R package ‘futureverse’ - Install ‘Futureverse’ in One Go

The Futureverse is a unifying framework for parallelization and distributed processing in R. This package, futureverse, is a utility wrapper package that makes it easy to install most common Futureverse packages in one go.

TL;DR

Start by configuring Futureverse to parallelize on the current computer:

future::plan(future::multisession)

After this, all it takes is a minor tweak to make your existing lapply(), map(), or foreach() code to run in parallel, e.g.

library(futurize)

## Sequential and parallel version of base R apply
y <- lapply(X, slow_fcn)
y <- lapply(X, slow_fcn) |> futurize()

## Sequential and parallel version of purrr map
library(purrr)
y <- X |> map(slow_fcn)
y <- X |> map(slow_fcn) |> futurize()

## Sequential and parallel version of foreach
library(foreach)
y <- foreach(x = X) %do% slow_fcn(x)
y <- foreach(x = X) %do% slow_fcn(x) |> futurize()

Installation

Call:

install.packages("futureverse")

to install:

• future - the core Futureverse package
• futurize - the one-stop map-reduce package
• future.apply - Futureverse variants of base-R apply functions
• furrr - Futureverse variants of purrr apply functions
• doFuture - Futureverse adaptors for the foreach package
• progressr - Near-live progress updates when using Futureverse

Call:

install.packages("futureverse", dependencies = TRUE)

to install also additional parallel backends:

• future.mirai - a modern alternative to built-in plan(multisession)
• future.callr - a memory efficient alternative to built-in plan(multisession)
• future.batchtools - parallelize on HPC job schedulers; Load Sharing Facility (LSF), OpenLava, TORQUE/PBS, Sun/Son of/Oracle/Univa/Altair Grid Engine (SGE), Slurm

Want to learn more?

• Tutorials and Workshops: https://www.futureverse.org/tutorials.html
• Blog: https://www.futureverse.org/blog.html
• Publications: https://www.futureverse.org/publications.html
• Support: https://github.com/orgs/futureverse/discussions