How to Install and Uninstall libhnswlib-dev Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: May 21,2024

1. Install "libhnswlib-dev" package

Please follow the guidance below to install libhnswlib-dev on Ubuntu 21.04 (Hirsute Hippo)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libhnswlib-dev
            
                    
    
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2. Uninstall "libhnswlib-dev" package

Please follow the steps below to uninstall libhnswlib-dev on Ubuntu 21.04 (Hirsute Hippo):


    
        
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                sudo apt remove
            
                        
                libhnswlib-dev
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libhnswlib-dev package on Ubuntu 21.04 (Hirsute Hippo)

Package: libhnswlib-dev
Architecture: all
Version: 0.4.0-3build1
Priority: optional
Section: universe/libdevel
Source: hnswlib
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 107
Filename: pool/universe/h/hnswlib/libhnswlib-dev_0.4.0-3build1_all.deb
Size: 19784
MD5sum: 731b6d8c6bc93810195b9a67f0d82474
SHA1: 1860c5ee7be1cf1a3f1800814dae968eedd61653
SHA256: 1f2431e8d49b70c934ae5a737c0f4e857b660635716fc0bff1ca7af1ccd2f78d
SHA512: 45b539d7a1a20ffb678672714167f4ab961aa8b3de2cb43c2f0cc6be1aed4e2bb5a8e32571ff55aed3d0dd7c9c49775542c56796618141b68bf2ce6d235f0865
Homepage: https://github.com/nmslib/hnswlib
Description-en: fast approximate nearest neighbor search
Header-only C++ HNSW implementation with Python bindings.
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A common task in data analysis but also in scientific computations
is to find data that is very close (multi-dimensional space) or
similar (same thing) to a given data point. Also as heuristics for
physics engines, it is the objects closest to you that you are
most likely to collide with. This library knows how to do this
fast.
Description-md5: c6ef7f656c66b99b44c182c1675b4c13