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.
poll()
R CMD
commandsR CMD
commands, synchronously or
asynchronously.r_process
,
rcmd_process
and rscript_process
R6 classes,
based on processx::process
.Install the stable version from CRAN:
install.packages("callr")
Use r()
to run an R function in a new R process. The
results are passed back seamlessly:
::r(function() var(iris[, 1:4])) callr
You can pass arguments to the function by setting args
to the list of arguments. This is often necessary as these arguments are
explicitly copied to the child process, whereas the evaluated function
cannot refer to variables in the parent. For example, the following does
not work:
<- cars
mycars ::r(function() summary(mycars)) callr
But this does:
<- cars
mycars ::r(function(x) summary(x), args = list(mycars)) callr
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.
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) }) callr
callr copies errors from the child process back to the main R session:
::r(function() 1 + "A") callr
callr sets the
.Last.error
variable, and after an error you can inspect
this for more details about the error, including stack traces both from
the main R process and the subprocess.
.Last.error
The error objects has two parts. The first belongs to the main process, and the second belongs to the subprocess.
.Last.error
also includes a stack trace, that includes
both the main R process and the subprocess:
The top part of the trace contains the frames in the main process, and the bottom part contains the frames in the subprocess, starting with the anonymous function.
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:
<- callr::r(function() { print("hello world!"); message("hello again!") },
x stdout = "/tmp/out", stderr = "/tmp/err"
)readLines("/tmp/out")
readLines("/tmp/err")
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.
r_bg()
is similar to r()
but it starts the
R process in the background. It returns an r_process
R6
object, that provides a rich API:
<- callr::r_bg(function() Sys.sleep(.2))
rp rp
This is a list of all r_process
methods:
ls(rp)
These include all methods of the processx::process
superclass and the new get_result()
method, to retrieve the
R object returned by the function call. Some of the handiest methods
are:
get_exit_status()
to query the exit status of a
finished process.get_result()
to collect the return value of the R
function call.interrupt()
to send an interrupt to the process. This
is equivalent to a CTRL+C
key press, and the R process
might ignore it.is_alive()
to check if the process is alive.kill()
to terminate the process.poll_io()
to wait for any standard output, standard
error, or the completion of the process, with a timeout.read_*()
to read the standard output or error.suspend()
and resume()
to stop and
continue a process.wait()
to wait for the completion of the process, with
a timeout.poll()
Multiple background R processes are best managed with the
processx::poll()
function that waits for events (standard
output/error or termination) from multiple processes. It returns as soon
as one process has generated an event, or if its timeout has expired.
The timeout is in milliseconds.
<- callr::r_bg(function() { Sys.sleep(1/2); "1 done" })
rp1 <- callr::r_bg(function() { Sys.sleep(1/1000); "2 done" })
rp2 ::poll(list(rp1, rp2), 1000) processx
$get_result() rp2
::poll(list(rp1), 1000) processx
$get_result() rp1
r_session
is another processx::process
subclass that represents a persistent background R session:
<- callr::r_session$new()
rs rs
r_session$run()
is a synchronous call, that works
similarly to r()
, but uses the persistent session.
r_session$call()
starts the function call and returns
immediately. The r_session$poll_process()
method or
processx::poll()
can then be used to wait for the
completion or other events from one or more R sessions, R processes or
other processx::process
objects.
Once an R session is done with an asynchronous computation, its
poll_process()
method returns "ready"
and the
r_session$read()
method can read out the result.
<- callr::r_session$new()
rs $run(function() runif(10)) rs
$call(function() rnorm(10))
rs rs
$poll_process(2000) rs
$read() rs
R CMD
commandsThe 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") callr
This returns a list with three components: the standard output, the
standard error, and the exit (status) code of the R CMD
command.
Please note that the callr project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
MIT © Mango Solutions, RStudio