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+/cvxpy-base-1.3.1.tar.gz
diff --git a/python-cvxpy-base.spec b/python-cvxpy-base.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-cvxpy-base
+Version:	1.3.1
+Release:	1
+Summary:	A domain-specific language for modeling convex optimization problems in Python.
+License:	Apache License, Version 2.0
+URL:		https://github.com/cvxpy/cvxpy
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/db/c4/8ba47328d38cc2311923b2ba4f13c3c55354138938aee5f96222f6f3f09f/cvxpy-base-1.3.1.tar.gz
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-setuptools
+Requires:	python3-cylp
+Requires:	python3-clarabel
+Requires:	python3-cvxopt
+Requires:	python3-diffcp
+Requires:	python3-ortools
+Requires:	python3-cvxopt
+Requires:	python3-cvxopt
+Requires:	python3-gurobipy
+Requires:	python3-scipy
+Requires:	python3-Mosek
+Requires:	python3-ortools
+Requires:	python3-proxsuite
+Requires:	python3-PySCIPOpt
+Requires:	python3-scipy
+Requires:	python3-setuptools
+Requires:	python3-xpress
+
+%description
+[![Build Status](http://github.com/cvxpy/cvxpy/workflows/build/badge.svg?event=push)](https://github.com/cvxpy/cvxpy/actions/workflows/build.yml)
+![PyPI - downloads](https://img.shields.io/pypi/dm/cvxpy.svg?label=Pypi%20downloads)
+![Conda - downloads](https://img.shields.io/conda/dn/conda-forge/cvxpy.svg?label=Conda%20downloads)
+[![Coverage](https://sonarcloud.io/api/project_badges/measure?project=cvxpy_cvxpy&metric=coverage)](https://sonarcloud.io/summary/new_code?id=cvxpy_cvxpy)
+[![Benchmarks](http://img.shields.io/badge/benchmarked%20by-asv-blue.svg?style=flat)](https://cvxpy.github.io/benchmarks/)
+[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/cvxpy/cvxpy/badge)](https://api.securityscorecards.dev/projects/github.com/cvxpy/cvxpy)
+**The CVXPY documentation is at [cvxpy.org](http://www.cvxpy.org/).**
+*We are building a CVXPY community on [Discord](https://discord.gg/4urRQeGBCr). Join the conversation! For issues and long-form discussions, use [Github Issues](https://github.com/cvxpy/cvxpy/issues) and [Github Discussions](https://github.com/cvxpy/cvxpy/discussions).*
+**Contents**
+- [Installation](#installation)
+- [Getting started](#getting-started)
+- [Issues](#issues)
+- [Community](#community)
+- [Contributing](#contributing)
+- [Team](#team)
+- [Citing](#citing)
+CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.
+For example, the following code solves a least-squares problem where the variable is constrained by lower and upper bounds:
+```python3
+import cvxpy as cp
+import numpy
+# Problem data.
+m = 30
+n = 20
+numpy.random.seed(1)
+A = numpy.random.randn(m, n)
+b = numpy.random.randn(m)
+# Construct the problem.
+x = cp.Variable(n)
+objective = cp.Minimize(cp.sum_squares(A @ x - b))
+constraints = [0 <= x, x <= 1]
+prob = cp.Problem(objective, constraints)
+# The optimal objective is returned by prob.solve().
+result = prob.solve()
+# The optimal value for x is stored in x.value.
+print(x.value)
+# The optimal Lagrange multiplier for a constraint
+# is stored in constraint.dual_value.
+print(constraints[0].dual_value)
+```
+With CVXPY, you can model
+* convex optimization problems,
+* mixed-integer convex optimization problems,
+* geometric programs, and
+* quasiconvex programs.
+CVXPY is not a solver. It relies upon the open source solvers
+[ECOS](http://github.com/ifa-ethz/ecos), [SCS](https://github.com/bodono/scs-python),
+and [OSQP](https://github.com/oxfordcontrol/osqp). Additional solvers are
+[available](https://www.cvxpy.org/tutorial/advanced/index.html#choosing-a-solver),
+but must be installed separately.
