futureAssign: Create a future assignment

In future: Unified Parallel and Distributed Processing in R for Everyone

Create a future assignment

Description

x %<-% value (also known as a "future assignment") and futureAssign("x", value) create a Future that evaluates the expression (value) and binds it to variable x (as a promise). The expression is evaluated in parallel in the background. Later on, when x is first queried, the value of future is automatically retrieved as it were a regular variable and x is materialized as a regular value.

Usage

futureAssign(
  x,
  value,
  envir = parent.frame(),
  substitute = TRUE,
  lazy = FALSE,
  seed = FALSE,
  globals = TRUE,
  packages = NULL,
  stdout = TRUE,
  conditions = "condition",
  earlySignal = FALSE,
  label = NULL,
  gc = FALSE,
  ...,
  assign.env = envir
)

x %<-% value

fassignment %globals% globals
fassignment %packages% packages

fassignment %seed% seed

fassignment %stdout% capture

fassignment %conditions% capture

fassignment %lazy% lazy

fassignment %label% label

fassignment %plan% strategy

fassignment %tweak% tweaks

Arguments

x	the name of a future variable, which will hold the value of the future expression (as a promise).
value	An R expression.
envir	The environment from where global objects should be identified.
substitute	If TRUE, argument expr is substitute():ed, otherwise not.
lazy	If FALSE (default), the future is resolved eagerly (starting immediately), otherwise not.
seed	(optional) If TRUE, the random seed, that is, the state of the random number generator (RNG) will be set such that statistically sound random numbers are produced (also during parallelization). If FALSE (default), it is assumed that the future expression does neither need nor use random numbers generation. To use a fixed random seed, specify a L'Ecuyer-CMRG seed (seven integer) or a regular RNG seed (a single integer). If the latter, then a L'Ecuyer-CMRG seed will be automatically created based on the given seed. Furthermore, if FALSE, then the future will be monitored to make sure it does not use random numbers. If it does and depending on the value of option future.rng.onMisuse, the check is ignored, an informative warning, or error will be produced. If seed is NULL, then the effect is as with seed = FALSE but without the RNG check being performed.
globals	(optional) a logical, a character vector, or a named list to control how globals are handled. For details, see section 'Globals used by future expressions' in the help for future().
packages	(optional) a character vector specifying packages to be attached in the R environment evaluating the future.
stdout	If TRUE (default), then the standard output is captured, and re-outputted when value() is called. If FALSE, any output is silenced (by sinking it to the null device as it is outputted). Using stdout = structure(TRUE, drop = TRUE) causes the captured standard output to be dropped from the future object as soon as it has been relayed. This can help decrease the overall memory consumed by captured output across futures. Using stdout = NA fully avoids intercepting the standard output; behavior of such unhandled standard output depends on the future backend.
conditions	A character string of conditions classes to be captured and relayed. The default is to relay all conditions, including messages and warnings. To drop all conditions, use conditions = character(0). Errors are always relayed. Attribute exclude can be used to ignore specific classes, e.g. conditions = structure("condition", exclude = "message") will capture all condition classes except those that inherits from the message class. Using conditions = structure(..., drop = TRUE) causes any captured conditions to be dropped from the future object as soon as it has been relayed, e.g. by value(f). This can help decrease the overall memory consumed by captured conditions across futures. Using conditions = NULL (not recommended) avoids intercepting conditions, except from errors; behavior of such unhandled conditions depends on the future backend and the environment from which R runs.
earlySignal	Specified whether conditions should be signaled as soon as possible or not.
label	A character string label attached to the future.
gc	If TRUE, the garbage collector run (in the process that evaluated the future) only after the value of the future is collected. Exactly when the values are collected may depend on various factors such as number of free workers and whether earlySignal is TRUE (more frequently) or FALSE (less frequently). Some types of futures ignore this argument.
assign.env	The environment to which the variable should be assigned.
fassignment	The future assignment, e.g. x %<-% { expr }.
capture	If TRUE, the standard output will be captured, otherwise not.
strategy	The mechanism for how the future should be resolved. See plan() for further details.
tweaks	A named list (or vector) with arguments that should be changed relative to the current strategy.
...	Additional arguments passed to Future().

