wlandau-lilly/drake: A Pipeline Toolkit for Reproducible Computation at Scale

A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://docs.ropensci.org/drake/> and the online manual <https://ropenscilabs.github.io/drake-manual/>.

Getting started

Package details

URL https://github.com/ropensci/drake https://docs.ropensci.org/drake https://github.com/ropenscilabs/drake-manual
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
wlandau-lilly/drake documentation built on Oct. 23, 2019, 6:46 a.m.