+CVXPY began as a Stanford University research project. It is now developed by
+many people, across many institutions and countries.
+## Installation
+CVXPY is available on PyPI, and can be installed with
+```
+pip install cvxpy
+```
+CVXPY can also be installed with conda, using
+```
+conda install -c conda-forge cvxpy
+```
+CVXPY has the following dependencies:
+- Python >= 3.7
+- OSQP >= 0.4.1
+- ECOS >= 2
+- SCS >= 1.1.6
+- NumPy >= 1.15
+- SciPy >= 1.1.0
+For detailed instructions, see the [installation
+guide](https://www.cvxpy.org/install/index.html).
+## Getting started
+To get started with CVXPY, check out the following:
+* [official CVXPY tutorial](https://www.cvxpy.org/tutorial/index.html)
+* [example library](https://www.cvxpy.org/examples/index.html)
+* [API reference](https://www.cvxpy.org/api_reference/cvxpy.html)
+## Issues
+We encourage you to report issues using the [Github tracker](https://github.com/cvxpy/cvxpy/issues). We welcome all kinds of issues, especially those related to correctness, documentation, performance, and feature requests.
+For basic usage questions (e.g., "Why isn't my problem DCP?"), please use [StackOverflow](https://stackoverflow.com/questions/tagged/cvxpy) instead.
+## Community
+The CVXPY community consists of researchers, data scientists, software engineers, and students from all over the world. We welcome you to join us!
+* To chat with the CVXPY community in real-time, join us on [Discord](https://discord.gg/4urRQeGBCr).
+* To have longer, in-depth discussions with the CVXPY community, use [Github Discussions](https://github.com/cvxpy/cvxpy/discussions).
+* To share feature requests and bug reports, use [Github Issues](https://github.com/cvxpy/cvxpy/issues).
+Please be respectful in your communications with the CVXPY community, and make sure to abide by our [code of conduct](https://github.com/cvxpy/cvxpy/blob/master/CODE_OF_CONDUCT.md).
+## Contributing
+We appreciate all contributions. You don't need to be an expert in convex
+optimization to help out.
+You should first
+install [CVXPY from source](https://www.cvxpy.org/install/index.html#install-from-source).
+Here are some simple ways to start contributing immediately:
+* Read the CVXPY source code and improve the documentation, or address TODOs
+* Enhance the [website documentation](https://github.com/cvxpy/cvxpy/tree/master/doc)
+* Browse the [issue tracker](https://github.com/cvxpy/cvxpy/issues), and look for issues tagged as "help wanted"
+* Polish the [example library](https://github.com/cvxpy/cvxpy/tree/master/examples)
+* Add a [benchmark](https://github.com/cvxpy/cvxpy/tree/master/cvxpy/tests/test_benchmarks.py)
+If you'd like to add a new example to our library, or implement a new feature,
+please get in touch with us first to make sure that your priorities align with
+ours. 
+Contributions should be submitted as [pull requests](https://github.com/cvxpy/cvxpy/pulls).
+A member of the CVXPY development team will review the pull request and guide
+you through the contributing process.
+Before starting work on your contribution, please read the [contributing guide](https://github.com/cvxpy/cvxpy/blob/master/CONTRIBUTING.md).
+## Team
+CVXPY is a community project, built from the contributions of many
+researchers and engineers.
+CVXPY is developed and maintained by [Steven
+Diamond](https://stevendiamond.me/), [Akshay
+Agrawal](https://akshayagrawal.com), [Riley Murray](https://rileyjmurray.wordpress.com/), 
+[Philipp Schiele](https://www.philippschiele.com/),
+and [Bartolomeo Stellato](https://stellato.io/), with many others contributing
+significantly. A non-exhaustive list of people who have shaped CVXPY over the
+years includes Stephen Boyd, Eric Chu, Robin Verschueren, Michael Sommerauer,
+Jaehyun Park, Enzo Busseti, AJ Friend, Judson Wilson, Chris
+Dembia, and Philipp Schiele.
