callr

Call R from R

It is sometimes useful to perform a computation in a separate R process, without affecting the current R process at all. This packages does exactly that.

---

• Installation
• Usage
  • Introduction
  • Passing arguments
  • Using packages
  • Error handling
  • Standard output and error
  • Showing progress
  • Tips
  • R CMD <command>
• License

Installation

Install the stable version from CRAN:

install.packages("callr")

Install the development version from GitHub:

source("https://install-github.me/r-lib/callr")

Usage

Introduction

Use r to run an R function in a new child process. The results are passed back seamlessly:

r(function() var(iris[, 1:4]))

#>              Sepal.Length Sepal.Width Petal.Length Petal.Width
#> Sepal.Length    0.6856935  -0.0424340    1.2743154   0.5162707
#> Sepal.Width    -0.0424340   0.1899794   -0.3296564  -0.1216394
#> Petal.Length    1.2743154  -0.3296564    3.1162779   1.2956094
#> Petal.Width     0.5162707  -0.1216394    1.2956094   0.5810063

Passing arguments

You can pass arguments to the function by setting args to the list of arguments. This is often necessary as these arguments are explicitly passed to the child process, whereas the evaluated function cannot refer to variables in the parent. For example, the following does not work:

mycars <- cars
r(function() summary(mycars))

#> Error in summary(mycars) (from internal.R#90) : object 'mycars' not found

But this does:

r(function(x) summary(x), args = list(mycars))

#>     speed           dist
#> Min.   : 4.0   Min.   :  2.00
#> 1st Qu.:12.0   1st Qu.: 26.00
#> Median :15.0   Median : 36.00
#> Mean   :15.4   Mean   : 42.98
#> 3rd Qu.:19.0   3rd Qu.: 56.00
#> Max.   :25.0   Max.   :120.00

Note that the arguments will be serialized and saved to a file, so if they are large R objects, it might take a long time for the child process to start up.

Using packages

You can use any R package in the child process, just make sure to refer to it explicitly with the :: operator. For example, the following code creates an igraph graph in the child, and calculates some metrics of it.

r(function() { g <- igraph::sample_gnp(1000, 4/1000); igraph::diameter(g) })

#> 12

Error handling

callr provides three ways to handle errors that happen in the child process. The default is to forward any errors to the parent:

r(function() 1 + "A")
#> Error in 1 + "A" : non-numeric argument to binary operator

You can catch these errors on the parent, but the context is of course lost. To get the context, you need to specify the error = "stack" option. This copies the whole stack to the parent on an error. The stack is part of the error object thrown on the parent, and you can catch it with tryCatch, and examine it. Here is an example:

tryCatch(
  r(function() { f <- function() g(); g <- function() 1 + "A"; f() },
    error = "stack"),
  error = function(e) print(e$stack)
)

#> $`(function () \n{\n    f <- function() g()\n    g <- function() 1 + "A"\n    f()`
#> <environment: 0x7fc1e4b61e08>
#>
#> $`#2: f()`
#> <environment: 0x7fc1e4b62150>
#>
#> $`#2: g()`
#> <environment: 0x7fc1e4b62188>
#>
#> attr(,"error.message")
#> [1] "non-numeric argument to binary operator"
#> attr(,"class")
#> [1] "dump.frames"

The third possible value for error is "debugger" which starts a debugger (see ?debugger in the call stack returned from the child:

r(function() { f <- function() g(); g <- function() 1 + "A"; f() },
  error = "debugger")

#> Message:  non-numeric argument to binary operator
#> Available environments had calls:
#> 1: (function ()
#> {
#>     f <- function() g()
#>     g <- function() 1 + "A"
#>     f()
#> 2: #1: f()
#> 3: #1: g()
#>
#> Enter an environment number, or 0 to exit  Selection:

Standard output and error

By default, the standard output and error of the child is lost, but you can request callr to redirect them to files, and then inspect the files in the parent:

x <- r(function() { print("hello world!"); message("hello again!") },
  stdout = "/tmp/out", stderr = "/tmp/err"
)
readLines("/tmp/out")

#> [1] "[1] \"hello world!\""

readLines("/tmp/err")

#> [1] "hello again!"

Showing progress

With the stdout option, the standard output is collected and can be examined once the child process finished. The show = TRUE options will also show the output of the child, as it is printed, on the console of the parent.

Tips

1) It is good practice to create an anonymous function for the r() call, instead of passing a function from a package to r() directly. This is because callr resets the environment of the function, which prevents some functions from working. Here is an example:

r(praise::praise)

#> Error: could not find function "is_template"

But with an anonymous function this works fine:

r(function() praise::praise())

#> [1] "You are outstanding!"

2) If the function you call in the other session calls quit() with a non-zero status, then callr interprets that as an R crash. Zero status is a clean exit, but callr returns NULL, as no results were saved:

r(function() quit(status = 0))
#> NULL

r(function() quit(status = 2))
#> Error: callr failed, could not start R, exited with non-zero status, has crashed or was killed

R CMD <command>

The rcmd() function calls an R CMD command. For example, you can call R CMD INSTALL, R CMD check or R CMD config this way:

rcmd("config", "CC")

#>$stdout
#>[1] "clang\n"
#>
#>$stderr
#>[1] ""
#>
#>$status
#>[1] 0

This returns a list with three components: the standard output, the standard error, and the exit (status) code of the R CMD command.

License

MIT © Mango Solutions, RStudio