07. R studio/R 工具指南（六：后台运行R 命令）

a <- 3*x

Error in eval(statements[[idx]], envir = sourceEnv) :
  object 'x' not found
Calls: sourceWithProgress -> eval -> eval
Execution halted

"Copy job results" 里有三个选项:

Don't copy: 不复制到当前全局变量
To global environment: 变量直接复制到当前全局变量,
To results object in global environment: 变量会存放在environment 对象中

> test_results$x
[1] 3

remotes::install_github("lindeloev/job")

> remotes::install_github("lindeloev/job")
错误: Failed to install 'unknown package' from GitHub:
  畸形'Config/testthat/edit ...'开头行!

job::job(
  { tmp <- matrix(sample(letters, 1000, replace = T), ncol = 10) }
)

job::job({<your code>})

job::job(brm_result = {
  fit = brm(model, data)
  fit = add_criterion(fit, "loo")
  print(summary(fit))  # Show a summary in the job
  the_test = hypothesis(fit, "hp > 0")
})

Finer control
RStudio jobs spin up a new session, i.e., a new environment. By default, job::job() will make this environment identical to your current one. But you can fine control this:

import: the default "auto" setting imports all objects that are referenced by the code into the job. Control this using job::job({}, import = c(model, data)). You can also import everything (import = "all") or nothing (import = NULL).

packages: by default, all attached packages are attached in the job. Control this using job::job({}, packages = c("brms")) or set packages = NULL to load nothing. If brms is not loaded in your current session, adding library("brms") to the job code may be more readable.

options: by default, all options are overwritten/inserted to the job. Control this using, e.g., job::job({}, opts = list(mc.cores = 2) or set opts = NULL to use default options. If you want to set job-specific options, adding options(mc.cores = 2) to the job code may be more readable.

export: in the example above, we assigned the job environment to brm_result upon completion. Naturally, you can choose any name, e.g., job::job(fancy_name = {a = 5}). To return nothing, use an unnamed code chunk (insert results to globalenv() and remove everything before return: (job::job({a = 5; rm(list=ls())}). Returning nothing is useful when

your main result is a text output or a file on the disk, or

when the return is a very large object. The underlying rstudioapi::jobRunScript() is slow in the back-transfer so it's usually faster to saveRDS(obj, filename) them in the job and readRDS(filename) into your current session.

Some use cases
Model training, cross validation, or hyperparameter tuning: train multiple models simultaneously, each in their own job. If one fails, the others continue.
Heavy I/O tasks, like processing large files. Save the results to disk and return nothing.
Run unit tests and other code in an empty environment. By default, devtools::test() runs in the current environment, including manually defined variables (e.g., from the last test-run) and attached packages. Call job::job({devtools::test()}, import = NULL, packages = NULL, opts = NULL) to run the test in complete isolation.
Upgrading packages
See also
job::job() is aimed at easing interactive development within RStudio. For larger problems, production code, and solutions that work outside of RStudio, check out:

The future package's %<- operator combined with plan(multisession).

The callr package is a general tool to run code in new R sessions.