+For more information about the team and our processes, see our [governance document](https://github.com/cvxpy/org/blob/main/governance.md).
+## Citing
+If you use CVXPY for academic work, we encourage you to [cite our papers](https://www.cvxpy.org/citing/index.html). If you use CVXPY in industry, we'd love to hear from you as well, on Discord or over email.
+
+%package -n python3-cvxpy-base
+Summary:	A domain-specific language for modeling convex optimization problems in Python.
+Provides:	python-cvxpy-base
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+BuildRequires:	python3-cffi
+BuildRequires:	gcc
+BuildRequires:	gdb
+%description -n python3-cvxpy-base
+[![Build Status](http://github.com/cvxpy/cvxpy/workflows/build/badge.svg?event=push)](https://github.com/cvxpy/cvxpy/actions/workflows/build.yml)
+![PyPI - downloads](https://img.shields.io/pypi/dm/cvxpy.svg?label=Pypi%20downloads)
+![Conda - downloads](https://img.shields.io/conda/dn/conda-forge/cvxpy.svg?label=Conda%20downloads)
+[![Coverage](https://sonarcloud.io/api/project_badges/measure?project=cvxpy_cvxpy&metric=coverage)](https://sonarcloud.io/summary/new_code?id=cvxpy_cvxpy)
+[![Benchmarks](http://img.shields.io/badge/benchmarked%20by-asv-blue.svg?style=flat)](https://cvxpy.github.io/benchmarks/)
+[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/cvxpy/cvxpy/badge)](https://api.securityscorecards.dev/projects/github.com/cvxpy/cvxpy)
+**The CVXPY documentation is at [cvxpy.org](http://www.cvxpy.org/).**
+*We are building a CVXPY community on [Discord](https://discord.gg/4urRQeGBCr). Join the conversation! For issues and long-form discussions, use [Github Issues](https://github.com/cvxpy/cvxpy/issues) and [Github Discussions](https://github.com/cvxpy/cvxpy/discussions).*
+**Contents**
+- [Installation](#installation)
+- [Getting started](#getting-started)
+- [Issues](#issues)
+- [Community](#community)
+- [Contributing](#contributing)
+- [Team](#team)
+- [Citing](#citing)
+CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.
+For example, the following code solves a least-squares problem where the variable is constrained by lower and upper bounds:
+```python3
+import cvxpy as cp
+import numpy
+# Problem data.
+m = 30
+n = 20
+numpy.random.seed(1)
+A = numpy.random.randn(m, n)
+b = numpy.random.randn(m)
+# Construct the problem.
+x = cp.Variable(n)
+objective = cp.Minimize(cp.sum_squares(A @ x - b))
+constraints = [0 <= x, x <= 1]
+prob = cp.Problem(objective, constraints)
+# The optimal objective is returned by prob.solve().
+result = prob.solve()
+# The optimal value for x is stored in x.value.
+print(x.value)
+# The optimal Lagrange multiplier for a constraint
+# is stored in constraint.dual_value.
+print(constraints[0].dual_value)
+```
+With CVXPY, you can model
+* convex optimization problems,
+* mixed-integer convex optimization problems,
+* geometric programs, and
+* quasiconvex programs.
+CVXPY is not a solver. It relies upon the open source solvers
+[ECOS](http://github.com/ifa-ethz/ecos), [SCS](https://github.com/bodono/scs-python),
+and [OSQP](https://github.com/oxfordcontrol/osqp). Additional solvers are
+[available](https://www.cvxpy.org/tutorial/advanced/index.html#choosing-a-solver),
+but must be installed separately.
+CVXPY began as a Stanford University research project. It is now developed by
+many people, across many institutions and countries.
