How to Install and Uninstall marisa.x86_64 Package on Fedora 35
Last updated: November 26,2024
1. Install "marisa.x86_64" package
Please follow the step by step instructions below to install marisa.x86_64 on Fedora 35
$
sudo dnf update
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$
sudo dnf install
marisa.x86_64
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2. Uninstall "marisa.x86_64" package
This guide covers the steps necessary to uninstall marisa.x86_64 on Fedora 35:
$
sudo dnf remove
marisa.x86_64
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$
sudo dnf autoremove
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3. Information about the marisa.x86_64 package on Fedora 35
Last metadata expiration check: 0:56:57 ago on Wed Sep 7 14:25:02 2022.
Available Packages
Name : marisa
Version : 0.2.4
Release : 52.fc35
Architecture : x86_64
Size : 82 k
Source : marisa-0.2.4-52.fc35.src.rpm
Repository : fedora
Summary : Static and spece-efficient trie data structure library
URL : https://code.google.com/p/marisa-trie
License : BSD or LGPLv2+
Description : Matching Algorithm with Recursively Implemented StorAge (MARISA) is a
: static and space-efficient trie data structure. And libmarisa is a C++
: library to provide an implementation of MARISA. Also, the package of
: libmarisa contains a set of command line tools for building and
: operating a MARISA-based dictionary.
:
: A MARISA-based dictionary supports not only lookup but also reverse
: lookup, common prefix search and predictive search.
Available Packages
Name : marisa
Version : 0.2.4
Release : 52.fc35
Architecture : x86_64
Size : 82 k
Source : marisa-0.2.4-52.fc35.src.rpm
Repository : fedora
Summary : Static and spece-efficient trie data structure library
URL : https://code.google.com/p/marisa-trie
License : BSD or LGPLv2+
Description : Matching Algorithm with Recursively Implemented StorAge (MARISA) is a
: static and space-efficient trie data structure. And libmarisa is a C++
: library to provide an implementation of MARISA. Also, the package of
: libmarisa contains a set of command line tools for building and
: operating a MARISA-based dictionary.
:
: A MARISA-based dictionary supports not only lookup but also reverse
: lookup, common prefix search and predictive search.