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r-cran-progressr package

r-cran-progressr 0.11.0-1 source package in Ubuntu

Changelog

r-cran-progressr (0.11.0-1) unstable; urgency=medium

  * New upstream version
  * Reorder sequence of d/control fields by cme (routine-update)
  * lintian-overrides for source-is-missing

 -- Andreas Tille <email address hidden>  Thu, 15 Sep 2022 16:17:41 +0200

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

Lunar: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
r-cran-progressr_0.11.0-1.dsc 2.1 KiB 45eca3c50a244b16d7583d57e8d37f7a5d0f7fd05e53c0be4cd668c6ece0842b
r-cran-progressr_0.11.0.orig.tar.gz 109.5 KiB d8668c82348a20cca34bb18c0c94e6083dbb6dbea40615e07e4161aff7366cd9
r-cran-progressr_0.11.0-1.debian.tar.xz 2.9 KiB 0139a28821efa48f419d7fb695e1cc6c41fd50830d950dc4a903e3825cd8d617

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.