crew0.10.2 package

A Distributed Worker Launcher Framework

crew_assert

Crew assertion

crew_async

Local asynchronous client object.

crew_class_async

R6 async class.

crew_class_client

R6 client class.

crew_class_controller_group

Controller group class

crew_class_controller

Controller class

crew_class_launcher_local

Local process launcher class

crew_class_launcher

Launcher abstract class

crew_class_monitor_local

Local monitor class

crew_class_relay

R6 relay class.

crew_class_throttle

R6 throttle class.

crew_class_tls

R6 TLS class.

crew_clean

Terminate dispatchers and/or workers

crew_client

Create a client object.

crew_controller_group

Create a controller group.

crew_controller_local

Create a controller with a local process launcher.

crew_controller

Create a controller object from a client and launcher.

crew_deprecate

Deprecate a crew feature.

crew_eval_async

Run an asynchronous task in the crew launcher.

crew_eval

Evaluate an R command and return results as a monad.

crew_launcher_local

Create a launcher with local process workers.

crew_launcher

Create an abstract launcher.

crew_monitor_local

Create a local monitor object.

crew_options_local

Local crew launcher options.

crew_options_metrics

Options for logging resource usage metrics.

crew_random_name

Random name

crew_relay

Create a crew relay object.

crew_retry

Retry code.

crew_terminate_process

Manually terminate a local process.

crew_terminate_signal

Get the termination signal.

crew_throttle

Create a stateful throttling object.

crew_tls

Configure TLS.

crew_worker

Crew worker.

crew-package

crew: a distributed worker launcher framework

reexports

Objects exported from other packages

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>.

  • Maintainer: William Michael Landau
  • License: MIT + file LICENSE
  • Last published: 2024-11-15