How to Install and Uninstall python-colorspacious-doc.noarch Package on Fedora 34
Last updated: November 25,2024
1. Install "python-colorspacious-doc.noarch" package
Please follow the guidelines below to install python-colorspacious-doc.noarch on Fedora 34
$
sudo dnf update
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$
sudo dnf install
python-colorspacious-doc.noarch
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2. Uninstall "python-colorspacious-doc.noarch" package
Please follow the guidance below to uninstall python-colorspacious-doc.noarch on Fedora 34:
$
sudo dnf remove
python-colorspacious-doc.noarch
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$
sudo dnf autoremove
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3. Information about the python-colorspacious-doc.noarch package on Fedora 34
Last metadata expiration check: 3:43:42 ago on Tue Sep 6 08:10:37 2022.
Available Packages
Name : python-colorspacious-doc
Version : 1.1.2
Release : 12.fc34
Architecture : noarch
Size : 1.4 M
Source : python-colorspacious-1.1.2-12.fc34.src.rpm
Repository : fedora
Summary : HTML documentation for python colorspacious module
URL : https://github.com/njsmith/colorspacious
License : MIT
Description :
: Colorspacious is a powerful, accurate, and easy-to-use library for
: performing colorspace conversions.
:
: In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
: CIELab, CIELCh), we also include: color vision deficiency ("color
: blindness") simulations using the approach of Machado et al (2009);
: a complete implementation of CIECAM02; and the perceptually uniform
: CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al (2006).
:
: This package contains the HTML documentation.
Available Packages
Name : python-colorspacious-doc
Version : 1.1.2
Release : 12.fc34
Architecture : noarch
Size : 1.4 M
Source : python-colorspacious-1.1.2-12.fc34.src.rpm
Repository : fedora
Summary : HTML documentation for python colorspacious module
URL : https://github.com/njsmith/colorspacious
License : MIT
Description :
: Colorspacious is a powerful, accurate, and easy-to-use library for
: performing colorspace conversions.
:
: In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
: CIELab, CIELCh), we also include: color vision deficiency ("color
: blindness") simulations using the approach of Machado et al (2009);
: a complete implementation of CIECAM02; and the perceptually uniform
: CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al (2006).
:
: This package contains the HTML documentation.