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%global _empty_manifest_terminate_build 0
Name: python-niapy
Version: 2.0.4
Release: 1
Summary: Python micro framework for building nature-inspired algorithms.
License: MIT
URL: https://github.com/NiaOrg/NiaPy
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f1/44/ab840e655f1a08b68f311cfc02358892866895cc555ca4eeea9a649a3769/niapy-2.0.4.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-matplotlib
Requires: python3-pandas
Requires: python3-openpyxl
%description
|Check codestyle and test build| |PyPI Version| |PyPI - Python Version|
|PyPI - Status| |PyPI - Downloads| |GitHub Release Date|
|Anaconda-Server Badge| |Fedora package| |AUR package| |Documentation Status| |GitHub license|
|Scrutinizer Code Quality| |Coverage Status| |GitHub commit activity|
|Updates| |Average time to resolve an issue| |Percentage of issues still
open| |GitHub contributors|
|DOI| |image1|
Nature-inspired algorithms are a very popular tool for solving
optimization problems. Numerous variants of nature-inspired algorithms
have been developed (`paper 1 <https://arxiv.org/abs/1307.4186>`__,
`paper 2 <https://www.mdpi.com/2076-3417/8/9/1521>`__) since the
beginning of their era. To prove their versatility, those were tested in
various domains on various applications, especially when they are
hybridized, modified or adapted. However, implementation of
nature-inspired algorithms is sometimes a difficult, complex and tedious
task. In order to break this wall, NiaPy is intended for simple and
quick use, without spending time for implementing algorithms from
scratch.
- **Free software:** MIT license
- **Documentation:** https://niapy.readthedocs.io/en/stable/
- **Python versions:** 3.6.x, 3.7.x, 3.8.x, 3.9.x
- **Dependencies:** `click
here <CONTRIBUTING.md#development-dependencies>`__
%package -n python3-niapy
Summary: Python micro framework for building nature-inspired algorithms.
Provides: python-niapy
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-niapy
|Check codestyle and test build| |PyPI Version| |PyPI - Python Version|
|PyPI - Status| |PyPI - Downloads| |GitHub Release Date|
|Anaconda-Server Badge| |Fedora package| |AUR package| |Documentation Status| |GitHub license|
|Scrutinizer Code Quality| |Coverage Status| |GitHub commit activity|
|Updates| |Average time to resolve an issue| |Percentage of issues still
open| |GitHub contributors|
|DOI| |image1|
Nature-inspired algorithms are a very popular tool for solving
optimization problems. Numerous variants of nature-inspired algorithms
have been developed (`paper 1 <https://arxiv.org/abs/1307.4186>`__,
`paper 2 <https://www.mdpi.com/2076-3417/8/9/1521>`__) since the
beginning of their era. To prove their versatility, those were tested in
various domains on various applications, especially when they are
hybridized, modified or adapted. However, implementation of
nature-inspired algorithms is sometimes a difficult, complex and tedious
task. In order to break this wall, NiaPy is intended for simple and
quick use, without spending time for implementing algorithms from
scratch.
- **Free software:** MIT license
- **Documentation:** https://niapy.readthedocs.io/en/stable/
- **Python versions:** 3.6.x, 3.7.x, 3.8.x, 3.9.x
- **Dependencies:** `click
here <CONTRIBUTING.md#development-dependencies>`__
%package help
Summary: Development documents and examples for niapy
Provides: python3-niapy-doc
%description help
|Check codestyle and test build| |PyPI Version| |PyPI - Python Version|
|PyPI - Status| |PyPI - Downloads| |GitHub Release Date|
|Anaconda-Server Badge| |Fedora package| |AUR package| |Documentation Status| |GitHub license|
|Scrutinizer Code Quality| |Coverage Status| |GitHub commit activity|
|Updates| |Average time to resolve an issue| |Percentage of issues still
open| |GitHub contributors|
|DOI| |image1|
Nature-inspired algorithms are a very popular tool for solving
optimization problems. Numerous variants of nature-inspired algorithms
have been developed (`paper 1 <https://arxiv.org/abs/1307.4186>`__,
`paper 2 <https://www.mdpi.com/2076-3417/8/9/1521>`__) since the
beginning of their era. To prove their versatility, those were tested in
various domains on various applications, especially when they are
hybridized, modified or adapted. However, implementation of
nature-inspired algorithms is sometimes a difficult, complex and tedious
task. In order to break this wall, NiaPy is intended for simple and
quick use, without spending time for implementing algorithms from
scratch.
- **Free software:** MIT license
- **Documentation:** https://niapy.readthedocs.io/en/stable/
- **Python versions:** 3.6.x, 3.7.x, 3.8.x, 3.9.x
- **Dependencies:** `click
here <CONTRIBUTING.md#development-dependencies>`__
%prep
%autosetup -n niapy-2.0.4
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-niapy -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu Mar 09 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.4-1
- Package Spec generated
|
