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crew (version 0.5.0)

A Distributed Worker Launcher Framework

Description

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) 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) , 'rrq' by FitzJohn and Ashton (2023) , 'clustermq' by Schubert (2019) ), and 'batchtools' by Lang, Bischel, and Surmann (2017) .

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Install

install.packages('crew')

Monthly Downloads

2,294

Version

0.5.0

License

MIT + file LICENSE

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Last Published

September 18th, 2023

Functions in crew (0.5.0)

crew_class_tls

R6 TLS class.
crew_class_controller_group

Controller group class
crew_class_client

R6 client class.
crew-package

crew: a distributed worker launcher framework
crew_class_launcher

Launcher abstract class
crew_clean

Terminate dispatchers and/or workers
crew_class_controller

Controller class
crew_class_launcher_local

Local process launcher class
crew_class_schedule

Schedule class
crew_assert

Crew assertion
crew_client

Create a client object.
crew_controller

Create a controller object from a client and launcher.
crew_controller_group

Create a controller group.
crew_controller_local

Create a controller with a local process launcher.
crew_launcher_local

Create a launcher with local process workers.
crew_launcher

Create an abstract launcher.
crew_random_name

Random name
crew_retry

Retry code.
crew_deprecate

Deprecate a crew feature.
crew_worker

Crew worker.
reexports

Objects exported from other packages
crew_eval

Evaluate an R command and return results as a monad.
crew_schedule

Create a schedule for bookkeeping tasks.
crew_tls

Configure TLS.