% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/zzz.plan.R
\name{plan}
\alias{plan}
\title{Plan how to resolve a future}
\usage{
plan(
  strategy = NULL,
  ...,
  substitute = TRUE,
  .skip = FALSE,
  .call = TRUE,
  .cleanup = TRUE,
  .init = TRUE
)
}
\arguments{
\item{strategy}{The evaluation function (or name of it) to use
for resolving a future. If \code{NULL}, then the current strategy is returned.}

\item{\dots}{Additional arguments overriding the default arguments
of the evaluation function.  Which additional arguments are supported
depends on what evaluation function is used, e.g. several support
argument \code{workers} but not all. For details, see the individual
functions of which some are linked to below.}

\item{substitute}{If \code{TRUE}, the \code{strategy} expression is
\code{substitute()}:d, otherwise not.}

\item{.skip}{(internal) If \code{TRUE}, then attempts to set a strategy
that is the same as what is currently in use, will be skipped.}

\item{.call}{(internal) Used for recording the call to this function.}

\item{.cleanup}{(internal) Used to stop implicitly started clusters.}

\item{.init}{(internal) Used to initiate workers.}
}
\value{
If a new strategy is chosen, then the previous one is returned
(invisible), otherwise the current one is returned (visibly).
}
\description{
This function allows \emph{the user} to plan the future, more specifically,
it specifies how \code{\link[=future]{future()}}:s are resolved,
e.g. sequentially or in parallel.
}
\details{
The default strategy is \code{\link{sequential}}, but the default can be
configured by option \option{future.plan} and, if that is not set,
system environment variable \env{R_FUTURE_PLAN}.
To reset the strategy back to the default, use \code{plan("default")}.
}
\section{Built-in evaluation strategies}{

The \pkg{future} package provides the following built-in backends:

\describe{
\item{\code{\link{sequential}}:}{
Resolves futures sequentially in the current \R process, e.g.
\code{plan(sequential)}.
}
\item{\code{\link{multisession}}:}{
Resolves futures asynchronously (in parallel) in separate
\R sessions running in the background on the same machine, e.g.
\code{plan(multisession)} and \code{plan(multisession, workers = 2)}.
}
\item{\code{\link{multicore}}:}{
Resolves futures asynchronously (in parallel) in separate
\emph{forked} \R processes running in the background on
the same machine, e.g.
\code{plan(multicore)} and \code{plan(multicore, workers = 2)}.
This backend is not supported on Windows.
}
\item{\code{\link{cluster}}:}{
Resolves futures asynchronously (in parallel) in separate
\R sessions running typically on one or more machines, e.g.
\code{plan(cluster)}, \code{plan(cluster, workers = 2)}, and
\code{plan(cluster, workers = c("n1", "n1", "n2", "server.remote.org"))}.
}
}

Other package provide additional evaluation strategies.
For example, the \pkg{future.callr} package implements an alternative
to the \code{multisession} backend on top of the \pkg{callr} package, e.g.
\code{plan(future.callr::callr, workers = 2)}.
Another example is the \pkg{future.batchtools} package, which implements,
on top of the \pkg{batchtools} package, e.g.
\code{plan(future.batchtools::batchtools_slurm)}.
These types of futures are resolved via job schedulers, which typically
are available on high-performance compute (HPC) clusters, e.g. LSF,
Slurm, TORQUE/PBS, Sun Grid Engine, and OpenLava.

To "close" any background workers (e.g. \code{multisession}), change
the plan to something different; \code{plan(sequential)} is recommended
for this.
}

\section{For package developers}{

Please refrain from modifying the future strategy inside your packages /
functions, i.e. do not call \code{plan()} in your code. Instead, leave
the control on what backend to use to the end user. This idea is part of
the core philosophy of the future framework---as a developer you can never
know what future backends the user have access to. Moreover, by not making
any assumptions about what backends are available, your code will also work
automatically with any new backends developed after you wrote your code.

If you think it is necessary to modify the future strategy within a
function, then make sure to undo the changes when exiting the function.
This can be done using:

\preformatted{
  oplan <- plan(new_set_of_strategies)
  on.exit(plan(oplan), add = TRUE)
  [...]
}

This is important because the end-user might have already set the future
strategy elsewhere for other purposes and will most likely not known that
calling your function will break their setup.
\emph{Remember, your package and its functions might be used in a greater
context where multiple packages and functions are involved and those might
also rely on the future framework, so it is important to avoid stepping on
others' toes.}
}

\section{Using plan() in scripts and vignettes}{

When writing scripts or vignettes that use futures, try to place any
call to \code{plan()} as far up (i.e. as early on) in the code as possible.
This will help users to quickly identify where the future plan is set up
and allow them to modify it to their computational resources.
Even better is to leave it to the user to set the \code{plan()} prior to
\code{source()}:ing the script or running the vignette.
If a \file{\link{.future.R}} exists in the current directory and / or in
the user's home directory, it is sourced when the \pkg{future} package is
\emph{loaded}. Because of this, the \file{.future.R} file provides a
convenient place for users to set the \code{plan()}.
This behavior can be controlled via an \R option---see
\link[future:future.options]{future options} for more details.
}

\examples{
a <- b <- c <- NA_real_

# An sequential future
plan(sequential)
f <- future({
  a <- 7
  b <- 3
  c <- 2
  a * b * c
})
y <- value(f)
print(y)
str(list(a = a, b = b, c = c)) ## All NAs


# A sequential future with lazy evaluation
plan(sequential)
f <- future({
  a <- 7
  b <- 3
  c <- 2
  a * b * c
}, lazy = TRUE)
y <- value(f)
print(y)
str(list(a = a, b = b, c = c)) ## All NAs


# A multicore future (specified as a string)
plan("multicore")
f <- future({
  a <- 7
  b <- 3
  c <- 2
  a * b * c
})
y <- value(f)
print(y)
str(list(a = a, b = b, c = c)) ## All NAs

## Multisession futures gives an error on R CMD check on
## Windows (but not Linux or macOS) for unknown reasons.
## The same code works in package tests.
\donttest{

# A multisession future (specified via a string variable)
plan("future::multisession")
f <- future({
  a <- 7
  b <- 3
  c <- 2
  a * b * c
})
y <- value(f)
print(y)
str(list(a = a, b = b, c = c)) ## All NAs

}


## Explicitly specifying number of workers
## (default is parallelly::availableCores())
plan(multicore, workers = 2)
message("Number of parallel workers: ", nbrOfWorkers())


## Explicitly close multisession workers by switching plan
plan(sequential)
}
