How to Install and Uninstall python3-distroinfo.noarch Package on Fedora 35
Last updated: November 14,2024
1. Install "python3-distroinfo.noarch" package
This guide covers the steps necessary to install python3-distroinfo.noarch on Fedora 35
$
sudo dnf update
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$
sudo dnf install
python3-distroinfo.noarch
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2. Uninstall "python3-distroinfo.noarch" package
Please follow the instructions below to uninstall python3-distroinfo.noarch on Fedora 35:
$
sudo dnf remove
python3-distroinfo.noarch
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$
sudo dnf autoremove
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3. Information about the python3-distroinfo.noarch package on Fedora 35
Last metadata expiration check: 1:34:15 ago on Wed Sep 7 14:25:02 2022.
Available Packages
Name : python3-distroinfo
Version : 0.5.0
Release : 1.fc35
Architecture : noarch
Size : 38 k
Source : python-distroinfo-0.5.0-1.fc35.src.rpm
Repository : fedora
Summary : Parsing and querying distribution metadata stored in text/YAML files
URL : https://github.com/softwarefactory-project/distroinfo
License : ASL 2.0
Description : distroinfo is a python module for parsing, validating and querying
: distribution/packaging metadata stored in human readable and review-able
: text/YAML files.
:
: distroinfo is a generic (re)implementation of rdoinfo parser which proved
: well suited for the task of interfacing with distribution metadata in a human
: friendly way. If you consider code reviews human friendly, that is.
Available Packages
Name : python3-distroinfo
Version : 0.5.0
Release : 1.fc35
Architecture : noarch
Size : 38 k
Source : python-distroinfo-0.5.0-1.fc35.src.rpm
Repository : fedora
Summary : Parsing and querying distribution metadata stored in text/YAML files
URL : https://github.com/softwarefactory-project/distroinfo
License : ASL 2.0
Description : distroinfo is a python module for parsing, validating and querying
: distribution/packaging metadata stored in human readable and review-able
: text/YAML files.
:
: distroinfo is a generic (re)implementation of rdoinfo parser which proved
: well suited for the task of interfacing with distribution metadata in a human
: friendly way. If you consider code reviews human friendly, that is.