How to Install and Uninstall python3-bluepyopt-doc.noarch Package on Fedora 36
Last updated: September 28,2024
1. Install "python3-bluepyopt-doc.noarch" package
Learn how to install python3-bluepyopt-doc.noarch on Fedora 36
$
sudo dnf update
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$
sudo dnf install
python3-bluepyopt-doc.noarch
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2. Uninstall "python3-bluepyopt-doc.noarch" package
Learn how to uninstall python3-bluepyopt-doc.noarch on Fedora 36:
$
sudo dnf remove
python3-bluepyopt-doc.noarch
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$
sudo dnf autoremove
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3. Information about the python3-bluepyopt-doc.noarch package on Fedora 36
Last metadata expiration check: 0:55:33 ago on Thu Sep 8 08:04:50 2022.
Available Packages
Name : python3-bluepyopt-doc
Version : 1.11.15
Release : 2.fc36
Architecture : noarch
Size : 4.5 M
Source : python-bluepyopt-1.11.15-2.fc36.src.rpm
Repository : fedora
Summary : Documentation for bluepyopt
URL : https://github.com/BlueBrain/BluePyOpt
License : LGPLv3
Description : The Blue Brain Python Optimisation Library (BluePyOpt) is an extensible
: framework for data-driven model parameter optimisation that wraps and
: standardises several existing open-source tools. It simplifies the task of
: creating and sharing these optimisations, and the associated techniques and
: knowledge. This is achieved by abstracting the optimisation and evaluation
: tasks into various reusable and flexible discrete elements according to
: established best-practices.
Available Packages
Name : python3-bluepyopt-doc
Version : 1.11.15
Release : 2.fc36
Architecture : noarch
Size : 4.5 M
Source : python-bluepyopt-1.11.15-2.fc36.src.rpm
Repository : fedora
Summary : Documentation for bluepyopt
URL : https://github.com/BlueBrain/BluePyOpt
License : LGPLv3
Description : The Blue Brain Python Optimisation Library (BluePyOpt) is an extensible
: framework for data-driven model parameter optimisation that wraps and
: standardises several existing open-source tools. It simplifies the task of
: creating and sharing these optimisations, and the associated techniques and
: knowledge. This is achieved by abstracting the optimisation and evaluation
: tasks into various reusable and flexible discrete elements according to
: established best-practices.