Define a target using unrefined names and language objects.
Source:R/tar_target_raw.R
tar_target_raw.Rd
tar_target_raw()
is just like tar_target()
except
it avoids non-standard evaluation for the arguments: name
is a character string, command
and pattern
are language objects,
and there is no tidy_eval
argument. Use tar_target_raw()
instead of tar_target()
if you are creating entire batches
of targets programmatically (metaprogramming, static branching).
Usage
tar_target_raw(
name,
command,
pattern = NULL,
packages = targets::tar_option_get("packages"),
library = targets::tar_option_get("library"),
deps = NULL,
string = NULL,
format = targets::tar_option_get("format"),
repository = targets::tar_option_get("repository"),
iteration = targets::tar_option_get("iteration"),
error = targets::tar_option_get("error"),
memory = targets::tar_option_get("memory"),
garbage_collection = targets::tar_option_get("garbage_collection"),
deployment = targets::tar_option_get("deployment"),
priority = targets::tar_option_get("priority"),
resources = targets::tar_option_get("resources"),
storage = targets::tar_option_get("storage"),
retrieval = targets::tar_option_get("retrieval"),
cue = targets::tar_option_get("cue")
)
Arguments
- name
Character of length 1, name of the target. A target name must be a valid name for a symbol in R, and it must not start with a dot. Subsequent targets can refer to this name symbolically to induce a dependency relationship: e.g.
tar_target(downstream_target, f(upstream_target))
is a target nameddownstream_target
which depends on a targetupstream_target
and a functionf()
. In addition, a target's name determines its random number generator seed. In this way, each target runs with a reproducible seed so someone else running the same pipeline should get the same results, and no two targets in the same pipeline share the same seed. (Even dynamic branches have different names and thus different seeds.) You can recover the seed of a completed target withtar_meta(your_target, seed)
and runset.seed()
on the result to locally recreate the target's initial RNG state.- command
Similar to the
command
argument oftar_target()
except the object must already be an expression instead of informally quoted code.base::expression()
andbase::quote()
can produce such objects.- pattern
Similar to the
pattern
argument oftar_target()
except the object must already be an expression instead of informally quoted code.base::expression()
andbase::quote()
can produce such objects.- packages
Character vector of packages to load right before the target builds or the output data is reloaded for downstream targets. Use
tar_option_set()
to set packages globally for all subsequent targets you define.- library
Character vector of library paths to try when loading
packages
.- deps
Optional character vector of the adjacent upstream dependencies of the target, including targets and global objects. If
NULL
, dependencies are resolved automatically as usual. Thedeps
argument is only for developers of extension packages such astarchetypes
, not for end users, and it should almost never be used at all. In scenarios that at first appear to requiresdeps
, there is almost always a simpler and more robust workaround that avoids settingdeps
.- string
Optional string representation of the command. Internally, the string gets hashed to check if the command changed since last run, which helps
targets
decide whether the target is up to date. External interfaces can take control ofstring
to ignore changes in certain parts of the command. IfNULL
, the strings is just deparsed fromcommand
(default).- format
Optional storage format for the target's return value. With the exception of
format = "file"
, each target gets a file in_targets/objects
, and each format is a different way to save and load this file. See the "Storage formats" section for a detailed list of possible data storage formats.- repository
Character of length 1, remote repository for target storage. Choices:
"local"
: file system of the local machine."aws"
: Amazon Web Services (AWS) S3 bucket. Can be configured with a non-AWS S3 bucket using theendpoint
argument oftar_resources_aws()
, but versioning capabilities may be lost in doing so. See the cloud storage section of https://books.ropensci.org/targets/data.html for details for instructions."gcp"
: Google Cloud Platform storage bucket. See the cloud storage section of https://books.ropensci.org/targets/data.html for details for instructions.
Note: if
repository
is not"local"
andformat
is"file"
then the target should create a single output file. That output file is uploaded to the cloud and tracked for changes where it exists in the cloud. The local file is deleted after the target runs.- iteration
Character of length 1, name of the iteration mode of the target. Choices:
"vector"
: branching happens withvctrs::vec_slice()
and aggregation happens withvctrs::vec_c()
."list"
, branching happens with[[]]
and aggregation happens withlist()
."group"
:dplyr::group_by()
-like functionality to branch over subsets of a data frame. The target's return value must be a data frame with a specialtar_group
column of consecutive integers from 1 through the number of groups. Each integer designates a group, and a branch is created for each collection of rows in a group. See thetar_group()
function to see how you can create the specialtar_group
column withdplyr::group_by()
.
- error
Character of length 1, what to do if the target stops and throws an error. Options:
"stop"
: the whole pipeline stops and throws an error."continue"
: the whole pipeline keeps going."abridge"
: any currently running targets keep running, but no new targets launch after that. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)"null"
: The errored target continues and returnsNULL
. The data hash is deliberately wrong so the target is not up to date for the next run of the pipeline.
