Execute and Control System Processes
Tools to run system processes in the background, read their standard output and error and kill them.
processx can poll the standard output and error of a single process, or multiple processes, using the operating system’s polling and waiting facilities, with a timeout.
- Features
- Installation
- Usage
- Related tools
- Code of Conduct
- License
- Start system processes in the background and find their process id.
- Read the standard output and error, using non-blocking connections
- Poll the standard output and error connections of a single process or multiple processes.
- Write to the standard input of background processes.
- Check if a background process is running.
- Wait on a background process, or multiple processes, with a timeout.
- Get the exit status of a background process, if it has already finished.
- Kill background processes.
- Kill background process, when its associated object is garbage collected.
- Kill background processes and all their child processes.
- Works on Linux, macOS and Windows.
- Lightweight, it only depends on the also lightweight R6 and ps packages.
Install the stable version from CRAN:
install.packages("processx")
If you need the development version, install it from GitHub:
pak::pak("r-lib/processx")
library(processx)
Note: the following external commands are usually present in macOS and Linux systems, but not necessarily on Windows. We will also use the
px
command line tool (px.exe
on Windows), that is a very simple program that can produce output tostdout
andstderr
, with the specified timings.
px <- paste0(
system.file(package = "processx", "bin", "px"),
system.file(package = "processx", "bin", .Platform$r_arch, "px.exe")
)
px
#> [1] "/Users/gaborcsardi/Library/R/arm64/4.2/library/processx/bin/px"
The run()
function runs an external command. It requires a single
command, and a character vector of arguments. You don’t need to quote
the command or the arguments, as they are passed directly to the
operating system, without an intermediate shell.
run("echo", "Hello R!")
#> $status
#> [1] 0
#>
#> $stdout
#> [1] "Hello R!\n"
#>
#> $stderr
#> [1] ""
#>
#> $timeout
#> [1] FALSE
Short summary of the px
binary we are using extensively below:
result <- run(px, "--help", echo = TRUE)
#> Usage: px [command arg] [command arg] ...
#>
#> Commands:
#> sleep <seconds> -- sleep for a number os seconds
#> out <string> -- print string to stdout
#> err <string> -- print string to stderr
#> outln <string> -- print string to stdout, add newline
#> errln <string> -- print string to stderr, add newline
#> errflush -- flush stderr stream
#> cat <filename> -- print file to stdout
#> return <exitcode> -- return with exitcode
#> writefile <path> <string> -- write to file
#> write <fd> <string> -- write to file descriptor
#> echo <fd1> <fd2> <nbytes> -- echo from fd to another fd
#> getenv <var> -- environment variable to stdout
Note: From version 3.0.1, processx does not let you specify a full shell command line, as this involves starting a grandchild process from the child process, and it is difficult to clean up the grandchild process when the child process is killed. The user can still start a shell (
sh
orcmd.exe
) directly of course, and then proper cleanup is the user’s responsibility.
By default run()
throws an error if the process exits with a non-zero
status code. To avoid this, specify error_on_status = FALSE
:
run(px, c("out", "oh no!", "return", "2"), error_on_status = FALSE)
#> $status
#> [1] 2
#>
#> $stdout
#> [1] "oh no!"
#>
#> $stderr
#> [1] ""
#>
#> $timeout
#> [1] FALSE
To show the output of the process on the screen, use the echo
argument. Note that the order of stdout
and stderr
lines may be
incorrect, because they are coming from two different connections.
result <- run(px,
c("outln", "out", "errln", "err", "outln", "out again"),
echo = TRUE)
#> out
#> out again
#> err
If you have a terminal that support ANSI colors, then the standard error output is shown in red.
