How to Install and Uninstall berrynet-dashboard Package on Ubuntu 21.10 (Impish Indri)

Last updated: February 03,2025

1. Install "berrynet-dashboard" package

In this section, we are going to explain the necessary steps to install berrynet-dashboard on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                berrynet-dashboard
            
                    
    
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2. Uninstall "berrynet-dashboard" package

Learn how to uninstall berrynet-dashboard on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                berrynet-dashboard
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the berrynet-dashboard package on Ubuntu 21.10 (Impish Indri)

Package: berrynet-dashboard
Architecture: all
Version: 3.10.2-1build1
Priority: optional
Section: universe/web
Source: berrynet
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Ying-Chun Liu (PaulLiu)
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 235
Depends: freeboard
Filename: pool/universe/b/berrynet/berrynet-dashboard_3.10.2-1build1_all.deb
Size: 85372
MD5sum: 743e89a445421311056ee22a807a005f
SHA1: 8fd3fddabf2afc14f0f0b1c21caad515821f160f
SHA256: d12b47ad4efa10bbeef180be694c1e5275650dbe7b43a6beae204260644f64af
SHA512: 5961595ee166bbbf227d98e02a5e23fc44d7e6f203522c0f392b37163378c1ab4a15ea5dd85d7447493c0e04b7657a5aaccaac82ab7a235f333bbee52194122a
Homepage: https://github.com/DT42/BerryNet
Description-en: deep learning gateway - python3 modules
BerryNet turns devices into an intelligent gateway with deep learning
running on it. No internet connection is required, everything is done
locally on the local LAN and the IoT devices.
.
This package contains the dashboard.
Description-md5: fad4bb00ecce7dcbabea6f3c3425016f