pins: Pin, Discover and Share Resources

Pin remote resources into a local cache to work offline, improve speed and avoid recomputing; discover and share resources in local folders, 'GitHub', 'Kaggle' or 'RStudio Connect'. Resources can be anything from 'CSV', 'JSON', or image files to arbitrary R objects.

Version: 0.4.4
Depends: R (≥ 3.2.0)
Imports: backports, base64enc, crayon, digest, filelock, fs, httr, jsonlite, magrittr, mime, openssl, rappdirs, stats, withr, yaml, zip
Suggests: callr, covr, data.table, knitr, rmarkdown, R6, stringi, tibble, testthat, xml2
Published: 2020-10-30
Author: Javier Luraschi [aut, cre], RStudio [cph]
Maintainer: Javier Luraschi <javier at>
License: Apache License 2.0
NeedsCompilation: no
Materials: README NEWS
CRAN checks: pins results


Reference manual: pins.pdf
Vignettes: Versioning
Using Azure Boards
Using DigitalOcean Boards
Extending Board
Using Google Cloud Boards
Using GitHub Boards
Using Kaggle Boards
Using RStudio Connect Boards
Using S3 Boards
Understanding Boards
Using Website Boards
Extending Pins
Using Pins in RStudio
Getting Started
Package source: pins_0.4.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: pins_0.4.4.tgz, r-oldrel: pins_0.4.4.tgz
Old sources: pins archive

Reverse dependencies:

Reverse imports: BFS, connections, polyglot
Reverse suggests: tfhub


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