The standard output and error are still included in the result of the
run()
call:
result
#> $status
#> [1] 0
#>
#> $stdout
#> [1] "out\nout again\n"
#>
#> $stderr
#> [1] "err\n"
#>
#> $timeout
#> [1] FALSE
Note that run()
is different from system()
, and it always shows the
output of the process on R’s proper standard output, instead of writing
to the terminal directly. This means for example that you can capture
the output with capture.output()
or use sink()
, etc.:
out1 <- capture.output(r1 <- system("ls"))
out2 <- capture.output(r2 <- run("ls", echo = TRUE))
out1
#> character(0)
out2
#> [1] "CODE_OF_CONDUCT.md" "DESCRIPTION" "LICENSE"
#> [4] "LICENSE.md" "Makefile" "NAMESPACE"
#> [7] "NEWS.md" "R" "README.Rmd"
#> [10] "README.md" "_pkgdown.yml" "codecov.yml"
#> [13] "inst" "man" "processx.Rproj"
#> [16] "src" "tests"
The spinner
option of run()
puts a calming spinner to the terminal
while the background program is running. The spinner is always shown in
the first character of the last line, so you can make it work nicely
with the regular output of the background process if you like. E.g. try
this in your R terminal:
result <- run(px,
c("out", " foo",
"sleep", "1",
"out", "\r bar",
"sleep", "1",
"out", "\rX foobar\n"),
echo = TRUE, spinner = TRUE)
run()
can call an R function for each line of the standard output or
error of the process, just supply the stdout_line_callback
or the
stderr_line_callback
arguments. The callback functions take two
arguments, the first one is a character scalar, the output line. The
second one is the process
object that represents the background
process. (See more below about process
objects.) You can manipulate
this object in the callback, if you want. For example you can kill it in
response to an error or some text on the standard output:
cb <- function(line, proc) {
cat("Got:", line, "\n")
if (line == "done") proc$kill()
}
result <- run(px,
c("outln", "this", "outln", "that", "outln", "done",
"outln", "still here", "sleep", "10", "outln", "dead by now"),
stdout_line_callback = cb,
error_on_status = FALSE,
)
#> Got: this
#> Got: that
#> Got: done
#> Got: still here
result
#> $status
#> [1] -9
#>
#> $stdout
#> [1] "this\nthat\ndone\nstill here\n"
#>
#> $stderr
#> [1] ""
#>
#> $timeout
#> [1] FALSE
Keep in mind, that while the R callback is running, the background
process is not stopped, it is also running. In the previous example,
whether still here
is printed or not depends on the scheduling of the
R process and the background process by the OS. Typically, it is
printed, because the R callback takes a while to run.
In addition to the line-oriented callbacks, the stdout_callback
and
stderr_callback
arguments can specify callback functions that are
called with output chunks instead of single lines. A chunk may contain
multiple lines (separated by \n
or \r\n
), or even incomplete lines.
If you need better control over possibly multiple background processes,
then you can use the R6 process
class directly.
To start a new background process, create a new instance of the
process
class.
p <- process$new("sleep", "20")
A process can be killed via the kill()
method.
p$is_alive()
#> [1] TRUE
p$kill()
#> [1] TRUE
p$is_alive()
#> [1] FALSE
Note that processes are finalized (and killed) automatically if the
corresponding process
object goes out of scope, as soon as the object
is garbage collected by R:
p <- process$new("sleep", "20")
rm(p)
invisible(gc())
Here, the direct call to the garbage collector kills the sleep
process
as well. See the cleanup
option if you want to avoid this behavior.
By default the standard output and error of the processes are ignored.
You can set the stdout
and stderr
constructor arguments to a file
name, and then they are redirected there, or to "|"
, and then processx
creates connections to them. (Note that starting from processx 3.0.0
these connections are not regular R connections, because the public R
connection API was retroactively removed from R.)
The read_output_lines()
and read_error_lines()
methods can be used
to read complete lines from the standard output or error connections.
They work similarly to the readLines()
base R function.
Note, that the connections have a buffer, which can fill up, if R does not read out the output, and then the process will stop, until R reads the connection and the buffer is freed.
Always make sure that you read out the standard output and/or error of the pipes, otherwise the background process will stop running!
If you don’t need the standard output or error any more, you can also close it, like this:
close(p$get_output_connection())
close(p$get_error_connection())
Note that the connections used for reading the output and error streams are non-blocking, so the read functions will return immediately, even if there is no text to read from them. If you want to make sure that there is data available to read, you need to poll, see below.
p <- process$new(px,
c("sleep", "1", "outln", "foo", "errln", "bar", "outln", "foobar"),
stdout = "|", stderr = "|")
p$read_output_lines()
#> character(0)
p$read_error_lines()
#> character(0)
The standard R way to query the end of the stream for a non-blocking
connection, is to use the isIncomplete()
function. After a read
attempt, this function returns FALSE
if the connection has surely no
more data. (If the read attempt returns no data, but isIncomplete()
returns TRUE
, then the connection might deliver more data in the
future.
The is_incomplete_output()
and is_incomplete_error()
functions work
similarly for process
objects.
The poll_io()
method waits for data on the standard output and/or
error of a process. It will return if any of the following events
happen:
- data is available on the standard output of the process (assuming there is a connection to the standard output).
