Ubuntu
r-cran-progressr package

r-cran-progressr 0.10.1-1 source package in Ubuntu

Changelog

r-cran-progressr (0.10.1-1) unstable; urgency=medium

  * Team upload.
  * New upstream version 0.10.1
  * Bump Standards-Version to 4.6.1 (no changes needed)

 -- Nilesh Patra <email address hidden>  Thu, 09 Jun 2022 08:25:49 +0530

Upload details

Uploaded by:
Debian R Packages Maintainers
Uploaded to:
Sid
Original maintainer:
Debian R Packages Maintainers
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Builds

Kinetic: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
r-cran-progressr_0.10.1-1.dsc 2.1 KiB 49c37e29d7c02217c205ba6b7d18dc7da6b8bfe09fdd779b94cef1d1e187edc7
r-cran-progressr_0.10.1.orig.tar.gz 107.4 KiB 39d71db6e654af5534bc2db909b459329f6f8a9d61a252f9a1bc9469eada6c4b
r-cran-progressr_0.10.1-1.debian.tar.xz 2.8 KiB 41fba921445b0a9ed4950abc0d8947d90199a84b9aa02ce25a5232491d02eb89

Available diffs

No changes file available.

Binary packages built by this source

r-cran-progressr: GNU R inclusive, unifying API for progress updates

 A minimal, unifying API for scripts and packages to report progress
 updates from anywhere including when using parallel processing. The
 package is designed such that the developer can to focus on what
 progress should be reported on without having to worry about how to
 present it. The end user has full control of how, where, and when to
 render these progress updates, e.g. in the terminal using
 utils::txtProgressBar() or progress::progress_bar(), in a graphical user
 interface using utils::winProgressBar(), tcltk::tkProgressBar() or
 shiny::withProgress(), via the speakers using beep::beepr(), or on a
 file system via the size of a file. Anyone can add additional,
 customized, progression handlers. The 'progressr' package uses R's
 condition framework for signaling progress updated. Because of this,
 progress can be reported from almost anywhere in R, e.g. from classical
 for and while loops, from map-reduce APIs like the lapply() family of
 functions, 'purrr', 'plyr', and 'foreach'. It will also work with
 parallel processing via the 'future' framework, e.g.
 future.apply::future_lapply(), furrr::future_map(), and 'foreach' with
 'doFuture'. The package is compatible with Shiny applications.