%global _empty_manifest_terminate_build 0 Name: python-osqp Version: 0.6.2.post8 Release: 1 Summary: OSQP: The Operator Splitting QP Solver License: Apache 2.0 URL: https://osqp.org/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/5a/61/7b94eb7de2b7c9d12d8757ef9d0f5dfe3c5dc0ba0e88f08d4ae929996a34/osqp-0.6.2.post8.tar.gz Requires: python3-numpy Requires: python3-scipy Requires: python3-qdldl %description Python wrapper for `OSQP `__: the Operator Splitting QP Solver. The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving problems in the form minimize 0.5 x' P x + q' x subject to l <= A x <= u where ``x in R^n`` is the optimization variable. The objective function is defined by a positive semidefinite matrix ``P in S^n_+`` and vector ``q in R^n``. The linear constraints are defined by matrix ``A in R^{m x n}`` and vectors ``l in R^m U {-inf}^m``, ``u in R^m U {+inf}^m``. %package -n python3-osqp Summary: OSQP: The Operator Splitting QP Solver Provides: python-osqp BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip BuildRequires: python3-cffi BuildRequires: gcc BuildRequires: gdb %description -n python3-osqp Python wrapper for `OSQP `__: the Operator Splitting QP Solver. The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving problems in the form minimize 0.5 x' P x + q' x subject to l <= A x <= u where ``x in R^n`` is the optimization variable. The objective function is defined by a positive semidefinite matrix ``P in S^n_+`` and vector ``q in R^n``. The linear constraints are defined by matrix ``A in R^{m x n}`` and vectors ``l in R^m U {-inf}^m``, ``u in R^m U {+inf}^m``. %package help Summary: Development documents and examples for osqp Provides: python3-osqp-doc %description help Python wrapper for `OSQP `__: the Operator Splitting QP Solver. The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving problems in the form minimize 0.5 x' P x + q' x subject to l <= A x <= u where ``x in R^n`` is the optimization variable. The objective function is defined by a positive semidefinite matrix ``P in S^n_+`` and vector ``q in R^n``. The linear constraints are defined by matrix ``A in R^{m x n}`` and vectors ``l in R^m U {-inf}^m``, ``u in R^m U {+inf}^m``. %prep %autosetup -n osqp-0.6.2.post8 %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-osqp -f filelist.lst %dir %{python3_sitearch}/* %files help -f doclist.lst %{_docdir}/* %changelog * Mon Apr 10 2023 Python_Bot - 0.6.2.post8-1 - Package Spec generated