How to Install and Uninstall python39-networkx Package on openSuSE Tumbleweed
Last updated: December 25,2024
1. Install "python39-networkx" package
Here is a brief guide to show you how to install python39-networkx on openSuSE Tumbleweed
$
sudo zypper refresh
Copied
$
sudo zypper install
python39-networkx
Copied
2. Uninstall "python39-networkx" package
This tutorial shows how to uninstall python39-networkx on openSuSE Tumbleweed:
$
sudo zypper remove
python39-networkx
Copied
3. Information about the python39-networkx package on openSuSE Tumbleweed
Information for package python39-networkx:
------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-networkx
Version : 3.1-1.3
Arch : noarch
Vendor : openSUSE
Installed Size : 12.4 MiB
Installed : No
Status : not installed
Source package : python-networkx-3.1-1.3.src
Upstream URL : https://networkx.github.io/
Summary : Python package for the study of complex networks
Description :
NetworkX (NX) is a Python package for the creation, manipulation, and study of the structure, dynamics,
and functions of complex networks.
Features:
* Includes standard graph-theoretic and statistical physics functions
* Exchange of network algorithms between applications, disciplines, and platforms
* Includes many classic graphs and synthetic networks
* Nodes and edges can be "anything" (e.g. time-series, text, images, XML records)
* Exploits existing code from high-quality legacy software in C, C++, Fortran, etc.
* Unit-tested
------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-networkx
Version : 3.1-1.3
Arch : noarch
Vendor : openSUSE
Installed Size : 12.4 MiB
Installed : No
Status : not installed
Source package : python-networkx-3.1-1.3.src
Upstream URL : https://networkx.github.io/
Summary : Python package for the study of complex networks
Description :
NetworkX (NX) is a Python package for the creation, manipulation, and study of the structure, dynamics,
and functions of complex networks.
Features:
* Includes standard graph-theoretic and statistical physics functions
* Exchange of network algorithms between applications, disciplines, and platforms
* Includes many classic graphs and synthetic networks
* Nodes and edges can be "anything" (e.g. time-series, text, images, XML records)
* Exploits existing code from high-quality legacy software in C, C++, Fortran, etc.
* Unit-tested