mirai (version 1.2.0)

collect_mirai: mirai (Collect Value)

Description

collect_mirai waits for the ‘mirai’ to resolve if still in progress, and returns its value directly. It is a more efifcient version of and equivalent to call_mirai(x)$data.

Usage

collect_mirai(x)

Value

An object (the return value of the ‘mirai’), or a list of such objects (the same length as ‘x’, preserving names).

Arguments

x

a ‘mirai’ object, or list of ‘mirai’ objects.

Alternatively

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.

Using unresolved on a ‘mirai’ returns TRUE only if it has yet to resolve and FALSE otherwise. This is suitable for use in control flow statements such as while or if.

Errors

If an error occurs in evaluation, the error message is returned as a character string of class ‘miraiError’ and ‘errorValue’ (the stack trace is available at $stack.trace on the error object). is_mirai_error may be used to test for this.

If a daemon crashes or terminates unexpectedly during evaluation, an ‘errorValue’ 19 (Connection reset) is returned (when not using dispatcher or using dispatcher with retry = FALSE). Otherwise, using dispatcher with retry = TRUE, the mirai will remain unresolved and is automatically re-tried on the next daemon to connect to the particular instance. To cancel the task instead, use saisei(force = TRUE) (see saisei).

is_error_value tests for all error conditions including ‘mirai’ errors, interrupts, and timeouts.

Details

This function will wait for the asynchronous operation(s) to complete if still in progress (blocking), and is not interruptible.

x[] may be used to wait for and return the value of a mirai x, and is the user-interruptible counterpart to collect_mirai(x).

Examples

if (interactive()) {
# Only run examples in interactive R sessions

# using collect_mirai()
df1 <- data.frame(a = 1, b = 2)
df2 <- data.frame(a = 3, b = 1)
m <- mirai(as.matrix(rbind(df1, df2)), df1 = df1, df2 = df2, .timeout = 1000)
collect_mirai(m)

# using x[]
m[]

}