Imports: codetools, evaluate, digest, dplyr, formatR, fs, igraph,
0.2.0), stats, storr (>= 1.1.0), stringi, tibble, tidyselect
Suggests: abind, bindr, callr, clustermq, crayon, DBI, downloader,
future, future.apply, grDevices, ggplot2, ggraph, knitr,
lubridate, MASS, methods, networkD3, RSQLite, rprojroot,
testthat, txtq, rmarkdown, styler, visNetwork, webshot

Imports: codetools, digest, dplyr, evaluate, formatR, fs, future,
igraph, magrittr, parallel, pkgconfig, purrr, R6, R.utils,
rlang (>= 0.2.0), stats, storr (>= 1.1.0), stringi, tibble,
Suggests: abind, bindr, callr, clustermq, CodeDepends, crayon, DBI,
downloader, future.apply, grDevices, ggplot2, ggraph, knitr,
lubridate, MASS, methods, networkD3, prettycode, RSQLite,
rprojroot, testthat, txtq, rmarkdown, styler, visNetwork,

Author: William Michael Landau [aut, cre]

there is native support for parallel and distributed computing,
Imports: codetools, digest, formatR, igraph, methods, pkgconfig, rlang
Suggests: abind, bindr, callr, clustermq, CodeDepends, crayon,
datasets, DBI, downloader, future, future.apply, grDevices,
ggplot2, ggraph, knitr, lubridate, networkD3, parallel,
prettycode, RSQLite, stats, testthat, tidyselect (>= 0.2.4),
txtq, rmarkdown, styler, visNetwork, webshot

Imports: base64url, digest, igraph, methods, rlang (>= 0.2.0), storr
Suggests: abind, bindr, callr, clustermq, CodeDepends, crayon, curl,
datasets, downloader, future, grDevices, ggplot2, ggraph,
knitr, lubridate, networkD3, parallel, prettycode, stats,
testthat, tibble, tidyselect (>= 0.2.4), rmarkdown, styler,

Suggests: abind, bindr, callr, cli, clustermq, CodeDepends, crayon,
curl, datasets, downloader, future, ggplot2, ggraph, grDevices,
knitr, lubridate, networkD3, parallel, prettycode, Rcpp,
rmarkdown, rstudioapi, stats, styler, testthat, tibble,
tidyselect (>= 0.2.4), usethis, visNetwork, webshot

Description: 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
Imports: base64url, digest, igraph, methods, parallel, rlang (>=
Suggests: abind, bindr, callr, cli (>= 1.1.0), clustermq (>= 0.8.8),
crayon, curl (>= 2.7), data.table, datasets, disk.frame,
downloader, fst, future, ggplot2, ggraph, grDevices, keras,
knitr, lubridate, networkD3, prettycode, qs (>= 0.20.2), Rcpp,
rmarkdown, rstudioapi, stats, styler (>= 1.2.0), testthat (>=
2.1.0), tibble, tidyselect (>= 0.2.4), txtplot, usethis,