How to Install and Uninstall python312-ntc-templates Package on openSuSE Tumbleweed
Last updated: November 24,2024
1. Install "python312-ntc-templates" package
Please follow the instructions below to install python312-ntc-templates on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python312-ntc-templates
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2. Uninstall "python312-ntc-templates" package
This guide covers the steps necessary to uninstall python312-ntc-templates on openSuSE Tumbleweed:
$
sudo zypper remove
python312-ntc-templates
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3. Information about the python312-ntc-templates package on openSuSE Tumbleweed
Information for package python312-ntc-templates:
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Repository : openSUSE-Tumbleweed-Oss
Name : python312-ntc-templates
Version : 3.5.0-1.3
Arch : noarch
Vendor : openSUSE
Installed Size : 747.3 KiB
Installed : No
Status : not installed
Source package : python-ntc-templates-3.5.0-1.3.src
Upstream URL : https://github.com/networktocode/ntc-templates
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 : python312-ntc-templates
Version : 3.5.0-1.3
Arch : noarch
Vendor : openSUSE
Installed Size : 747.3 KiB
Installed : No
Status : not installed
Source package : python-ntc-templates-3.5.0-1.3.src
Upstream URL : https://github.com/networktocode/ntc-templates
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.