Package: crew 0.9.5

William Michael Landau

crew: A Distributed Worker Launcher Framework

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>.

Authors:William Michael Landau [aut, cre], Daniel Woodie [ctb], Eli Lilly and Company [cph]

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NEWS

Peer review:

Bug tracker:https://github.com/wlandau/crew/issues

On CRAN:

high-performance-computing

41 exports 105 stars 4.85 score 24 dependencies 2 dependents 2.2k downloads

Last updated 9 days agofrom:8ca02085fb (via 0.9.5)

Exports:all_ofany_ofcontainscrew_assertcrew_asynccrew_class_asynccrew_class_clientcrew_class_controllercrew_class_controller_groupcrew_class_launchercrew_class_launcher_localcrew_class_monitor_localcrew_class_relaycrew_class_throttlecrew_class_tlscrew_cleancrew_clientcrew_controllercrew_controller_groupcrew_controller_localcrew_deprecatecrew_evalcrew_eval_asynccrew_launchercrew_launcher_localcrew_monitor_localcrew_random_namecrew_relaycrew_retrycrew_terminate_processcrew_terminate_signalcrew_throttlecrew_tlscrew_workerends_witheverythinglast_colmatchesnum_rangeone_ofstarts_with

Dependencies:clidata.tablefansifastmapgetipgluelaterlifecyclemagrittrmirainanonextpillarpkgconfigprocessxpromisespsR6Rcpprlangtibbletidyselectutf8vctrswithr