How to Install and Uninstall python3-munkres.noarch Package on Oracle Linux 9
Last updated: November 15,2024
1. Install "python3-munkres.noarch" package
Please follow the guidance below to install python3-munkres.noarch on Oracle Linux 9
$
sudo dnf update
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$
sudo dnf install
python3-munkres.noarch
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2. Uninstall "python3-munkres.noarch" package
In this section, we are going to explain the necessary steps to uninstall python3-munkres.noarch on Oracle Linux 9:
$
sudo dnf remove
python3-munkres.noarch
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$
sudo dnf autoremove
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3. Information about the python3-munkres.noarch package on Oracle Linux 9
Last metadata expiration check: 0:42:16 ago on Thu Feb 15 07:50:05 2024.
Available Packages
Name : python3-munkres
Version : 1.1.2
Release : 14.el9
Architecture : noarch
Size : 23 k
Source : python-munkres-1.1.2-14.el9.src.rpm
Repository : epel
Summary : A Munkres algorithm for Python
URL : http://software.clapper.org/munkres/
License : ASL 2.0
Description : The Munkres module provides an implementation of the Munkres algorithm (also
: called the Hungarian algorithm or the Kuhn-Munkres algorithm). The algorithm
: models an assignment problem as an NxM cost matrix, where each element
: represents the cost of assigning the ith worker to the jth job, and it figures
: out the least-cost solution, choosing a single item from each row and column in
: the matrix, such that no row and no column are used more than once.
Available Packages
Name : python3-munkres
Version : 1.1.2
Release : 14.el9
Architecture : noarch
Size : 23 k
Source : python-munkres-1.1.2-14.el9.src.rpm
Repository : epel
Summary : A Munkres algorithm for Python
URL : http://software.clapper.org/munkres/
License : ASL 2.0
Description : The Munkres module provides an implementation of the Munkres algorithm (also
: called the Hungarian algorithm or the Kuhn-Munkres algorithm). The algorithm
: models an assignment problem as an NxM cost matrix, where each element
: represents the cost of assigning the ith worker to the jth job, and it figures
: out the least-cost solution, choosing a single item from each row and column in
: the matrix, such that no row and no column are used more than once.