How to Install and Uninstall r-cran-rcppparallel Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 19,2024

1. Install "r-cran-rcppparallel" package

This guide covers the steps necessary to install r-cran-rcppparallel on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                r-cran-rcppparallel
            
                    
    
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2. Uninstall "r-cran-rcppparallel" package

This is a short guide on how to uninstall r-cran-rcppparallel on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-rcppparallel
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-rcppparallel package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-rcppparallel
Architecture: amd64
Version: 5.0.2+dfsg-3
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 263
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, libc6 (>= 2.4), libgcc-s1 (>= 3.0), libstdc++6 (>= 4.1.1), libtbb2 (>= 2017~U7), libtbb-dev
Recommends: r-cran-runit, r-cran-rcpp
Suggests: r-cran-knitr, r-cran-rmarkdown
Filename: pool/universe/r/r-cran-rcppparallel/r-cran-rcppparallel_5.0.2+dfsg-3_amd64.deb
Size: 103444
MD5sum: 6091fdf82a80169426900d8cb72a41ed
SHA1: c7b95e9ce6c37da7075299664d820585995ff25f
SHA256: effdb9cda805b2a78cdb34ae51751b5c9accfb78add149a6ca2225bc61550740
SHA512: a7d434d460d5512c03b11e42049bb2d34bbc1bc6ec8521cbd5d19359c3735192096d5d6b1d059e1149c05163d4a7c7703b79acdb74149d524e93ba760a098f11
Homepage: https://cran.r-project.org/package=RcppParallel
Description-en: parallel programming tools for Rcpp
High level functions for parallel programming with 'Rcpp' (GNU R).
For example, the 'parallelFor()' function can be used to convert the work of
a standard serial "for" loop into a parallel one and the 'parallelReduce()'
function can be used for accumulating aggregate or other values.
Description-md5: 33e0e1ca6e4cd7102cb489dac22b3502