+## Installation
+CVXPY is available on PyPI, and can be installed with
+```
+pip install cvxpy
+```
+CVXPY can also be installed with conda, using
+```
+conda install -c conda-forge cvxpy
+```
+CVXPY has the following dependencies:
+- Python >= 3.7
+- OSQP >= 0.4.1
+- ECOS >= 2
+- SCS >= 1.1.6
+- NumPy >= 1.15
+- SciPy >= 1.1.0
+For detailed instructions, see the [installation
+guide](https://www.cvxpy.org/install/index.html).
+## Getting started
+To get started with CVXPY, check out the following:
+* [official CVXPY tutorial](https://www.cvxpy.org/tutorial/index.html)
+* [example library](https://www.cvxpy.org/examples/index.html)
+* [API reference](https://www.cvxpy.org/api_reference/cvxpy.html)
+## Issues
+We encourage you to report issues using the [Github tracker](https://github.com/cvxpy/cvxpy/issues). We welcome all kinds of issues, especially those related to correctness, documentation, performance, and feature requests.
+For basic usage questions (e.g., "Why isn't my problem DCP?"), please use [StackOverflow](https://stackoverflow.com/questions/tagged/cvxpy) instead.
+## Community
+The CVXPY community consists of researchers, data scientists, software engineers, and students from all over the world. We welcome you to join us!
+* To chat with the CVXPY community in real-time, join us on [Discord](https://discord.gg/4urRQeGBCr).
+* To have longer, in-depth discussions with the CVXPY community, use [Github Discussions](https://github.com/cvxpy/cvxpy/discussions).
+* To share feature requests and bug reports, use [Github Issues](https://github.com/cvxpy/cvxpy/issues).
+Please be respectful in your communications with the CVXPY community, and make sure to abide by our [code of conduct](https://github.com/cvxpy/cvxpy/blob/master/CODE_OF_CONDUCT.md).
+## Contributing
+We appreciate all contributions. You don't need to be an expert in convex
+optimization to help out.
+You should first
+install [CVXPY from source](https://www.cvxpy.org/install/index.html#install-from-source).
+Here are some simple ways to start contributing immediately:
+* Read the CVXPY source code and improve the documentation, or address TODOs
+* Enhance the [website documentation](https://github.com/cvxpy/cvxpy/tree/master/doc)
+* Browse the [issue tracker](https://github.com/cvxpy/cvxpy/issues), and look for issues tagged as "help wanted"
+* Polish the [example library](https://github.com/cvxpy/cvxpy/tree/master/examples)
+* Add a [benchmark](https://github.com/cvxpy/cvxpy/tree/master/cvxpy/tests/test_benchmarks.py)
+If you'd like to add a new example to our library, or implement a new feature,
+please get in touch with us first to make sure that your priorities align with
+ours. 
+Contributions should be submitted as [pull requests](https://github.com/cvxpy/cvxpy/pulls).
+A member of the CVXPY development team will review the pull request and guide
+you through the contributing process.
+Before starting work on your contribution, please read the [contributing guide](https://github.com/cvxpy/cvxpy/blob/master/CONTRIBUTING.md).
+## Team
+CVXPY is a community project, built from the contributions of many
+researchers and engineers.
+CVXPY is developed and maintained by [Steven
+Diamond](https://stevendiamond.me/), [Akshay
+Agrawal](https://akshayagrawal.com), [Riley Murray](https://rileyjmurray.wordpress.com/), 
+[Philipp Schiele](https://www.philippschiele.com/),
+and [Bartolomeo Stellato](https://stellato.io/), with many others contributing
+significantly. A non-exhaustive list of people who have shaped CVXPY over the
+years includes Stephen Boyd, Eric Chu, Robin Verschueren, Michael Sommerauer,
+Jaehyun Park, Enzo Busseti, AJ Friend, Judson Wilson, Chris
+Dembia, and Philipp Schiele.
+For more information about the team and our processes, see our [governance document](https://github.com/cvxpy/org/blob/main/governance.md).
