How to Install and Uninstall python311-distob Package on openSuSE Tumbleweed

Last updated: November 12,2024

Deprecated! Installation of this package may no longer be supported.

1. Install "python311-distob" package

Please follow the guidance below to install python311-distob on openSuSE Tumbleweed


    
        
            $
        

        
            
                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                python311-distob
            
                    
    
    Copied

2. Uninstall "python311-distob" package

Learn how to uninstall python311-distob on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                python311-distob
            
                    
    
    Copied

3. Information about the python311-distob package on openSuSE Tumbleweed

Information for package python311-distob:
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Repository : openSUSE-Tumbleweed-Oss
Name : python311-distob
Version : 0.3.3-3.9
Arch : noarch
Vendor : openSUSE
Installed Size : 529.5 KiB
Installed : No
Status : not installed
Source package : python-distob-0.3.3-3.9.src
Upstream URL : https://github.com/mattja/distob/
Summary : Distributed computing using remote objects
Description :
Distob will take your existing python objects, or a sequence of
objects, and scatter them onto many IPython parallel engines, which
may be running on a single computer or on a cluster.
In place of the original objects, proxy objects are kept on the client
computer that provide the same interface as the original objects. You
can continue to use these as if the objects were still local. All
methods are passed through to the remote objects, where computation is
done.
In particular, sending numpy arrays to the cluster is supported.
A numpy array can also be scattered across the cluster, along a
particular axis. Operations on the array can then be automatically
done in parallel.