How to Install and Uninstall python3.11-scipy.x86_64 Package on CentOS Stream 8
Last updated: November 24,2024
1. Install "python3.11-scipy.x86_64" package
Learn how to install python3.11-scipy.x86_64 on CentOS Stream 8
$
sudo dnf update
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$
sudo dnf install
python3.11-scipy.x86_64
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2. Uninstall "python3.11-scipy.x86_64" package
Please follow the guidance below to uninstall python3.11-scipy.x86_64 on CentOS Stream 8:
$
sudo dnf remove
python3.11-scipy.x86_64
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$
sudo dnf autoremove
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3. Information about the python3.11-scipy.x86_64 package on CentOS Stream 8
Last metadata expiration check: 4:08:58 ago on Sun Feb 25 03:03:59 2024.
Available Packages
Name : python3.11-scipy
Version : 1.10.1
Release : 2.el8
Architecture : x86_64
Size : 22 M
Source : python3.11-scipy-1.10.1-2.el8.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.
Available Packages
Name : python3.11-scipy
Version : 1.10.1
Release : 2.el8
Architecture : x86_64
Size : 22 M
Source : python3.11-scipy-1.10.1-2.el8.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.