Details

For a future created via a future assignment, x %<-% value or futureAssign("x", value), the value is bound to a promise, which when queried will internally call value() on the future and which will then be resolved into a regular variable bound to that value. For example, with future assignment x %<-% value, the first time variable x is queried the call blocks if, and only if, the future is not yet resolved. As soon as it is resolved, and any succeeding queries, querying x will immediately give the value.

The future assignment construct x %<-% value is not a formal assignment per se, but a binary infix operator on objects x and expression value. However, by using non-standard evaluation, this constructs can emulate an assignment operator similar to x <- value. Due to R's precedence rules of operators, future expressions often need to be explicitly bracketed, e.g. x %<-% { a + b }.

Value

futureAssign() and x %<-% expr returns the Future invisibly, e.g. f <- futureAssign("x", expr) and f <- (x %<-% expr).

Adjust future arguments of a future assignment

future() and futureAssign() take several arguments that can be used to explicitly specify what global variables and packages the future should use. They can also be used to override default behaviors of the future, e.g. whether output should be relayed or not. When using a future assignment, these arguments can be specified via corresponding assignment expression. For example, x %<-% { rnorm(10) } %seed% TRUE corresponds to futureAssign("x", { rnorm(10) }, seed = TRUE). Here are a several examples.

To explicitly specify variables and functions that a future assignment should use, use ⁠%globals%⁠. To explicitly specify which packages need to be attached for the evaluate to success, use ⁠%packages%⁠. For example,

> x <- rnorm(1000)
> y %<-% { median(x) } %globals% list(x = x) %packages% "stats"
> y
[1] -0.03956372

The median() function is part of the 'stats' package.

To declare that you will generate random numbers, use ⁠%seed%⁠, e.g.

> x %<-% { rnorm(3) } %seed% TRUE
> x
[1] -0.2590562 -1.2262495  0.8858702

To disable relaying of standard output (e.g. print(), cat(), and str()), while keeping relaying of conditions (e.g. message() and

> x %<-% { cat("Hello\n"); message("Hi there"); 42 } %stdout% FALSE
> y <- 13
> z <- x + y
Hi there
> z
[1] 55

To disable relaying of conditions, use ⁠%conditions%⁠, e.g.

> x %<-% { cat("Hello\n"); message("Hi there"); 42 } %conditions% character(0)
> y <- 13
> z <- x + y
Hello
> z
[1] 55

> x %<-% { print(1:10); message("Hello"); 42 } %stdout% FALSE
> y <- 13
> z <- x + y
Hello
> z
[1] 55

To create a future without launching in such that it will only be processed if the value is really needed, use ⁠%lazy%⁠, e.g.

> x %<-% { Sys.sleep(5); 42 } %lazy% TRUE
> y <- sum(1:10)
> system.time(z <- x + y)
  user  system elapsed 
  0.004   0.000   5.008
> z
[1] 97

Error handling

Because future assignments are promises, errors produced by the the future expression will not be signaled until the value of the future is requested. For example, if you create a future assignment that produce an error, you will not be affected by the error until you "touch" the future-assignment variable. For example,

> x %<-% { stop("boom") }
> y <- sum(1:10)
> z <- x + y
Error in eval(quote({ : boom

Use alternative future backend for future assignment

Futures are evaluated on the future backend that the user has specified by plan(). With regular futures, we can temporarily use another future backend by wrapping our code in ⁠with(plan(...), { ... }]⁠, or temporarily inside a function using with(plan(...), local = TRUE). To achieve the same for a specific future assignment, use ⁠%plan%⁠, e.g.

> plan(multisession)
> x %<-% { 42 }
> y %<-% { 13 } %plan% sequential
> z <- x + y
> z
[1] 55

Here x is resolved in the background via the multisession backend, whereas y is resolved sequentially in the main R session.

Getting the future object of a future assignment

The underlying Future of a future variable x can be retrieved without blocking using f <- futureOf(x), e.g.

> x %<-% { stop("boom") }
> f_x <- futureOf(x)
> resolved(f_x)
[1] TRUE
> x
Error in eval(quote({ : boom
> value(f_x)
Error in eval(quote({ : boom

Technically, both the future and the variable (promise) are assigned at the same time to environment assign.env where the name of the future is ⁠.future_<name>⁠.

future documentation built on April 12, 2025, 1:25 a.m.