How to Install and Uninstall python3-sparse Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 14,2024

1. Install "python3-sparse" package

Learn how to install python3-sparse on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                python3-sparse
            
                    
    
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2. Uninstall "python3-sparse" package

Please follow the step by step instructions below to uninstall python3-sparse on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                python3-sparse
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-sparse package on Ubuntu 20.10 (Groovy Gorilla)

Package: python3-sparse
Architecture: all
Version: 0.2.0-1
Priority: optional
Section: universe/python
Source: python-sparse
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Python Modules Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 143
Depends: python3-numpy, python3-scipy (>= 0.19), python3-six, python3:any (>= 3.3.2-2~)
Filename: pool/universe/p/python-sparse/python3-sparse_0.2.0-1_all.deb
Size: 26008
MD5sum: 8ecb8527342512985c83a25e51e690ff
SHA1: 9e2624c48a17413183c130ae82a20eb714e8f911
SHA256: 85e92779991f696072a89845a578b77a00a79a6a32386cf18b24530a7f14e6bf
SHA512: 67243b27f368d71863e6ed52e9e0ff891ac3157cf94cfc08e5e16154d3b8f21edfd6131a24f8444e59551db58cdb6448245d2cba52973750aee5b0015e70513f
Homepage: https://github.com/mrocklin/sparse
Description-en: multidimensional sparse arrays for Python
This package implements sparse multidimensional arrays on top of NumPy
and scipy.sparse. It generalizes the scipy.sparse.coo_matrix layout but
extends beyond just rows and columns to an arbitrary number of
dimensions. The original motivation is for machine learning algorithms,
but it is intended for somewhat general use.
.
It supports:
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- NumPy ufuncs (where zeros are preserved)
- Arithmetic with scalars (where zeros are preserved)
- Reductions (sum, max)
- Reshape
- Transpose
- Tensordot
- Slicing with integers, lists, and slices (with no step value)
- Concatenation and stacking
- Addition with other sparse arrays of the same shape
.
This package provides the modules for Python 3.
Description-md5: 1562b1a9e9bf72cd7e4a98f4c276b81c