How to Install and Uninstall python36-ntc-templates Package on openSuSE Tumbleweed
Last updated: November 06,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "python36-ntc-templates" package
This guide let you learn how to install python36-ntc-templates on openSuSE Tumbleweed
$
sudo zypper refresh
Copied
$
sudo zypper install
python36-ntc-templates
Copied
2. Uninstall "python36-ntc-templates" package
Here is a brief guide to show you how to uninstall python36-ntc-templates on openSuSE Tumbleweed:
$
sudo zypper remove
python36-ntc-templates
Copied
3. Information about the python36-ntc-templates package on openSuSE Tumbleweed
Information for package python36-ntc-templates:
-----------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python36-ntc-templates
Version : 3.0.0-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 726,2 KiB
Installed : No
Status : not installed
Source package : python-ntc-templates-3.0.0-1.1.src
Summary : Package to return structured data from the output of network devices
Description :
TextFSM is a project built by Google that takes CLI string output and passes each line through a series of regular expressions until it finds a match. The regular expressions use named capture groups to build a text table out of the significant text. The names of the capture groups are used as column headers, and the captured values are stored as rows in the table.
-----------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python36-ntc-templates
Version : 3.0.0-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 726,2 KiB
Installed : No
Status : not installed
Source package : python-ntc-templates-3.0.0-1.1.src
Summary : Package to return structured data from the output of network devices
Description :
TextFSM is a project built by Google that takes CLI string output and passes each line through a series of regular expressions until it finds a match. The regular expressions use named capture groups to build a text table out of the significant text. The names of the capture groups are used as column headers, and the captured values are stored as rows in the table.