Target with an R Markdown document.
Shorthand to include an R Markdown document in a
targets pipeline.
tar_render(
name,
path,
tidy_eval = targets::tar_option_get("tidy_eval"),
packages = targets::tar_option_get("packages"),
library = targets::tar_option_get("library"),
error = targets::tar_option_get("error"),
deployment = "main",
priority = targets::tar_option_get("priority"),
resources = targets::tar_option_get("resources"),
retrieval = targets::tar_option_get("retrieval"),
cue = targets::tar_option_get("cue"),
quiet = TRUE,
...
)name |
Symbol, name of the target. Subsequent targets
can refer to this name symbolically to induce a dependency relationship:
e.g. |
path |
Character string, file path to the R Markdown source file. Must have length 1. |
tidy_eval |
Logical, whether to enable tidy evaluation
when interpreting |
packages |
Character vector of packages to load right before
the target builds. Use |
library |
Character vector of library paths to try
when loading |
error |
Character of length 1, what to do if the target
runs into an error. If |
deployment |
Character of length 1, only relevant to
|
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 |
resources |
A named list of computing resources. Uses:
|
retrieval |
Character of length 1, only relevant to
|
cue |
An optional object from |
quiet |
An option to suppress printing of the pandoc command line. |
... |
Named arguments to |
tar_render() is an alternative to tar_target() for
R Markdown reports that depend on other targets. The R Markdown source
should mention dependency targets with tar_load() and tar_read()
in the active code chunks (which also allows you to render the report
outside the pipeline if the _targets/ data store already exists).
(Do not use tar_load_raw() or tar_read_raw() for this.)
Then, tar_render() defines a special kind of target. It
1. Finds all the tar_load()/tar_read() dependencies in the report
and inserts them into the target's command.
This enforces the proper dependency relationships.
(Do not use tar_load_raw() or tar_read_raw() for this.)
2. Sets format = "file" (see tar_target()) so targets
watches the files at the returned paths and reruns the report
if those files change.
3. Configures the target's command to return both the output
report files and the input source file. All these file paths
are relative paths so the project stays portable.
4. Forces the report to run in the user's current working directory
instead of the working directory of the report.
5. Sets convenient default options such as deployment = "main"
in the target and quiet = TRUE in rmarkdown::render().
A target object with format = "file".
When this target runs, it returns a character vector
of file paths: the rendered document, the source file,
and then the *_files/ directory if it exists.
Unlike rmarkdown::render(),
all returned paths are relative paths to ensure portability
(so that the project can be moved from one file system to another
without invalidating the target).
See the "Target objects" section for background.
Most tarchetypes functions are target factories,
which means they return target objects
or lists of target objects.
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.
Other Literate programming targets:
tar_knit_raw(),
tar_knit(),
tar_render_raw(),
tar_render_rep_raw(),
tar_render_rep()
if (identical(Sys.getenv("TAR_LONG_EXAMPLES"), "true")) {
targets::tar_dir({ # tar_dir() runs code from a temporary directory.
# Unparameterized R Markdown:
lines <- c(
"---",
"title: report.Rmd source file",
"output_format: html_document",
"---",
"Assume these lines are in report.Rmd.",
"```{r}",
"targets::tar_read(data)",
"```"
)
# Include the report in a pipeline as follows.
targets::tar_script({
library(tarchetypes)
list(
tar_target(data, data.frame(x = seq_len(26), y = letters)),
tar_render(report, "report.Rmd")
)
}, ask = FALSE)
# Then, run the targets pipeline as usual.
# Parameterized R Markdown:
lines <- c(
"---",
"title: 'report.Rmd source file with parameters'",
"output_format: html_document",
"params:",
" your_param: \"default value\"",
"---",
"Assume these lines are in report.Rmd.",
"```{r}",
"print(params$your_param)",
"```"
)
# Include the report in the pipeline as follows.
targets::tar_script({
library(tarchetypes)
list(
tar_target(data, data.frame(x = seq_len(26), y = letters)),
tar_render(report, "report.Rmd", params = list(your_param = data))
)
}, ask = FALSE)
})
# Then, run the targets pipeline as usual.
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.