future: Unified Parallel and Distributed Processing in R for Everyone

The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use 'x %<-% { expression }' with 'plan(multisession)'. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers, etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.

Version:	1.34.0
Imports:	digest, globals (≥ 0.16.1), listenv (≥ 0.8.0), parallel, parallelly (≥ 1.38.0), utils
Suggests:	methods, RhpcBLASctl, R.rsp, markdown
Published:	2024-07-29
DOI:	10.32614/CRAN.package.future
Author:	Henrik Bengtsson [aut, cre, cph]
Maintainer:	Henrik Bengtsson <henrikb at braju.com>
BugReports:	https://github.com/HenrikBengtsson/future/issues
License:	LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2.1)]
URL:	https://future.futureverse.org, https://github.com/HenrikBengtsson/future
NeedsCompilation:	no
Citation:	future citation info
Materials:	NEWS
In views:	HighPerformanceComputing
CRAN checks:	future results

Documentation:

Reference manual:

future.pdf

Vignettes:

A Future for R: A Comprehensive Overview A Future for R: Text and Message Output A Future for R: Future Topologies A Future for R: Common Issues with Solutions A Future for R: Non-Exportable Objects A Future for R: Controlling Default Future Strategy A Future for R: Future API Backend Specification A Future for R: Best Practices for Package Developers A Future for R: How the Future Framework is Validated

Downloads:

Package source:	future_1.34.0.tar.gz
Windows binaries:	r-devel: future_1.34.0.zip, r-release: future_1.34.0.zip, r-oldrel: future_1.34.0.zip
macOS binaries:	r-release (arm64): future_1.34.0.tgz, r-oldrel (arm64): future_1.34.0.tgz, r-release (x86_64): future_1.34.0.tgz, r-oldrel (x86_64): future_1.34.0.tgz
Old sources:	future archive

Reverse dependencies:

Reverse depends:	doFuture, eCV, furrr, future.apply, future.batchtools, future.callr, future.mirai, isopam, MAMS, rpm, SCtools, spatialwarnings, spFSR
Reverse imports:	AICcPermanova, ale, alookr, amadeus, antaresEditObject, aroma.affymetrix, aroma.core, ARPALData, bamm, BatchGetSymbols, bayesmove, bbknnR, BEKKs, bigDM, bistablehistory, bkmrhat, brms, bspcov, CAESAR.Suite, calmr, campsis, cccrm, ceRNAnetsim, cft, chatAI4R, civis, clickR, Clustering, ClustIRR, codalm, codebook, conformalInference.fd, conformalInference.multi, Coxmos, CSCNet, cSEM, CSGo, dartR.popgen, delayed, deseats, dipsaus, disk.frame, DQAstats, drimmR, ecic, EFAtools, EGAnet, elevatr, envi, epe4md, epitweetr, erah, esemifar, FAMoS, fect, fiery, FLAMES, flowGraph, flowml, fst4pg, funGp, future.tests, futureverse, fxTWAPLS, GeDS, genBaRcode, GeoModels, GetBCBData, googleComputeEngineR, googleTagManageR, GPCsign, greatR, greed, greta, gsynth, gtfs2gps, gWQS, hbamr, heterogen, hoopR, hwep, idmodelr, iml, incubate, infercnv, InPAS, interflex, ivDiag, JointAI, kernelboot, kmeRtone, LandComp, latentcor, lavaangui, ldaPrototype, lmtp, LTFHPlus, LWFBrook90R, MAI, mbbe, mcp, metaGE, migraph, mlr3, mplusParallel.automation, mrgsim.parallel, multilevelcoda, multilevelmediation, multitool, nebula, netShiny, NetSimR, nflfastR, nflseedR, nixtlar, OOS, optimLanduse, origami, paramsim, parseRPDR, pGRN, pgxRpi, PINstimation, PLNmodels, POMADE, powRICLPM, ProFAST, Prostar, proteus, psborrow2, PSCBS, PUMP, QBMS, qgcomp, qgcompint, rangeMapper, rBiasCorrection, readsdr, rechaRge, refineR, remiod, restriktor, RTransferEntropy, rTwig, s3fs, saeczi, sampcompR, scDiffCom, sctransform, seer, segtest, Seurat, SeuratObject, sharp, sigminer, Signac, signeR, SimDesign, simIDM, simtrial, skewlmm, skpr, SmCCNet, smoots, sNPLS, sovereign, sparrpowR, SPARSEMODr, spatialTIME, spdesign, specr, sperrorest, sphunif, spStack, stacks, startR, steps, survstan, synergyfinder, tableschema.r, TaxaNorm, tealeaves, tenm, text, tglkmeans, tidyMC, tipmap, TKCat, tramvs, TreeMineR, TreeSearch, TriDimRegression, tsdistributions, tsfeatures, tsgarch, tune, uci, updog, vmeasur, webdeveloper, WeightedCluster, whitewater, winputall, wru, yfR
Reverse suggests:	altdoc, apsimx, BAMBI, baseballr, batchtools, bayesian, bcmaps, bhmbasket, bsitar, bslib, canaper, ChromSCape, collinear, crossmap, cvasi, cvCovEst, dar, dataquieR, DeclareDesign, dispositionEffect, drake, DT, easyalluvial, EpiForsk, EpiNow2, ezcox, fabletools, fastRhockey, fdacluster, fdWasserstein, finbif, fitlandr, fmeffects, fundiversity, geocmeans, googlePubsubR, gstat, GSVA, hacksig, hal9001, haldensify, httpgd, hydroloom, imagefluency, inlinedocs, ipc, ivmte, jlmerclusterperm, jstor, JuliaConnectoR, ldsr, lemna, lgr, lidR, maestro, manynet, mapme.biodiversity, marginaleffects, mice, mikropml, MineICA, missSBM, mistyR, mlr3db, mlr3pipelines, mlr3resampling, mlr3spatial, mlr3torch, mlr3tuning, modelsummary, momentuHMM, mslp, multiverse, nfl4th, nhdplusTools, nncc, oncomsm, partR2, pbapply, PeakSegDisk, penaltyLearning, photosynthesis, plumber, portvine, progressr, projpred, promises, protti, pseudohouseholds, QDNAseq, RAINBOWR, Rcurvep, receptiviti, regmedint, reproducible, reval, rgee, robust2sls, sapfluxnetr, SCArray.sat, SCdeconR, sdmTMB, semPower, semtree, sentopics, shiny, simglm, simhelpers, sims, sits, SpaDES.core, spaMM, squat, ssdtools, targets, templr, txshift, UCSCXenaShiny, vital, wildmeta, wingen, xegaPopulation
Reverse enhances:	scRNAseqApp

Linking:

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