How to Install and Uninstall python3.11-scipy.x86_64 Package on CentOS Stream 9

Last updated: September 27,2024

1. Install "python3.11-scipy.x86_64" package

Please follow the step by step instructions below to install python3.11-scipy.x86_64 on CentOS Stream 9


    
        
            $
        

        
            
                sudo dnf update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf install
            
                        
                python3.11-scipy.x86_64
            
                    
    
    Copied

2. Uninstall "python3.11-scipy.x86_64" package

Please follow the step by step instructions below to uninstall python3.11-scipy.x86_64 on CentOS Stream 9:


    
        
            $
        

        
            
                sudo dnf remove
            
                        
                python3.11-scipy.x86_64
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the python3.11-scipy.x86_64 package on CentOS Stream 9

Last metadata expiration check: 2:46:32 ago on Sat Mar 16 16:03:45 2024.
Available Packages
Name : python3.11-scipy
Version : 1.10.1
Release : 2.el9
Architecture : x86_64
Size : 23 M
Source : python3.11-scipy-1.10.1-2.el9.src.rpm
Repository : appstream
Summary : Scientific Tools for Python
URL : http://www.scipy.org/scipylib/index.html
License : BSD and Boost and Public Domain
Description : Scipy is open-source software for mathematics, science, and
: engineering. The core library is NumPy which provides convenient and
: fast N-dimensional array manipulation. The SciPy library is built to
: work with NumPy arrays, and provides many user-friendly and efficient
: numerical routines such as routines for numerical integration and
: optimization. Together, they run on all popular operating systems, are
: quick to install, and are free of charge. NumPy and SciPy are easy to
: use, but powerful enough to be depended upon by some of the world's
: leading scientists and engineers.