How to Install and Uninstall python-jieba-doc Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 16,2024

1. Install "python-jieba-doc" package

This guide let you learn how to install python-jieba-doc on Ubuntu 21.10 (Impish Indri)


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                python-jieba-doc
            
                    
    
    Copied

2. Uninstall "python-jieba-doc" package

This guide let you learn how to uninstall python-jieba-doc on Ubuntu 21.10 (Impish Indri):


    
        
            $
        

        
            
                sudo apt remove
            
                        
                python-jieba-doc
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the python-jieba-doc package on Ubuntu 21.10 (Impish Indri)

Package: python-jieba-doc
Architecture: all
Version: 0.42.1-2
Multi-Arch: foreign
Priority: optional
Section: universe/doc
Source: python-jieba
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Chinese Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 14021
Filename: pool/universe/p/python-jieba/python-jieba-doc_0.42.1-2_all.deb
Size: 3563096
MD5sum: 18c7f827f37a0a6e78847f5cf9776022
SHA1: 0e7374218c5d2cd67ac6092933f45e2b3f0f2147
SHA256: 1b8dfb7b7709e67e85490df885437178133913ad6b6e1cc228f6cd744c1313a9
SHA512: e20d0135bf0379afb693995dd352e7d73ecd0418365dc9520e5e22e58365182cc6fa9e104ca33301f31c1e816ebf3a36e774802cbb650097c7ebc0974dcb4d90
Homepage: https://github.com/fxsjy/jieba
Description-en: Jieba Chinese text segmenter (common documentation)
"Jieba" (Chinese for "to stutter")is a high-accuracy Chinese text segmenteran
based on HMM-model and Viterbi algorithm. It uses dynamic programming to find
the most probable combination based on the word frequency.
.
This is the common documentation package.
Description-md5: 9b71be0d2e0bc556b41ff448d0af92e3