How to Install and Uninstall python3-lazyarray Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 14,2024

1. Install "python3-lazyarray" package

Please follow the guidelines below to install python3-lazyarray on Ubuntu 21.10 (Impish Indri)


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

This guide let you learn how to uninstall python3-lazyarray on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python3-lazyarray
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-lazyarray package on Ubuntu 21.10 (Impish Indri)

Package: python3-lazyarray
Architecture: all
Version: 0.3.3-2
Priority: optional
Section: universe/python
Source: lazyarray
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 39
Depends: python3:any, python3-numpy, python3-scipy
Filename: pool/universe/l/lazyarray/python3-lazyarray_0.3.3-2_all.deb
Size: 9248
MD5sum: 56baf0bda98cbd4817ab339b0c5d4f7b
SHA1: 8645c5aac22f07baf42e6a430d1af7f60a092e94
SHA256: 69ac3f0fb3b131837b0ff78da4fa829da6baeab94d78a7e0c7ad6d44008fa24b
SHA512: f222addd599354b2415ce756d288cf12b0ff4e81f7df91862860bda36c39d0ad08ba06edaf789f3dddf78b0e55b5cd944baddfb608e6bd6d44bd22c9e7d1254b
Homepage: https://bitbucket.org/apdavison/lazyarray/
Description-en: Python module providing a NumPy-compatible lazily-evaluated array
The 'larray' class is a NumPy-compatible numerical array where operations on
the array (potentially including array construction) are not performed
immediately, but are delayed until evaluation is specifically requested.
Evaluation of only parts of the array is also possible. Consequently,
use of an 'larray' can potentially save considerable computation time
and memory in cases where arrays are used conditionally, or only parts of an
array are used (for example in distributed computation, in which each MPI node
operates on a subset of the elements of the array).
Description-md5: 7a295752428975a462dd8f5e8fd3bfce