Evaluate an expression asynchronously in a new background R process or persistent daemon (local or remote). This function will return immediately with a 'mirai', which will resolve to the evaluated result once complete.
mirai(.expr, ..., .args = list(), .timeout = NULL, .compute = "default")an expression to evaluate asynchronously (of arbitrary length, wrapped in {} if necessary), or a language object passed by name.
(optional) named arguments (name = value pairs) specifying objects referenced in '.expr'. Used in addition to, and taking precedence over, any arguments specified via '.args'.
(optional) either a list of objects to be passed by name (found in the current scope), or else a list of name = value pairs, as in '...'.
[default NULL] for no timeout, or an integer value in milliseconds. A mirai will resolve to an 'errorValue' 5 (timed out) if evaluation exceeds this limit.
[default 'default'] character value for the compute profile to use when sending the mirai.
A 'mirai' object.
This function will return a 'mirai' object immediately.
The value of a mirai may be accessed at any time at $data, and
if yet to resolve, an 'unresolved' logical NA will be returned instead.
unresolved may be used on a mirai, returning TRUE if a
'mirai' has yet to resolve and FALSE otherwise. This is suitable for use
in control flow statements such as while or if.
Alternatively, to call (and wait for) the result, use call_mirai
on the returned mirai. This will block until the result is returned
(although interruptible with e.g. ctrl+c).
The expression '.expr' will be evaluated in a separate R process in a clean environment, which is not the global environment, consisting only of the named objects passed as '...' and/or the list supplied to '.args'.
If an error occurs in evaluation, the error message is returned as a
character string of class 'miraiError' and 'errorValue'.
is_mirai_error may be used to test for this.
is_error_value tests for all error conditions including
'mirai' errors, interrupts, and timeouts.
Specify '.compute' to send the mirai using a specific compute profile (if
previously created by daemons), otherwise leave as 'default'.
if (interactive()) {
# Only run examples in interactive R sessions
# specifying objects via '...'
n <- 3
m <- mirai(x + y + 2, x = 2, y = n)
m
m$data
Sys.sleep(0.2)
m$data
# passing existing objects by name via '.args'
df1 <- data.frame(a = 1, b = 2)
df2 <- data.frame(a = 3, b = 1)
m <- mirai(as.matrix(rbind(df1, df2)), .args = list(df1, df2), .timeout = 1000)
call_mirai(m)$data
# using unresolved()
m <- mirai(
{
res <- rnorm(n)
res / rev(res)
},
n = 1e6
)
while (unresolved(m)) {
cat("unresolved\n")
Sys.sleep(0.1)
}
str(m$data)
# evaluating scripts using source(local = TRUE) in '.expr'
n <- 10L
file <- tempfile()
cat("r <- rnorm(n)", file = file)
m <- mirai({source(file, local = TRUE); r}, .args = list(file, n))
call_mirai(m)[["data"]]
unlink(file)
# specifying global variables using list2env(envir = .GlobalEnv) in '.expr'
n <- 10L
file <- tempfile()
cat("r <- rnorm(n)", file = file)
globals <- list(file = file, n = n)
m <- mirai(
{
list2env(globals, envir = .GlobalEnv)
source(file)
r
},
globals = globals
)
call_mirai(m)[["data"]]
unlink(file)
# passing a language object to '.expr' and a named list to '.args'
expr <- quote(a + b + 2)
args <- list(a = 2, b = 3)
m <- mirai(.expr = expr, .args = args)
call_mirai(m)$data
}