crew: A Distributed Worker Launcher Framework (original) (raw)

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>.

Version:	0.10.0
Depends:	R (≥ 4.0.0)
Imports:	autometric, cli (≥ 3.1.0), data.table, getip, later, mirai (≥ 1.3.0), nanonext (≥ 1.3.0), processx, promises, ps, R6, rlang, stats, tibble, tidyselect, tools, utils
Suggests:	knitr (≥ 1.30), markdown (≥ 1.1), rmarkdown (≥ 2.4), testthat (≥ 3.0.0)
Published:	2024-10-11
DOI:	10.32614/CRAN.package.crew
Author:	William Michael Landau [aut, cre], Daniel Woodie [ctb], Eli Lilly and Company [cph, fnd]
Maintainer:	William Michael Landau <will.landau.oss at gmail.com>
BugReports:	https://github.com/wlandau/crew/issues
License:	MIT + file
URL:	https://wlandau.github.io/crew/, https://github.com/wlandau/crew
NeedsCompilation:	no
Language:	en-US
Materials:	NEWS
In views:	HighPerformanceComputing
CRAN checks:	crew results

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