How to Install and Uninstall python3-logreduce Package on openSUSE Leap
Last updated: November 26,2024
1. Install "python3-logreduce" package
In this section, we are going to explain the necessary steps to install python3-logreduce on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
python3-logreduce
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2. Uninstall "python3-logreduce" package
This tutorial shows how to uninstall python3-logreduce on openSUSE Leap:
$
sudo zypper remove
python3-logreduce
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3. Information about the python3-logreduce package on openSUSE Leap
Information for package python3-logreduce:
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Repository : Main Repository
Name : python3-logreduce
Version : 0.5.2-bp155.2.10
Arch : noarch
Vendor : openSUSE
Installed Size : 491.2 KiB
Installed : No
Status : not installed
Source package : python-logreduce-0.5.2-bp155.2.10.src
Upstream URL : https://logreduce.softwarefactory-project.io/
Summary : Log file anomaly extractor
Description :
Based on success logs, logreduce highlights useful text in failed logs.
The goal is to save time in finding a failure's root cause.
On average, learning run at 2000 lines per second, and
testing run at 1300 lines per seconds.
logreduce uses a *model* to learn successful logs and detect novelties in
failed logs:
* Random words are manually removed using regular expression
* Then lines are converted to a matrix of token occurrences
(using **HashingVectorizer**),
* An unsupervised learner implements neighbor searches
(using **NearestNeighbors**).
------------------------------------------
Repository : Main Repository
Name : python3-logreduce
Version : 0.5.2-bp155.2.10
Arch : noarch
Vendor : openSUSE
Installed Size : 491.2 KiB
Installed : No
Status : not installed
Source package : python-logreduce-0.5.2-bp155.2.10.src
Upstream URL : https://logreduce.softwarefactory-project.io/
Summary : Log file anomaly extractor
Description :
Based on success logs, logreduce highlights useful text in failed logs.
The goal is to save time in finding a failure's root cause.
On average, learning run at 2000 lines per second, and
testing run at 1300 lines per seconds.
logreduce uses a *model* to learn successful logs and detect novelties in
failed logs:
* Random words are manually removed using regular expression
* Then lines are converted to a matrix of token occurrences
(using **HashingVectorizer**),
* An unsupervised learner implements neighbor searches
(using **NearestNeighbors**).