meta` argument, then successive calls to `tar_read()` may run much faster.
`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

The target's return value from its file in ⁠_targets/objects/⁠, or the paths to the custom files and directories if format = "file" was set.

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().

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().

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(x, 1 + 1))
})
tar_make()
tar_read(x)
tar_read_raw("x")
})
}

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