How to Install and Uninstall python3-pyfastnoisesimd.x86_64 Package on Fedora 39
Last updated: November 28,2024
1. Install "python3-pyfastnoisesimd.x86_64" package
Please follow the guidance below to install python3-pyfastnoisesimd.x86_64 on Fedora 39
$
sudo dnf update
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$
sudo dnf install
python3-pyfastnoisesimd.x86_64
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2. Uninstall "python3-pyfastnoisesimd.x86_64" package
Here is a brief guide to show you how to uninstall python3-pyfastnoisesimd.x86_64 on Fedora 39:
$
sudo dnf remove
python3-pyfastnoisesimd.x86_64
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$
sudo dnf autoremove
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3. Information about the python3-pyfastnoisesimd.x86_64 package on Fedora 39
Last metadata expiration check: 4:26:02 ago on Thu Mar 7 17:44:52 2024.
Available Packages
Name : python3-pyfastnoisesimd
Version : 0.4.2
Release : 10.fc39
Architecture : x86_64
Size : 226 k
Source : python-pyfastnoisesimd-0.4.2-10.fc39.src.rpm
Repository : fedora
Summary : Python Fast Noise with SIMD
URL : http://github.com/robbmcleod/pyfastnoisesimd
License : BSD-3-Clause
Description : PyFastNoiseSIMD is a wrapper around Jordan Peck's synthetic noise library which
: has been accelerated with SIMD instruction sets.
:
: Parallelism is further enhanced by the use of concurrent.futures to
: multi-thread the generation of noise for large arrays. Thread scaling is
: generally in the range of 50-90%, depending largely on the vectorized
: instruction set used. The number of threads, defaults to the number of virtual
: cores on the system.
Available Packages
Name : python3-pyfastnoisesimd
Version : 0.4.2
Release : 10.fc39
Architecture : x86_64
Size : 226 k
Source : python-pyfastnoisesimd-0.4.2-10.fc39.src.rpm
Repository : fedora
Summary : Python Fast Noise with SIMD
URL : http://github.com/robbmcleod/pyfastnoisesimd
License : BSD-3-Clause
Description : PyFastNoiseSIMD is a wrapper around Jordan Peck's synthetic noise library which
: has been accelerated with SIMD instruction sets.
:
: Parallelism is further enhanced by the use of concurrent.futures to
: multi-thread the generation of noise for large arrays. Thread scaling is
: generally in the range of 50-90%, depending largely on the vectorized
: instruction set used. The number of threads, defaults to the number of virtual
: cores on the system.