How to Install and Uninstall R-parallelly.noarch Package on Fedora 36
Last updated: October 07,2024
1. Install "R-parallelly.noarch" package
This is a short guide on how to install R-parallelly.noarch on Fedora 36
$
sudo dnf update
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$
sudo dnf install
R-parallelly.noarch
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2. Uninstall "R-parallelly.noarch" package
This guide covers the steps necessary to uninstall R-parallelly.noarch on Fedora 36:
$
sudo dnf remove
R-parallelly.noarch
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$
sudo dnf autoremove
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3. Information about the R-parallelly.noarch package on Fedora 36
Last metadata expiration check: 5:15:06 ago on Thu Sep 8 08:04:50 2022.
Available Packages
Name : R-parallelly
Version : 1.30.0
Release : 1.fc36
Architecture : noarch
Size : 320 k
Source : R-parallelly-1.30.0-1.fc36.src.rpm
Repository : fedora
Summary : Enhancing the 'parallel' Package
URL : https://CRAN.R-project.org/package=parallelly
License : LGPLv2+
Description : Utility functions that enhance the 'parallel' package and support the
: built-in parallel backends of the 'future' package. For example,
: availableCores() gives the number of CPU cores available to your R process
: as given by the operating system, 'cgroups' and Linux containers, R
: options, and environment variables, including those set by job schedulers
: on high-performance compute clusters. If none is set, it will fall back to
: parallel::detectCores(). Another example is makeClusterPSOCK(), which is
: backward compatible with parallel::makePSOCKcluster() while doing a better
: job in setting up remote cluster workers without the need for configuring
: the firewall to do port-forwarding to your local computer.
Available Packages
Name : R-parallelly
Version : 1.30.0
Release : 1.fc36
Architecture : noarch
Size : 320 k
Source : R-parallelly-1.30.0-1.fc36.src.rpm
Repository : fedora
Summary : Enhancing the 'parallel' Package
URL : https://CRAN.R-project.org/package=parallelly
License : LGPLv2+
Description : Utility functions that enhance the 'parallel' package and support the
: built-in parallel backends of the 'future' package. For example,
: availableCores() gives the number of CPU cores available to your R process
: as given by the operating system, 'cgroups' and Linux containers, R
: options, and environment variables, including those set by job schedulers
: on high-performance compute clusters. If none is set, it will fall back to
: parallel::detectCores(). Another example is makeClusterPSOCK(), which is
: backward compatible with parallel::makePSOCKcluster() while doing a better
: job in setting up remote cluster workers without the need for configuring
: the firewall to do port-forwarding to your local computer.