How to Install and Uninstall libgclib1 Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: November 22,2024

1. Install "libgclib1" package

This is a short guide on how to install libgclib1 on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libgclib1
            
                    
    
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2. Uninstall "libgclib1" package

Please follow the step by step instructions below to uninstall libgclib1 on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                libgclib1
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libgclib1 package on Ubuntu 20.10 (Groovy Gorilla)

Package: libgclib1
Architecture: amd64
Version: 0.11.8-1
Multi-Arch: same
Priority: optional
Section: universe/libs
Source: libgclib
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 378
Depends: libc6 (>= 2.14), libgcc-s1 (>= 3.3.1), libstdc++6 (>= 5)
Filename: pool/universe/libg/libgclib/libgclib1_0.11.8-1_amd64.deb
Size: 142660
MD5sum: 76ab5a228f06e2fac6ffde6cc739ad32
SHA1: 3dd865dc72eec0e8163c697a3226e8ee37eebb7c
SHA256: 780b07a3106d0a9f1909485b2fd96f5c6b07b1767668a690015813e69d191f2c
SHA512: 06b14ffae59e50c09de79c66c53d4c5fcb28f8753ff7d738dfe4866b026ecab6a5f0fbce60d6101ea8a612a5d2739c792c0a1ecb0b2ca13da70ddb80d7b6cc1c
Homepage: https://github.com/gpertea/gclib
Description-en: C++ library to handle biological short sequence data
This is an eclectic gathering of (mostly) C++ code which upstream used
for some bioinformatics projects. The main idea is to provide
lean code and efficient data structures, trying to avoid too many code
dependencies of heavy libraries while minimizing production cycles (and
this also implies a decent compile/build time -- looking at you,
bloated configure scripts and lengthy compile times of Boost code or
other heavy C++ template code..).
.
This code was gathered even before the C++ STL had been fully adopted as
a cross-platform "standard". Since STL by itself is a bit heavier for
most of the C++ needs, it is preferred to use simpler&leaner C++ classes
or templates for basic strings, containers, basic algorithms etc.
Description-md5: 9c72ef489798045bcaeb2c7757b107f6