How to Install and Uninstall ruby3.0-rubygem-raindrops Package on openSuSE Tumbleweed
Last updated: November 26,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "ruby3.0-rubygem-raindrops" package
This guide covers the steps necessary to install ruby3.0-rubygem-raindrops on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
ruby3.0-rubygem-raindrops
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2. Uninstall "ruby3.0-rubygem-raindrops" package
This guide let you learn how to uninstall ruby3.0-rubygem-raindrops on openSuSE Tumbleweed:
$
sudo zypper remove
ruby3.0-rubygem-raindrops
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3. Information about the ruby3.0-rubygem-raindrops package on openSuSE Tumbleweed
Information for package ruby3.0-rubygem-raindrops:
--------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : ruby3.0-rubygem-raindrops
Version : 0.19.2-1.2
Arch : x86_64
Vendor : openSUSE
Installed Size : 259,2 KiB
Installed : No
Status : not installed
Source package : rubygem-raindrops-0.19.2-1.2.src
Summary : real-time stats for preforking Rack servers
Description :
raindrops is a real-time stats toolkit to show statistics for Rack HTTP
servers. It is designed for preforking servers such as unicorn, but
should support any Rack HTTP server on platforms supporting POSIX shared
memory. It may also be used as a generic scoreboard for sharing atomic
counters across multiple processes.
--------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : ruby3.0-rubygem-raindrops
Version : 0.19.2-1.2
Arch : x86_64
Vendor : openSUSE
Installed Size : 259,2 KiB
Installed : No
Status : not installed
Source package : rubygem-raindrops-0.19.2-1.2.src
Summary : real-time stats for preforking Rack servers
Description :
raindrops is a real-time stats toolkit to show statistics for Rack HTTP
servers. It is designed for preforking servers such as unicorn, but
should support any Rack HTTP server on platforms supporting POSIX shared
memory. It may also be used as a generic scoreboard for sharing atomic
counters across multiple processes.