How to Install and Uninstall R-future.noarch Package on Fedora 39

Last updated: October 12,2024

1. Install "R-future.noarch" package

This guide covers the steps necessary to install R-future.noarch on Fedora 39


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                R-future.noarch
            
                    
    
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2. Uninstall "R-future.noarch" package

Please follow the guidance below to uninstall R-future.noarch on Fedora 39:


    
        
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                sudo dnf remove
            
                        
                R-future.noarch
            
                    
    
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            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the R-future.noarch package on Fedora 39

Last metadata expiration check: 2:45:50 ago on Thu Mar 7 17:44:52 2024.
Available Packages
Name : R-future
Version : 1.32.0
Release : 3.fc39
Architecture : noarch
Size : 698 k
Source : R-future-1.32.0-3.fc39.src.rpm
Repository : fedora
Summary : Unified Parallel and Distributed Processing in R for Everyone
URL : https://CRAN.R-project.org/package=future
License : LGPL-2.1-or-later
Description : The purpose of this package is to provide a lightweight and unified Future
: API for sequential and parallel processing of R expression via futures.
: The simplest way to evaluate an expression in parallel is to use `x %<-% {
: expression }` with `plan(multisession)`. This package implements
: sequential, multicore, multisession, and cluster futures. With these, R
: expressions can be evaluated on the local machine, in parallel a set of
: local machines, or distributed on a mix of local and remote machines.
: Extensions to this package implement additional backends for processing
: futures via compute cluster schedulers, etc. Because of its unified API,
: there is no need to modify any code in order switch from sequential on the
: local machine to, say, distributed processing on a remote compute cluster.
: Another strength of this package is that global variables and functions are
: automatically identified and exported as needed, making it straightforward
: to tweak existing code to make use of futures.