+## Citing
+If you use CVXPY for academic work, we encourage you to [cite our papers](https://www.cvxpy.org/citing/index.html). If you use CVXPY in industry, we'd love to hear from you as well, on Discord or over email.
+
+%package help
+Summary:	Development documents and examples for cvxpy-base
+Provides:	python3-cvxpy-base-doc
+%description help
+[![Build Status](http://github.com/cvxpy/cvxpy/workflows/build/badge.svg?event=push)](https://github.com/cvxpy/cvxpy/actions/workflows/build.yml)
+![PyPI - downloads](https://img.shields.io/pypi/dm/cvxpy.svg?label=Pypi%20downloads)
+![Conda - downloads](https://img.shields.io/conda/dn/conda-forge/cvxpy.svg?label=Conda%20downloads)
+[![Coverage](https://sonarcloud.io/api/project_badges/measure?project=cvxpy_cvxpy&metric=coverage)](https://sonarcloud.io/summary/new_code?id=cvxpy_cvxpy)
+[![Benchmarks](http://img.shields.io/badge/benchmarked%20by-asv-blue.svg?style=flat)](https://cvxpy.github.io/benchmarks/)
+[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/cvxpy/cvxpy/badge)](https://api.securityscorecards.dev/projects/github.com/cvxpy/cvxpy)
+**The CVXPY documentation is at [cvxpy.org](http://www.cvxpy.org/).**
+*We are building a CVXPY community on [Discord](https://discord.gg/4urRQeGBCr). Join the conversation! For issues and long-form discussions, use [Github Issues](https://github.com/cvxpy/cvxpy/issues) and [Github Discussions](https://github.com/cvxpy/cvxpy/discussions).*
+**Contents**
+- [Installation](#installation)
+- [Getting started](#getting-started)
+- [Issues](#issues)
+- [Community](#community)
+- [Contributing](#contributing)
+- [Team](#team)
+- [Citing](#citing)
+CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.
+For example, the following code solves a least-squares problem where the variable is constrained by lower and upper bounds:
+```python3
+import cvxpy as cp
+import numpy
+# Problem data.
+m = 30
+n = 20
+numpy.random.seed(1)
+A = numpy.random.randn(m, n)
+b = numpy.random.randn(m)
+# Construct the problem.
+x = cp.Variable(n)
+objective = cp.Minimize(cp.sum_squares(A @ x - b))
+constraints = [0 <= x, x <= 1]
+prob = cp.Problem(objective, constraints)
+# The optimal objective is returned by prob.solve().
+result = prob.solve()
+# The optimal value for x is stored in x.value.
+print(x.value)
+# The optimal Lagrange multiplier for a constraint
+# is stored in constraint.dual_value.
+print(constraints[0].dual_value)
+```
+With CVXPY, you can model
+* convex optimization problems,
+* mixed-integer convex optimization problems,
+* geometric programs, and
+* quasiconvex programs.
+CVXPY is not a solver. It relies upon the open source solvers
+[ECOS](http://github.com/ifa-ethz/ecos), [SCS](https://github.com/bodono/scs-python),
+and [OSQP](https://github.com/oxfordcontrol/osqp). Additional solvers are
+[available](https://www.cvxpy.org/tutorial/advanced/index.html#choosing-a-solver),
+but must be installed separately.
+CVXPY began as a Stanford University research project. It is now developed by
+many people, across many institutions and countries.
+## Installation
+CVXPY is available on PyPI, and can be installed with
+```
+pip install cvxpy
+```
+CVXPY can also be installed with conda, using
+```
+conda install -c conda-forge cvxpy
+```
+CVXPY has the following dependencies:
+- Python >= 3.7
+- OSQP >= 0.4.1
+- ECOS >= 2
+- SCS >= 1.1.6
+- NumPy >= 1.15
+- SciPy >= 1.1.0
+For detailed instructions, see the [installation
+guide](https://www.cvxpy.org/install/index.html).
