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

Last updated: November 22,2024

1. Install "numba-doc" package

Please follow the steps below to install numba-doc on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                numba-doc
            
                    
    
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2. Uninstall "numba-doc" package

Please follow the guidelines below to uninstall numba-doc on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                numba-doc
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the numba-doc package on Ubuntu 21.10 (Impish Indri)

Package: numba-doc
Architecture: all
Version: 0.52.0-4
Priority: optional
Section: universe/doc
Source: numba
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 18210
Depends: libjs-sphinxdoc (>= 2.4.3-5~), sphinx-rtd-theme-common (>= 0.5.1+dfsg)
Recommends: python3-numba
Filename: pool/universe/n/numba/numba-doc_0.52.0-4_all.deb
Size: 690040
MD5sum: e15bf1d5ad9773f270c2cad5c0579286
SHA1: 926c448c6b316aedfc6222b9e2dce1cbbb170d97
SHA256: cf95cb7e735aa93e46addbb2bc07d51837217acdf38b1a3be27cbf0a0a21cec8
SHA512: cdbcba1e85669506acf4f5a759f188b22e180d129a6e70095e5e5cb43192f9c7ca54bd1b7be02621e9206481a7a92f1369771883f36ddec5023f48ae5756d139
Homepage: http://numba.pydata.org/
Description-en: native machine code compiler for Python (docs)
Numba compiles native machine code instructions from Python programs at
runtime using the LLVM compiler infrastructure. Just-in-time compilation with
Numba could be easily employed by decorating individual computation intensive
functions in the Python code.
Numba could significantly speed up the performance of computations, and
optionally supports compilation to run on GPU processors through Nvidia's
CUDA platform.
It integrates well with the Python scientific software stack, and
especially recognizes Numpy arrays.
.
This package contains the documentation and examples.
Description-md5: c0dcfd237d66973e0d104bb73c082a8e