- data is available on the standard error of the process (assuming the is a connection to the standard error).
- The process has finished and the standard output and/or error connections were closed on the other end.
- The specified timeout period expired.
For example the following code waits about a second for output.
p <- process$new(px, c("sleep", "1", "outln", "kuku"), stdout = "|")
## No output yet
p$read_output_lines()
#> character(0)
## Wait at most 5 sec
p$poll_io(5000)
#> output error process
#> "ready" "nopipe" "nopipe"
## There is output now
p$read_output_lines()
#> [1] "kuku"
If you need to manage multiple background processes, and need to wait
for output from all of them, processx defines a poll()
function that
does just that. It is similar to the poll_io()
method, but it takes
multiple process objects, and returns as soon as one of them have data
on standard output or error, or a timeout expires. Here is an example:
p1 <- process$new(px, c("sleep", "1", "outln", "output"), stdout = "|")
p2 <- process$new(px, c("sleep", "2", "errln", "error"), stderr = "|")
## After 100ms no output yet
poll(list(p1 = p1, p2 = p2), 100)
#> $p1
#> output error process
#> "timeout" "nopipe" "nopipe"
#>
#> $p2
#> output error process
#> "nopipe" "timeout" "nopipe"
## But now we surely have something
poll(list(p1 = p1, p2 = p2), 1000)
#> $p1
#> output error process
#> "ready" "nopipe" "nopipe"
#>
#> $p2
#> output error process
#> "nopipe" "silent" "nopipe"
p1$read_output_lines()
#> [1] "output"
## Done with p1
close(p1$get_output_connection())
#> NULL
## The second process should have data on stderr soonish
poll(list(p1 = p1, p2 = p2), 5000)
#> $p1
#> output error process
#> "closed" "nopipe" "nopipe"
#>
#> $p2
#> output error process
#> "nopipe" "ready" "nopipe"
p2$read_error_lines()
#> [1] "error"
As seen before, is_alive()
checks if a process is running. The
wait()
method can be used to wait until it has finished (or a
specified timeout expires).. E.g. in the following code wait()
needs
to wait about 2 seconds for the sleep
px
command to finish.
p <- process$new(px, c("sleep", "2"))
p$is_alive()
#> [1] TRUE
Sys.time()
#> [1] "2022-06-10 13:57:49 CEST"
p$wait()
Sys.time()
#> [1] "2022-06-10 13:57:51 CEST"
It is safe to call wait()
multiple times:
p$wait() # already finished!
After a process has finished, its exit status can be queried via the
get_exit_status()
method. If the process is still running, then this
method returns NULL
.
p <- process$new(px, c("sleep", "2"))
p$get_exit_status()
#> NULL
p$wait()
p$get_exit_status()
#> [1] 0
In general, mixing processx (via callr or not) and parallel works fine.
If you use parallel’s ‘fork’ clusters, e.g. via
parallel::mcparallel()
, then you might see two issues. One is that
processx will not be able to determine the exit status of some processx
processes. This is because the status is read out by parallel, and
processx will set it to NA
. The other one is that parallel might
complain that it could not clean up some subprocesses. This is not an
error, and it is harmless, but it does hold up R for about 10 seconds,
before parallel gives up. To work around this, you can set the
PROCESSX_NOTIFY_OLD_SIGCHLD
environment variable to a non-empty value,
before you load processx. This behavior might be the default in the
future.
Errors are typically signalled via non-zero exits statuses. The processx constructor fails if the external program cannot be started, but it does not deal with errors that happen after the program has successfully started running.
p <- process$new("nonexistant-command-for-sure")
#> Error in c("process_initialize(self, private, command, args, stdin, stdout, ", : ! Native call to `processx_exec` failed
#> Caused by error in `chain_call(c_processx_exec, command, c(command, args), pty, pty_options, …` at initialize.R:138:3:
#> ! cannot start processx process 'nonexistant-command-for-sure' (system error 2, No such file or directory) @unix/processx.c:613 (processx_exec)
p2 <- process$new(px, c("sleep", "1", "command-does-not-exist"))
p2$wait()
p2$get_exit_status()
#> [1] 5
-
The
ps
package can query, list, manipulate all system processes (not just subprocesses), and processx uses it internally for some of its functionality. You can also convert aprocessx::process
object to aps::ps_handle
with theas_ps_handle()
method. -
The
callr
package uses processx to start another R process, and run R code in it, in the foreground or background.
Please note that the processx project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
MIT © Ascent Digital Services, RStudio, Gábor Csárdi