tar_render: Target with an R Markdown document.

Description Usage Arguments Details Value Target objects See Also Examples

View source: R/tar_render.R

Description

Shorthand to include an R Markdown document in a targets pipeline.

Usage

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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,
  ...
)

Arguments

name

Symbol, name of the target. 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 named downstream_target which depends on a target upstream_target and a function f(). 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 with tar_meta(your_target, seed) and run set.seed() on the result to locally recreate the target's initial RNG state.

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 command and pattern. If TRUE, you can use the "bang-bang" operator !! to programmatically insert the values of global objects.

packages

Character vector of packages to load right before the target builds. 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.

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.)

deployment

Character of length 1, only relevant to tar_make_clustermq() and tar_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 of targets. See tar_resources() for details.

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). If "main", the target's dependencies are loaded on the host machine and sent to the worker before the target builds. If "worker", the worker loads the targets dependencies.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.

quiet

An option to suppress printing during rendering from knitr, pandoc command line and others. To only suppress printing of the last "Output created: " message, you can set rmarkdown.render.message to FALSE

...

Named arguments to rmarkdown::render(). These arguments are evaluated when the target actually runs in tar_make(), not when the target is defined. That means, for example, you can use upstream targets as parameters of parameterized R Markdown reports. tar_render(your_target, "your_report.Rmd", params = list(your_param = your_target)) # nolint will run rmarkdown::render("your_report.Rmd", params = list(your_param = your_target)). # nolint For parameterized reports, it is recommended to supply a distinct output_file argument to each tar_render() call and set useful defaults for parameters in the R Markdown source. See the examples section for a demonstration.

Details

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().

Value

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.

Target objects

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.

See Also

Other Literate programming targets: tar_knit_raw(), tar_knit(), tar_render_raw(), tar_render_rep_raw(), tar_render_rep()

Examples

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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.
}

tarchetypes documentation built on Aug. 4, 2021, 9:05 a.m.