How to Install and Uninstall python3-pyeclib Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: May 14,2024

1. Install "python3-pyeclib" package

This guide covers the steps necessary to install python3-pyeclib on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-pyeclib
            
                    
    
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2. Uninstall "python3-pyeclib" package

This is a short guide on how to uninstall python3-pyeclib on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                python3-pyeclib
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-pyeclib package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: python3-pyeclib
Priority: optional
Section: universe/python
Installed-Size: 107
Maintainer: Ubuntu Developers
Original-Maintainer: PKG OpenStack
Architecture: amd64
Source: python-pyeclib
Version: 1.2.0-1
Depends: python3 (<< 3.6), python3 (>= 3.5~), libc6 (>= 2.4), liberasurecode1
Pre-Depends: dpkg (>= 1.15.6~)
Suggests: libjerasure2
Filename: pool/universe/p/python-pyeclib/python3-pyeclib_1.2.0-1_amd64.deb
Size: 24226
MD5sum: 56c53161e2eb0415d9bb0929d32f17a9
SHA1: 3d7060742c1d178ad954dd7148bc0e3bd8d69448
SHA256: 5ad863913c02a004338ca6e90c3e118981ce135f22fd3a68f986423c8b16fba7
Description-en: interface for implementing erasure codes - Python 3.x
This library provides a simple Python interface for implementing erasure
codes. To obtain the best possible performance, the underlying erasure code
algorithms are written in C.
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This library makes use of Jerasure for Reed-Solomon and provides its own flat
XOR-based erasure code encoder and decoder. Currently, it implements a
specific class of HD Combination Codes (see "Flat XOR-based erasure codes in
storage systems: Constructions, efficient recovery, and tradeoffs" in IEEE
MSST 2010). These codes are well-suited to archival use-cases, have a simple
construction and require a minimum number of participating disks during
single-disk reconstruction (think XOR-based LRC code).
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This package contains the Python 3.x module.
Description-md5: 68e698b8d7e713858257d7db26cef498
Homepage: https://bitbucket.org/kmgreen2/pyeclib
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu