automatic import of python-apricopt

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diff --git a/.gitignore b/.gitignore
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+/apricopt-0.0.2a3.tar.gz
diff --git a/python-apricopt.spec b/python-apricopt.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-apricopt
+Version:	0.0.2a3
+Release:	1
+Summary:	A library for simulation-based parameter optimization
+License:	GNU General Public License v3 (GPLv3)
+URL:		http://mclab.di.uniroma1.it
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/04/39/3609e58dc6f7b024051535511d817c365063bf03954f5f993956cd2a8748/apricopt-0.0.2a3.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-attrs
+Requires:	python3-chaospy
+Requires:	python3-cycler
+Requires:	python3-future
+Requires:	python3-importlib-metadata
+Requires:	python3-kiwisolver
+Requires:	python3-libroadrunner
+Requires:	python3-matplotlib
+Requires:	python3-mpmath
+Requires:	python3-numpy
+Requires:	python3-Pillow
+Requires:	python3-pyparsing
+Requires:	python3-copasi
+Requires:	python3-dateutil
+Requires:	python3-libsbml
+Requires:	python3-PyYAML
+Requires:	python3-scipy
+Requires:	python3-seaborn
+Requires:	python3-six
+Requires:	python3-sympy
+Requires:	python3-tqdm
+Requires:	python3-zipp
+
+%description
+# Apricopt #
+
+Apricopt is a python framework for simulation-based optimisation of dynamical systems.
+
+It is agnostic with respect to the optimiser and to the simulator.
+
+Apricopt supports the PEtab format for the definition of the optimisation problem. More info about PEtab [here](https://petab.readthedocs.io/en/latest/).
+
+Currently, we support the following simulators:
+
+* COPASI. A state-of-the-art simulator for models of biological processes. We support SBML models (any level and version).
+* RoadRunner. A fast state-of-the-art simulator of biological models.
+
+Currently, we support the following black-box optimisers:
+
+* NOMAD. A state-of the art black-box solver that supports surrogate models. More info [here](https://www.gerad.ca/nomad/).
+* SciPy.optimize. A python library that implements several algorithms for multivariate optimization. More info [here](https://docs.scipy.org/doc/scipy/reference/optimize.html).
+* PySwarms. A python library that implements various forms of the Particle Swarm Optimization algorithm. More info [here](https://pyswarms.readthedocs.io/en/latest/).
+
+Currently, we support the following white-box optimisers:
+
+* COPASI. It supports several optimisation algorithms for biological processes. More info [here](http://copasi.org/Support/User_Manual/Methods/Optimization_Methods/)
+
+### Info ###
+
+WIP
+
+* Version 0.0.2a3
+
+
+### Who do I talk to? ###
+
+* Marco Esposito (author) - esposito@di.uniroma1.it
+* Leonardo Picchiami (author) - picchiami.1643888@studenti.uniroma1.it
+
+
+Copyright (C) 2020-2021  Marco Esposito, Leonardo Picchiami.
+
+Distributed under GNU General Public License v3.
+
+
+
+
+%package -n python3-apricopt
+Summary:	A library for simulation-based parameter optimization
+Provides:	python-apricopt
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-apricopt
+# Apricopt #
+
+Apricopt is a python framework for simulation-based optimisation of dynamical systems.
+
+It is agnostic with respect to the optimiser and to the simulator.
+
+Apricopt supports the PEtab format for the definition of the optimisation problem. More info about PEtab [here](https://petab.readthedocs.io/en/latest/).
+
+Currently, we support the following simulators:
+
+* COPASI. A state-of-the-art simulator for models of biological processes. We support SBML models (any level and version).
+* RoadRunner. A fast state-of-the-art simulator of biological models.
+
+Currently, we support the following black-box optimisers:
+
+* NOMAD. A state-of the art black-box solver that supports surrogate models. More info [here](https://www.gerad.ca/nomad/).
+* SciPy.optimize. A python library that implements several algorithms for multivariate optimization. More info [here](https://docs.scipy.org/doc/scipy/reference/optimize.html).
+* PySwarms. A python library that implements various forms of the Particle Swarm Optimization algorithm. More info [here](https://pyswarms.readthedocs.io/en/latest/).
+
+Currently, we support the following white-box optimisers:
+
+* COPASI. It supports several optimisation algorithms for biological processes. More info [here](http://copasi.org/Support/User_Manual/Methods/Optimization_Methods/)
+
+### Info ###
+
+WIP
+
+* Version 0.0.2a3
+
+
+### Who do I talk to? ###
+
+* Marco Esposito (author) - esposito@di.uniroma1.it
+* Leonardo Picchiami (author) - picchiami.1643888@studenti.uniroma1.it
+
+
+Copyright (C) 2020-2021  Marco Esposito, Leonardo Picchiami.
+
+Distributed under GNU General Public License v3.
+
+
+
+
+%package help
+Summary:	Development documents and examples for apricopt
+Provides:	python3-apricopt-doc
+%description help
+# Apricopt #
+
+Apricopt is a python framework for simulation-based optimisation of dynamical systems.
+
+It is agnostic with respect to the optimiser and to the simulator.
+
+Apricopt supports the PEtab format for the definition of the optimisation problem. More info about PEtab [here](https://petab.readthedocs.io/en/latest/).
+
+Currently, we support the following simulators:
+
+* COPASI. A state-of-the-art simulator for models of biological processes. We support SBML models (any level and version).
+* RoadRunner. A fast state-of-the-art simulator of biological models.
+
+Currently, we support the following black-box optimisers:
+
+* NOMAD. A state-of the art black-box solver that supports surrogate models. More info [here](https://www.gerad.ca/nomad/).
+* SciPy.optimize. A python library that implements several algorithms for multivariate optimization. More info [here](https://docs.scipy.org/doc/scipy/reference/optimize.html).
+* PySwarms. A python library that implements various forms of the Particle Swarm Optimization algorithm. More info [here](https://pyswarms.readthedocs.io/en/latest/).
+
+Currently, we support the following white-box optimisers:
+
+* COPASI. It supports several optimisation algorithms for biological processes. More info [here](http://copasi.org/Support/User_Manual/Methods/Optimization_Methods/)
+
+### Info ###
+
+WIP
+
+* Version 0.0.2a3
+
+
+### Who do I talk to? ###
+
+* Marco Esposito (author) - esposito@di.uniroma1.it
+* Leonardo Picchiami (author) - picchiami.1643888@studenti.uniroma1.it
+
+
+Copyright (C) 2020-2021  Marco Esposito, Leonardo Picchiami.
+
+Distributed under GNU General Public License v3.
+
+
+
+
+%prep
+%autosetup -n apricopt-0.0.2a3
+
+%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-apricopt -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.2a3-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..75d3d56
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+b10d19de1bb1870a2266291f5b25640b  apricopt-0.0.2a3.tar.gz