How to Install and Uninstall ghc-cassava.x86_64 Package on Fedora 34

Last updated: December 24,2024

1. Install "ghc-cassava.x86_64" package

This guide let you learn how to install ghc-cassava.x86_64 on Fedora 34


    
        
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                sudo dnf update
            
                    
    
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                sudo dnf install
            
                        
                ghc-cassava.x86_64
            
                    
    
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2. Uninstall "ghc-cassava.x86_64" package

This tutorial shows how to uninstall ghc-cassava.x86_64 on Fedora 34:


    
        
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                sudo dnf remove
            
                        
                ghc-cassava.x86_64
            
                    
    
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            $
        

        
            
                sudo dnf autoremove
            
                    
    
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3. Information about the ghc-cassava.x86_64 package on Fedora 34

Last metadata expiration check: 3:54:28 ago on Tue Sep 6 02:10:55 2022.
Available Packages
Name : ghc-cassava
Version : 0.5.2.0
Release : 4.fc34
Architecture : x86_64
Size : 191 k
Source : ghc-cassava-0.5.2.0-4.fc34.src.rpm
Repository : fedora
Summary : A CSV parsing and encoding library
URL : https://hackage.haskell.org/package/cassava
License : BSD
Description : 'cassava' is a library for parsing and encoding RFC 4180 compliant
: comma-separated values (CSV) data, which is a textual line-oriented format
: commonly used for exchanging tabular data.
:
: cassava's API includes support for
:
: - Index-based record-conversion
: - Name-based record-conversion
: - Typeclass directed conversion of fields and records
: - Built-in field-conversion instances for standard types
: - Customizable record-conversion instance derivation via GHC generics
: - Low-level bytestring builders (see "Data.Csv.Builder")
: - Incremental decoding and encoding API (see "Data.Csv.Incremental")
: - Streaming API for constant-space decoding (see "Data.Csv.Streaming")
:
: Moreover, this library is designed to be easy to use. Please refer to the
: documentation in "Data.Csv" and the included README for more usage examples.