A Distributed Worker Launcher Framework R package crew version 1.3.2 CRAN Task View: HighPerformanceComputing (https://CRAN.R-project.org/view=HighPerformanceComputing) In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The 'NNG'-powered 'mirai' R package by Gao (2023) <doi:10.5281/zenodo.7912722> is a sleek and sophisticated scheduler that efficiently processes these intense workloads. The 'crew' package extends 'mirai' with a unifying interface for third-party worker launchers. Inspiration also comes from packages. 'future' by Bengtsson (2021) <doi:10.32614/RJ-2021-048>, 'rrq' by FitzJohn and Ashton (2023) <https://github.com/mrc-ide/rrq>, 'clustermq' by Schubert (2019) <doi:10.1093/bioinformatics/btz284>), and 'batchtools' by Lang, Bischel, and Surmann (2017) <doi:10.21105/joss.00135>. Software Depends: R (>= 4.0.0) Imports: cli (>= 3.1.0), collections (>= 0.3.9), data.table, later, mirai (>= 2.7.0), nanonext (>= 1.9.0), processx, promises, ps, R6, rlang, stats, tibble, tidyselect, tools, utils Suggests: autometric (>= 0.1.0), knitr, markdown (>= 1.1), rmarkdown, testthat (>= 3.0.0) William Michael Landau <will.landau.oss@gmail.com> Comprehensive R Archive Network (CRAN) William Michael Landau [aut, cre] (ORCID: <https://orcid.org/0000-0003-1878-3253>), Daniel Woodie [ctb], Eli Lilly and Company [cph, fnd] MIT + file LICENSE (https://CRAN.R-project.org/package=crew/LICENSE) 2026-07-30 application/tgz https://CRAN.R-project.org/package=crew doi:10.32614/CRAN.package.crew en-US