Evaluate multiple expressions created with symbol substitution.

Loop over a grid of values, create an expression object from each one, and then evaluate that expression. Helps with general metaprogramming.

tar_eval() expects an unevaluated expression for the expr object, whereas tar_eval_raw() expects an evaluated expression object.

Usage

tar_eval(expr, values, envir = parent.frame())

tar_eval_raw(expr, values, envir = parent.frame())

Arguments

expr

Starting expression. Values are iteratively substituted in place of symbols in expr to create each new expression, and then each new expression is evaluated.

tar_eval() expects an unevaluated expression for the expr object, whereas tar_eval_raw() expects an evaluated expression object.

values

List of values to substitute into expr to create the expressions. All elements of values must have the same length.

envir

Environment in which to evaluate the new expressions.

Value

A list of return values from the generated expression objects. Often, these values are target definition objects. See the "Target definition objects" section for background on target definition objects specifically.

Target definition objects

Most tarchetypes functions are target factories, which means they return target definition objects or lists of target definition objects. target definition 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 definition 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 definition objects.

See also

Other Metaprogramming utilities: tar_sub()

Examples

# tar_map() is incompatible with tar_render() because the latter
# operates on preexisting tar_target() objects. By contrast,
# tar_eval() and tar_sub() iterate over the literal code
# farther upstream.
values <- list(
  name = lapply(c("name1", "name2"), as.symbol),
  file = list("file1.Rmd", "file2.Rmd")
)
tar_sub(list(name, file), values = values)
#> [[1]]
#> expression(list(name1, "file1.Rmd"))
#> 
#> [[2]]
#> expression(list(name2, "file2.Rmd"))
#> 
tar_sub(tar_render(name, file), values = values)
#> [[1]]
#> expression(tar_render(name1, "file1.Rmd"))
#> 
#> [[2]]
#> expression(tar_render(name2, "file2.Rmd"))
#> 
path <- tempfile()
file.create(path)
#> [1] TRUE
str(tar_eval(tar_render(name, path), values = values))
#> List of 2
#>  $ :Classes 'tar_stem', 'tar_builder', 'tar_target', 'environment' <environment: 0x56335545f6f0> 
#>  $ :Classes 'tar_stem', 'tar_builder', 'tar_target', 'environment' <environment: 0x563355539fb8> 
str(tar_eval_raw(quote(tar_render(name, path)), values = values))
#> List of 2
#>  $ :Classes 'tar_stem', 'tar_builder', 'tar_target', 'environment' <environment: 0x563355700750> 
#>  $ :Classes 'tar_stem', 'tar_builder', 'tar_target', 'environment' <environment: 0x5633557c72b8> 
# So in your _targets.R file, you can define a pipeline like as below.
# Just make sure to set a unique name for each target
# (which tar_map() does automatically).
values <- list(
  name = lapply(c("name1", "name2"), as.symbol),
  file = c(path, path)
)
list(
  tar_eval(tar_render(name, file), values = values)
)
#> [[1]]
#> [[1]][[1]]
#> <tar_stem> 
#>   name: name1 
#>   description:  
#>   command:
#>     tarchetypes::tar_render_run(path = "/tmp/RtmpaqPtwQ/file5c132cd72f9", 
#>         args = list(input = "/tmp/RtmpaqPtwQ/file5c132cd72f9", knit_root_dir = getwd(), 
#>             quiet = TRUE), deps = list()) 
#>   format: file 
#>   repository: local 
#>   iteration method: vector 
#>   error mode: stop 
#>   memory mode: auto 
#>   storage mode: worker 
#>   retrieval mode: auto 
#>   deployment mode: worker 
#>   priority: 0 
#>   resources:
#>     list() 
#>   cue:
#>     seed: TRUE
#>     file: TRUE
#>     iteration: TRUE
#>     repository: TRUE
#>     format: TRUE
#>     depend: TRUE
#>     command: TRUE
#>     mode: thorough 
#>   packages:
#>     tarchetypes
#>     stats
#>     graphics
#>     grDevices
#>     utils
#>     datasets
#>     methods
#>     base 
#>   library:
#>     NULL
#> [[1]][[2]]
#> <tar_stem> 
#>   name: name2 
#>   description:  
#>   command:
#>     tarchetypes::tar_render_run(path = "/tmp/RtmpaqPtwQ/file5c132cd72f9", 
#>         args = list(input = "/tmp/RtmpaqPtwQ/file5c132cd72f9", knit_root_dir = getwd(), 
#>             quiet = TRUE), deps = list()) 
#>   format: file 
#>   repository: local 
#>   iteration method: vector 
#>   error mode: stop 
#>   memory mode: auto 
#>   storage mode: worker 
#>   retrieval mode: auto 
#>   deployment mode: worker 
#>   priority: 0 
#>   resources:
#>     list() 
#>   cue:
#>     seed: TRUE
#>     file: TRUE
#>     iteration: TRUE
#>     repository: TRUE
#>     format: TRUE
#>     depend: TRUE
#>     command: TRUE
#>     mode: thorough 
#>   packages:
#>     tarchetypes
#>     stats
#>     graphics
#>     grDevices
#>     utils
#>     datasets
#>     methods
#>     base 
#>   library:
#>     NULL
#>