Dynamic Function-Oriented 'Make'-Like Declarative Workflows

As a pipeline toolkit for Statistics and data science in R, the 'targets' package brings together function-oriented programming and 'Make'-like declarative workflows. It analyzes the dependency relationships among the tasks of a workflow, skips steps that are already up to date, runs the necessary computation with optional parallel workers, abstracts files as R objects, and provides tangible evidence that the results match the underlying code and data. The methodology in this package borrows from GNU 'Make' (2015, ISBN:978-9881443519) and 'drake' (2018, ).


Reference manual

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0.2.0 by William Michael Landau, 2 days ago

https://docs.ropensci.org/targets/, https://github.com/ropensci/targets

Report a bug at https://github.com/ropensci/targets/issues

Browse source code at https://github.com/cran/targets

Authors: William Michael Landau [aut, cre] , Matthew T. Warkentin [ctb] , Samantha Oliver [rev] , Tristan Mahr [rev] , Eli Lilly and Company [cph]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports callr, cli, codetools, data.table, digest, igraph, R6, rlang, stats, tibble, tidyselect, utils, vctrs, withr

Suggests aws.s3, bs4Dash, clustermq, curl, dplyr, fst, future, gt, keras, knitr, rmarkdown, pingr, pkgload, qs, rstudioapi, shiny, shinycssloaders, shinyWidgets, testthat, torch, usethis, visNetwork

Imported by tarchetypes.

See at CRAN