- memory
Character of length 1, memory strategy. If
"persistent"
, the target stays in memory until the end of the pipeline (unlessstorage
is"worker"
, in which casetargets
unloads the value from memory right after storing it in order to avoid sending copious data over a network). If"transient"
, the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files (e.g.format = "file"
withrepository = "aws"
), this memory strategy applies to the temporary local copy of the file:"persistent"
means it remains until the end of the pipeline and is then deleted, and"transient"
means it gets deleted as soon as possible. The former conserves bandwidth, and the latter conserves local storage.- garbage_collection
Logical, whether to run
base::gc()
just before the target runs.- deployment
Character of length 1, only relevant to
tar_make_clustermq()
andtar_make_future()
. If"worker"
, the target builds on a parallel worker. If"main"
, the target builds on the host machine / process managing the pipeline.- priority
Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get built earlier (and polled earlier in
tar_make_future()
).- resources
Object returned by
tar_resources()
with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities oftargets
. Seetar_resources()
for details.- storage
Character of length 1, only relevant to
tar_make_clustermq()
andtar_make_future()
. Must be one of the following values:"main"
: the target's return value is sent back to the host machine and saved/uploaded locally."worker"
: the worker saves/uploads the value."none"
: almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except whenretrieval = "none"
).If you select
storage = "none"
, then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file"
) it is the responsibility of the user to write to the data store from inside the target.The distinguishing feature of
storage = "none"
(as opposed toformat = "file"
) is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary,storage = "none"
is completely unnecessary ifformat
is"file"
.
- retrieval
Character of length 1, only relevant to
tar_make_clustermq()
andtar_make_future()
. Must be one of the following values:"main"
: the target's dependencies are loaded on the host machine and sent to the worker before the target builds."worker"
: the worker loads the targets dependencies."none"
: the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.
- cue
An optional object from
tar_cue()
to customize the rules that decide whether the target is up to date.
Value
A target object. Users should not modify these directly,
just feed them to list()
in your target script file
(default: _targets.R
).
See the "Target objects" section for details.
Target objects
Functions like tar_target()
produce target objects,
special objects with specialized sets of S3 classes.
Target objects represent skippable steps of the analysis pipeline
as described at https://books.ropensci.org/targets/.
Please read the walkthrough at
https://books.ropensci.org/targets/walkthrough.html
to understand the role of target objects in analysis pipelines.
For developers, https://wlandau.github.io/targetopia/contributing.html#target-factories explains target factories (functions like this one which generate targets) and the design specification at https://books.ropensci.org/targets-design/ details the structure and composition of target objects.
See also
Other targets:
tar_cue()
,
tar_format()
,
tar_target()
Examples
# The following are equivalent.
y <- tar_target(y, sqrt(x), pattern = map(x))
y <- tar_target_raw("y", expression(sqrt(x)), expression(map(x)))
# Programmatically create a chain of interdependent targets
target_list <- lapply(seq_len(4), function(i) {
tar_target_raw(
letters[i + 1],
substitute(do_something(x), env = list(x = as.symbol(letters[i])))
)
})
print(target_list[[1]])
#> <tar_stem>
#> name: b
#> command:
#> do_something(a)
#> format: rds
#> repository: local
#> iteration method: vector
#> error mode: stop
#> memory mode: persistent
#> storage mode: main
#> retrieval mode: main
#> deployment mode: worker
#> priority: 0
#> resources:
#> list()
#> cue:
#> mode: thorough
#> command: TRUE
#> depend: TRUE
#> format: TRUE
#> repository: TRUE
#> iteration: TRUE
#> file: TRUE
#> seed: TRUE
#> packages:
#> targets
#> stats
#> graphics
#> grDevices
#> utils
#> datasets
#> methods
#> base
#> library:
#> NULL
print(target_list[[2]])
#> <tar_stem>
#> name: c
#> command:
#> do_something(b)
#> format: rds
#> repository: local
#> iteration method: vector
#> error mode: stop
#> memory mode: persistent
#> storage mode: main
#> retrieval mode: main
#> deployment mode: worker
#> priority: 0
#> resources:
#> list()
#> cue:
#> mode: thorough
#> command: TRUE
#> depend: TRUE
#> format: TRUE
#> repository: TRUE
#> iteration: TRUE
#> file: TRUE
#> seed: TRUE
#> packages:
#> targets
#> stats
#> graphics
#> grDevices
#> utils
#> datasets
#> methods
#> base
#> library:
#> NULL
if (identical(Sys.getenv("TAR_EXAMPLES"), "true")) { # for CRAN
tar_dir({ # tar_dir() runs code from a temp dir for CRAN.
tar_script(tar_target_raw("x", quote(1 + 1)), ask = FALSE)
tar_make()
tar_read(x)
})
}