+## Getting started
+To get started with CVXPY, check out the following:
+* [official CVXPY tutorial](https://www.cvxpy.org/tutorial/index.html)
+* [example library](https://www.cvxpy.org/examples/index.html)
+* [API reference](https://www.cvxpy.org/api_reference/cvxpy.html)
+## Issues
+We encourage you to report issues using the [Github tracker](https://github.com/cvxpy/cvxpy/issues). We welcome all kinds of issues, especially those related to correctness, documentation, performance, and feature requests.
+For basic usage questions (e.g., "Why isn't my problem DCP?"), please use [StackOverflow](https://stackoverflow.com/questions/tagged/cvxpy) instead.
+## Community
+The CVXPY community consists of researchers, data scientists, software engineers, and students from all over the world. We welcome you to join us!
+* To chat with the CVXPY community in real-time, join us on [Discord](https://discord.gg/4urRQeGBCr).
+* To have longer, in-depth discussions with the CVXPY community, use [Github Discussions](https://github.com/cvxpy/cvxpy/discussions).
+* To share feature requests and bug reports, use [Github Issues](https://github.com/cvxpy/cvxpy/issues).
+Please be respectful in your communications with the CVXPY community, and make sure to abide by our [code of conduct](https://github.com/cvxpy/cvxpy/blob/master/CODE_OF_CONDUCT.md).
+## Contributing
+We appreciate all contributions. You don't need to be an expert in convex
+optimization to help out.
+You should first
+install [CVXPY from source](https://www.cvxpy.org/install/index.html#install-from-source).
+Here are some simple ways to start contributing immediately:
+* Read the CVXPY source code and improve the documentation, or address TODOs
+* Enhance the [website documentation](https://github.com/cvxpy/cvxpy/tree/master/doc)
+* Browse the [issue tracker](https://github.com/cvxpy/cvxpy/issues), and look for issues tagged as "help wanted"
+* Polish the [example library](https://github.com/cvxpy/cvxpy/tree/master/examples)
+* Add a [benchmark](https://github.com/cvxpy/cvxpy/tree/master/cvxpy/tests/test_benchmarks.py)
+If you'd like to add a new example to our library, or implement a new feature,
+please get in touch with us first to make sure that your priorities align with
+ours. 
+Contributions should be submitted as [pull requests](https://github.com/cvxpy/cvxpy/pulls).
+A member of the CVXPY development team will review the pull request and guide
+you through the contributing process.
+Before starting work on your contribution, please read the [contributing guide](https://github.com/cvxpy/cvxpy/blob/master/CONTRIBUTING.md).
+## Team
+CVXPY is a community project, built from the contributions of many
+researchers and engineers.
+CVXPY is developed and maintained by [Steven
+Diamond](https://stevendiamond.me/), [Akshay
+Agrawal](https://akshayagrawal.com), [Riley Murray](https://rileyjmurray.wordpress.com/), 
+[Philipp Schiele](https://www.philippschiele.com/),
+and [Bartolomeo Stellato](https://stellato.io/), with many others contributing
+significantly. A non-exhaustive list of people who have shaped CVXPY over the
+years includes Stephen Boyd, Eric Chu, Robin Verschueren, Michael Sommerauer,
+Jaehyun Park, Enzo Busseti, AJ Friend, Judson Wilson, Chris
+Dembia, and Philipp Schiele.
+For more information about the team and our processes, see our [governance document](https://github.com/cvxpy/org/blob/main/governance.md).
+## Citing
+If you use CVXPY for academic work, we encourage you to [cite our papers](https://www.cvxpy.org/citing/index.html). If you use CVXPY in industry, we'd love to hear from you as well, on Discord or over email.
+
+%prep
+%autosetup -n cvxpy-base-1.3.1
+
+%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-cvxpy-base -f filelist.lst
+%dir %{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 1.3.1-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..5fa9b8c
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+e01ee073d53eb62470a4565a6878b198  cvxpy-base-1.3.1.tar.gz