How to Install and Uninstall python3-acora.x86_64 Package on Fedora 36
Last updated: January 15,2025
1. Install "python3-acora.x86_64" package
This guide covers the steps necessary to install python3-acora.x86_64 on Fedora 36
$
sudo dnf update
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$
sudo dnf install
python3-acora.x86_64
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2. Uninstall "python3-acora.x86_64" package
This tutorial shows how to uninstall python3-acora.x86_64 on Fedora 36:
$
sudo dnf remove
python3-acora.x86_64
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$
sudo dnf autoremove
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3. Information about the python3-acora.x86_64 package on Fedora 36
Last metadata expiration check: 5:53:00 ago on Thu Sep 8 02:05:26 2022.
Available Packages
Name : python3-acora
Version : 2.2
Release : 11.fc36
Architecture : x86_64
Size : 138 k
Source : python-acora-2.2-11.fc36.src.rpm
Repository : fedora
Summary : A Python multi-keyword text search engine
URL : https://github.com/scoder/acora
License : BSD
Description : Acora is 'fgrep' for Python, a fast multi-keyword text search engine.
:
: Based on a set of keywords and the Aho-Corasick algorithm, it generates a
: search automaton and runs it over string input, either unicode or bytes.
:
: Acora comes with both a pure Python implementation and a fast binary module
: written in Cython. However, note that the current construction algorithm is
: not suitable for really large sets of keywords (i.e. more than a couple of
: thousand).
Available Packages
Name : python3-acora
Version : 2.2
Release : 11.fc36
Architecture : x86_64
Size : 138 k
Source : python-acora-2.2-11.fc36.src.rpm
Repository : fedora
Summary : A Python multi-keyword text search engine
URL : https://github.com/scoder/acora
License : BSD
Description : Acora is 'fgrep' for Python, a fast multi-keyword text search engine.
:
: Based on a set of keywords and the Aho-Corasick algorithm, it generates a
: search automaton and runs it over string input, either unicode or bytes.
:
: Acora comes with both a pure Python implementation and a fast binary module
: written in Cython. However, note that the current construction algorithm is
: not suitable for really large sets of keywords (i.e. more than a couple of
: thousand).