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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Parallelize Common Functions via One Magic Function</dc:title>
  <dc:title>R package futurize version 1.0.0</dc:title>
  <dc:subject>CRAN Task View: HighPerformanceComputing (https://CRAN.R-project.org/view=HighPerformanceComputing)</dc:subject>
  <dc:description>The futurize() function turns sequential map-reduce functions such as base::lapply(), purrr::map(), 'foreach::foreach() %do% { ... }' into concurrent alternatives, providing you with a simple, straightforward path to scalable parallel computing via the 'future' ecosystem &lt;doi:10.32614/RJ-2021-048&gt;. By combining this transpiler function with R's native pipe operator, you have a convenient way for speeding up iterative computations with minimal refactoring, e.g. 'lapply(xs, fcn) |&gt; futurize()', 'purrr::map(xs, fcn) |&gt; futurize()', and 'foreach::foreach(x = xs) %do% { fcn(x) } |&gt; futurize()'. Other map-reduce packages that can be "futurized" are 'BiocParallel', 'plyr', 'crossmap', 'pbapply' packages. There is also support for a growing set of domain-specific packages on CRAN (e.g. 'boot', 'caret', 'DiceKriging', 'ez', 'fgsea', 'fwb', 'gamlss', 'glmmTMB', 'glmnet', 'kernelshap', 'lme4', 'metafor', 'mgcv', 'modelsummary', 'parameters', 'partykit', 'pls', 'pvclust', 'riskRegression', 'rugarch', 'sandwich', 'seriation', 'shapr', 'Sim.DiffProc', 'SimDesign', 'stars', 'strucchange', 'SuperLearner', 'tm', 'TSP', and 'vegan') and on Bioconductor (e.g. 'DESeq2', 'GenomicAlignments', 'GSVA', 'Rsamtools', 'scater', 'scuttle', 'SingleCellExperiment', and 'sva').</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.1.0), future (&gt;= 1.69.0)</dc:relation>
  <dc:relation>Imports: utils</dc:relation>
  <dc:relation>Suggests: methods, future.apply (&gt;= 1.20.2), foreach, doFuture (&gt;=
1.2.1), purrr, furrr, crossmap, plyr, pbapply, BiocParallel,
boot, survival, caret, randomForest, DESeq2, DiceKriging, ez,
fgsea, GenomicAlignments, Rsamtools, fwb, gamlss, glmmTMB,
glmnet, GSVA, kernelshap, lme4, metafor, mgcv, modelsummary,
parameters (&gt;= 0.29.1), partykit, pls, pvclust, riskRegression,
rugarch, sandwich, scater, scuttle, seriation, shapr,
Sim.DiffProc, SimDesign, SingleCellExperiment, stars,
strucchange, SuperLearner, sva, tm, vegan, tools, commonmark,
base64enc</dc:relation>
  <dc:creator>Henrik Bengtsson &lt;henrikb@braju.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Henrik Bengtsson [aut, cre, cph] (ORCID:
    &lt;https://orcid.org/0000-0002-7579-5165&gt;)</dc:contributor>
  <dc:rights>Apache License (&gt;= 2)</dc:rights>
  <dc:date>2026-06-12</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=futurize</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.futurize</dc:identifier>
  <dc:language>en-US</dc:language>
</oai_dc:dc>
