%global _empty_manifest_terminate_build 0
Name:		python-sklearn-contrib-lightning
Version:	0.6.2.post0
Release:	1
Summary:	Large-scale sparse linear classification, regression and ranking in Python
License:	new BSD
URL:		https://github.com/scikit-learn-contrib/lightning
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/91/28/4badeccd1507b56f21d7500a8e264cbcce4bfd22e0ee82faac388a4216e2/sklearn-contrib-lightning-0.6.2.post0.tar.gz

Requires:	python3-joblib
Requires:	python3-numpy
Requires:	python3-scikit-learn
Requires:	python3-scipy

%description
lightning is a library for large-scale linear classification, regression and
ranking in Python.
Highlights:
- follows the `scikit-learn <https://scikit-learn.org>`_ API conventions
- supports natively both dense and sparse data representations
- computationally demanding parts implemented in `Cython <https://cython.org>`_
Solvers supported:
- primal coordinate descent
- dual coordinate descent (SDCA, Prox-SDCA)
- SGD, AdaGrad, SAG, SAGA, SVRG
- FISTA

%package -n python3-sklearn-contrib-lightning
Summary:	Large-scale sparse linear classification, regression and ranking in Python
Provides:	python-sklearn-contrib-lightning
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
BuildRequires:	python3-cffi
BuildRequires:	gcc
BuildRequires:	gdb
%description -n python3-sklearn-contrib-lightning
lightning is a library for large-scale linear classification, regression and
ranking in Python.
Highlights:
- follows the `scikit-learn <https://scikit-learn.org>`_ API conventions
- supports natively both dense and sparse data representations
- computationally demanding parts implemented in `Cython <https://cython.org>`_
Solvers supported:
- primal coordinate descent
- dual coordinate descent (SDCA, Prox-SDCA)
- SGD, AdaGrad, SAG, SAGA, SVRG
- FISTA

%package help
Summary:	Development documents and examples for sklearn-contrib-lightning
Provides:	python3-sklearn-contrib-lightning-doc
%description help
lightning is a library for large-scale linear classification, regression and
ranking in Python.
Highlights:
- follows the `scikit-learn <https://scikit-learn.org>`_ API conventions
- supports natively both dense and sparse data representations
- computationally demanding parts implemented in `Cython <https://cython.org>`_
Solvers supported:
- primal coordinate descent
- dual coordinate descent (SDCA, Prox-SDCA)
- SGD, AdaGrad, SAG, SAGA, SVRG
- FISTA

%prep
%autosetup -n sklearn-contrib-lightning-0.6.2.post0

%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-sklearn-contrib-lightning -f filelist.lst
%dir %{python3_sitearch}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.2.post0-1
- Package Spec generated