everywhere: Evaluate Everywhere

In mirai: Minimalist Async Evaluation Framework for R

Evaluate Everywhere

Description

Evaluate an expression 'everywhere' on all connected daemons for the specified compute profile. Daemons must be set prior to calling this function. Performs operations across daemons such as loading packages or exporting common data. Resultant changes to the global environment, loaded packages and options are persisted regardless of a daemon's cleanup setting.

Usage

everywhere(.expr, ..., .args = list(), .min = 1L, .compute = NULL)

Arguments

.expr	(expression) code to evaluate asynchronously, or a language object. Wrap multi-line expressions in {}.
...	(named arguments | environment) objects required by .expr, assigned to the daemon's global environment. See 'evaluation' section below.
.args	(named list | environment) objects required by .expr, kept local to the evaluation environment (unlike ...). See 'evaluation' section below.
.min	(integer) minimum daemons to evaluate on (dispatcher only). Creates a synchronization point, useful for remote daemons that take time to connect.
.compute	(character) name of the compute profile. Each profile has its own independent set of daemons. NULL (default) uses the 'default' profile.

Details

If using dispatcher, this function forces a synchronization point: the everywhere() call must complete on all daemons before subsequent mirai evaluations proceed.

Calling everywhere() does not affect the RNG stream for mirai calls when using a reproducible seed value at daemons(). This allows the seed associated with each mirai call to be the same, regardless of the number of daemons used. However, code evaluated in an everywhere() call is itself non-reproducible if it involves random numbers.

Value

A 'mirai_map' (list of 'mirai' objects).

Evaluation

The expression .expr will be evaluated in a separate R process in a clean environment (not the global environment), consisting only of the objects supplied to .args, with the objects passed as ... assigned to the global environment of that process.

As evaluation occurs in a clean environment, all undefined objects must be supplied through ... and/or .args, including self-defined functions. Functions from a package should use namespaced calls such as mirai::mirai(), or else the package should be loaded beforehand as part of .expr.

Supply objects to ... rather than .args for evaluation to occur as if in your global environment. This is needed for non-local variables or helper functions required by other functions, which scoping rules may otherwise prevent from being found.

Examples

daemons(sync = TRUE)

# export common data by a super-assignment expression:
everywhere(y <<- 3)
mirai(y)[]

# '...' variables are assigned to the global environment
# '.expr' may be specified as an empty {} in such cases:
everywhere({}, a = 1, b = 2)
mirai(a + b - y == 0L)[]

# everywhere() returns a mirai_map object:
mp <- everywhere("just a normal operation")
mp
mp[.flat]
mp <- everywhere(stop("everywhere"))
collect_mirai(mp)
daemons(0)

# loading a package on all daemons
daemons(sync = TRUE)
everywhere(library(parallel))
m <- mirai("package:parallel" %in% search())
m[]
daemons(0)

mirai documentation built on Feb. 13, 2026, 9:07 a.m.