use_targets | R Documentation |
Set up targets
for an existing project.
use_targets(
script = targets::tar_config_get("script"),
scheduler = targets::use_targets_scheduler(),
open = interactive(),
overwrite = FALSE,
job_name = targets::tar_random_name()
)
script |
Character of length 1, where to write
the target script file. Defaults to |
scheduler |
Character of length 1, type of scheduler for parallel computing. See <books.ropensci.org/targets/hpc.html> for details. The default is automatically detected from your system (but PBS and Torque cannot be distinguished from SGE, and SGE is the default among the three). Possible values:
|
open |
Logical, whether to open the file for editing in the RStudio IDE. |
overwrite |
Logical of length 1, whether to overwrite the targets file and supporting files if they already exist. |
job_name |
Character of length 1, job name to supply to schedulers like SLURM. |
To set up a project-oriented function-oriented
workflow for targets
, use_targets()
writes:
A target script _targets.R
tailored to your system.
Template files "clustermq.tmpl"
and "future.tmpl"
to configure tar_make_clustermq()
and tar_make_future()
to a resource manager if detected on your system.
They should work out of the box on most systems, but
you may need to modify them by hand if you encounter errors.
Script run.R
to conveniently execute the pipeline using
tar_make()
. You can change this to tar_make_clustermq()
or tar_make_future()
and supply the workers
argument to either.
Script run.sh
to conveniently call run.R
in a persistent
background process. Enter ./run.sh
in the shell to run it.
If you have a high-performance computing scheduler
like Sun Grid Engine (SGE) (or select one using the
scheduler
argument of use_targets()
), then
script job.sh
is created. job.sh
conveniently executes run.R
as a job on a cluster. For example, to run the pipeline as a
job on an SGE cluster, enter qsub job.sh
in the terminal.
job.sh
should work out of the box on most systems, but
you may need to modify it by hand if you encounter errors.
After you call use_targets()
, there is still configuration left to do:
Open _targets.R
and edit by hand. Follow the comments to
write any options, packages, and target definitions
that your pipeline requires.
Edit run.R
and choose which pipeline function to execute
(tar_make()
, tar_make_clustermq()
, or tar_make_future()
).
If applicable, edit clustermq.tmpl
and/or future.tmpl
to configure settings for your resource manager.
If applicable, configure job.sh
, "clustermq.tmpl"
, and/or
"future.tmpl"
for your resource manager.
After you finished configuring your project, follow the steps at https://books.ropensci.org/targets/walkthrough.html#inspect-the-pipeline: # nolint
Run tar_glimpse()
and tar_manifest()
to check that the
targets in the pipeline are defined correctly.
Run the pipeline. You may wish to call a tar_make*()
function
directly, or you may run run.R
or run.sh
.
Inspect the target output using tar_read()
and/or tar_load()
.
Develop the pipeline as needed by manually editing _targets.R
and the scripts in R/
and repeating steps (1) through (3).
NULL
(invisibly).
Other help:
tar_reprex()
,
targets-package
,
use_targets_rmd()
if (identical(Sys.getenv("TAR_INTERACTIVE_EXAMPLES"), "true")) {
tar_dir({ # tar_dir() runs code from a temp dir for CRAN.
use_targets(open = FALSE)
})
}
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