How to Install and Uninstall python-pynn-devel.x86_64 Package on Fedora 36

Last updated: November 25,2024

1. Install "python-pynn-devel.x86_64" package

This guide let you learn how to install python-pynn-devel.x86_64 on Fedora 36

$ sudo dnf update $ sudo dnf install python-pynn-devel.x86_64

2. Uninstall "python-pynn-devel.x86_64" package

Please follow the step by step instructions below to uninstall python-pynn-devel.x86_64 on Fedora 36:

$ sudo dnf remove python-pynn-devel.x86_64 $ sudo dnf autoremove

3. Information about the python-pynn-devel.x86_64 package on Fedora 36

Last metadata expiration check: 3:13:36 ago on Thu Sep 8 08:04:50 2022.
Available Packages
Name : python-pynn-devel
Version : 0.10.0
Release : 2.fc36
Architecture : x86_64
Size : 9.7 k
Source : python-pynn-0.10.0-2.fc36.src.rpm
Repository : fedora
Summary : A package for simulator-independent specification of neuronal network models
URL : http://neuralensemble.org/PyNN/
License : CeCILL
Description : PyNN (pronounced 'pine') is a simulator-independent language for building
: neuronal network models.
:
: In other words, you can write the code for a model once, using the PyNN API and
: the Python programming language, and then run it without modification on any
: simulator that PyNN supports (currently NEURON, NEST and Brian) and on a number
: of neuromorphic hardware systems.
:
: The PyNN API aims to support modelling at a high-level of abstraction
: (populations of neurons, layers, columns and the connections between them)
: while still allowing access to the details of individual neurons and synapses
: when required. PyNN provides a library of standard neuron, synapse and synaptic
: plasticity models, which have been verified to work the same on the different
: supported simulators. PyNN also provides a set of commonly-used connectivity
: algorithms (e.g. all-to-all, random, distance-dependent, small-world) but makes
: it easy to provide your own connectivity in a simulator-independent way.
:
: Even if you don’t wish to run simulations on multiple simulators, you may
: benefit from writing your simulation code using PyNN’s powerful, high-level
: interface. In this case, you can use any neuron or synapse model supported by
: your simulator, and are not restricted to the standard models.
:
: Documentation: http://neuralensemble.org/docs/PyNN/
: Mailing list: https://groups.google.com/forum/?fromgroups#!forum/neuralensemble
:
: This package supports the NEURON, NEST, and Brian simulators.