Loading Workflow Objects
Last updated on 2024-03-12 | Edit this page
Overview
Questions
- ワークフローはどこで行われるのか?
- ワークフローによって構築されたオブジェクトを確認するには?
Objectives
- Explain where
targets
runs the workflow and why - Be able to load objects built by the workflow into your R session
ワークフローはどこで行われるのか?
So we just finished running our first workflow. Now you probably want
to look at its output. But, if we just call the name of the object (for
example, penguins_data
), we get an error.
R
penguins_data
ERROR
Error in eval(expr, envir, enclos): object 'penguins_data' not found
Where are the results of our workflow?
We don’t see the workflow results because targets
runs the workflow in a separate R session that we can’t
interact with. This is for reproducibility—the objects built by the
workflow should only depend on the code in your project, not any
commands you may have interactively given to R.
Fortunately, targets
has two functions that can be used
to load objects built by the workflow into our current session,
tar_load()
and tar_read()
. Let’s see how these
work.
tar_load()
tar_load()
loads an object built by the workflow into
the current session. Its first argument is the name of the object you
want to load. Let’s use this to load penguins_data
and get
an overview of the data with summary()
.
R
tar_load(penguins_data)
summary(penguins_data)
OUTPUT
species bill_length_mm bill_depth_mm
Length:342 Min. :32.10 Min. :13.10
Class :character 1st Qu.:39.23 1st Qu.:15.60
Mode :character Median :44.45 Median :17.30
Mean :43.92 Mean :17.15
3rd Qu.:48.50 3rd Qu.:18.70
Max. :59.60 Max. :21.50
tar_load()
は、その副作用、つまり、目的のオブジェクトを現在のRセッションにロードするために使用されることに注意してください。
It doesn’t actually return a value.
tar_read()
tar_read()
is similar to tar_load()
in that
it is used to retrieve objects built by the workflow, but unlike
tar_load()
, it returns them directly as output.
Let’s try it with penguins_csv_file
.
R
tar_read(penguins_csv_file)
OUTPUT
[1] "/home/runner/.local/share/renv/cache/v5/R-4.3/x86_64-pc-linux-gnu/palmerpenguins/0.1.1/6c6861efbc13c1d543749e9c7be4a592/palmerpenguins/extdata/penguins_raw.csv"
We immediately see the contents of penguins_csv_file
.
But it has not been loaded into the environment. If you try to run
penguins_csv_file
now, you will get an error:
R
penguins_csv_file
ERROR
Error in eval(expr, envir, enclos): object 'penguins_csv_file' not found
When to use which function
tar_load()
tends to be more useful when you want to load
objects and do things with them. tar_read()
is more useful
when you just want to immediately inspect an object.
The targets cache
If you close your R session, then re-start it and use
tar_load()
or tar_read()
, you will notice that
it can still load the workflow objects. In other words, the workflow
output is saved across R sessions. How is this
possible?
You may have noticed a new folder has appeared in your project,
called _targets
. This is the targets
cache. It contains all of the workflow output; that is how we
can load the targets built by the workflow even after quitting then
restarting R.
You should not edit the contents of the cache by hand (with one exception). Doing so would make your analysis non-reproducible.
The one exception to this rule is a special subfolder called
_targets/user
. This folder does not exist by default. You
can create it if you want, and put whatever you want inside.
Generally, _targets/user
is a good place to store files
that are not code, like data and output.
Note that if you don’t have anything in _targets/user
that you need to keep around, it is possible to “reset” your workflow by
simply deleting the entire _targets
folder. Of course, this
means you will need to run everything over again, so don’t do this
lightly!