automatic import of python-supersuit

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diff --git a/.gitignore b/.gitignore
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+/SuperSuit-3.7.2.tar.gz
diff --git a/python-supersuit.spec b/python-supersuit.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-SuperSuit
+Version:	3.7.2
+Release:	1
+Summary:	Wrappers for Gymnasium and PettingZoo
+License:	MIT License
+URL:		https://github.com/Farama-Foundation/SuperSuit
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/ea/46/a966520971d4dc1c5159b13d4cfb0b7e15ebf12e5a8aafd98d807ee2c93d/SuperSuit-3.7.2.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-gymnasium
+
+%description
+<p align="center">
+    <img src="https://raw.githubusercontent.com/Farama-Foundation/SuperSuit/master/supersuit-text.png" width="500px"/>
+</p>
+
+
+SuperSuit introduces a collection of small functions which can wrap reinforcement learning environments to do preprocessing ('microwrappers').
+We support Gymnasium for single agent environments and PettingZoo for multi-agent environments (both AECEnv and ParallelEnv environments).
+
+
+Using it with Gymnasium to convert space invaders to have a grey scale observation space and stack the last 4 frames looks like:
+
+```
+import gymnasium
+from supersuit import color_reduction_v0, frame_stack_v1
+
+env = gymnasium.make('SpaceInvaders-v0')
+
+env = frame_stack_v1(color_reduction_v0(env, 'full'), 4)
+```
+
+Similarly, using SuperSuit with PettingZoo environments looks like
+
+```
+from pettingzoo.butterfly import pistonball_v0
+env = pistonball_v0.env()
+
+env = frame_stack_v1(color_reduction_v0(env, 'full'), 4)
+```
+
+
+**Please note**: Once the planned wrapper rewrite of Gymnasium is complete and the vector API is stabilized, this project will be deprecated and rewritten as part of a new wrappers package in PettingZoo and the vectorized API will be redone, taking inspiration from the functionality currently in Gymnasium.
+
+## Installing SuperSuit
+To install SuperSuit from pypi:
+
+```
+python3 -m venv env
+source env/bin/activate
+pip install --upgrade pip
+pip install supersuit
+```
+
+Alternatively, to install SuperSuit from source, clone this repo, `cd` to it, and then:
+
+```
+python3 -m venv env
+source env/bin/activate
+pip install --upgrade pip
+pip install -e .
+```
+
+
+
+%package -n python3-SuperSuit
+Summary:	Wrappers for Gymnasium and PettingZoo
+Provides:	python-SuperSuit
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-SuperSuit
+<p align="center">
+    <img src="https://raw.githubusercontent.com/Farama-Foundation/SuperSuit/master/supersuit-text.png" width="500px"/>
+</p>
+
+
+SuperSuit introduces a collection of small functions which can wrap reinforcement learning environments to do preprocessing ('microwrappers').
+We support Gymnasium for single agent environments and PettingZoo for multi-agent environments (both AECEnv and ParallelEnv environments).
+
+
+Using it with Gymnasium to convert space invaders to have a grey scale observation space and stack the last 4 frames looks like:
+
+```
+import gymnasium
+from supersuit import color_reduction_v0, frame_stack_v1
+
+env = gymnasium.make('SpaceInvaders-v0')
+
+env = frame_stack_v1(color_reduction_v0(env, 'full'), 4)
+```
+
+Similarly, using SuperSuit with PettingZoo environments looks like
+
+```
+from pettingzoo.butterfly import pistonball_v0
+env = pistonball_v0.env()
+
+env = frame_stack_v1(color_reduction_v0(env, 'full'), 4)
+```
+
+
+**Please note**: Once the planned wrapper rewrite of Gymnasium is complete and the vector API is stabilized, this project will be deprecated and rewritten as part of a new wrappers package in PettingZoo and the vectorized API will be redone, taking inspiration from the functionality currently in Gymnasium.
+
+## Installing SuperSuit
+To install SuperSuit from pypi:
+
+```
+python3 -m venv env
+source env/bin/activate
+pip install --upgrade pip
+pip install supersuit
+```
+
+Alternatively, to install SuperSuit from source, clone this repo, `cd` to it, and then:
+
+```
+python3 -m venv env
+source env/bin/activate
+pip install --upgrade pip
+pip install -e .
+```
+
+
+
+%package help
+Summary:	Development documents and examples for SuperSuit
+Provides:	python3-SuperSuit-doc
+%description help
+<p align="center">
+    <img src="https://raw.githubusercontent.com/Farama-Foundation/SuperSuit/master/supersuit-text.png" width="500px"/>
+</p>
+
+
+SuperSuit introduces a collection of small functions which can wrap reinforcement learning environments to do preprocessing ('microwrappers').
+We support Gymnasium for single agent environments and PettingZoo for multi-agent environments (both AECEnv and ParallelEnv environments).
+
+
+Using it with Gymnasium to convert space invaders to have a grey scale observation space and stack the last 4 frames looks like:
+
+```
+import gymnasium
+from supersuit import color_reduction_v0, frame_stack_v1
+
+env = gymnasium.make('SpaceInvaders-v0')
+
+env = frame_stack_v1(color_reduction_v0(env, 'full'), 4)
+```
+
+Similarly, using SuperSuit with PettingZoo environments looks like
+
+```
+from pettingzoo.butterfly import pistonball_v0
+env = pistonball_v0.env()
+
+env = frame_stack_v1(color_reduction_v0(env, 'full'), 4)
+```
+
+
+**Please note**: Once the planned wrapper rewrite of Gymnasium is complete and the vector API is stabilized, this project will be deprecated and rewritten as part of a new wrappers package in PettingZoo and the vectorized API will be redone, taking inspiration from the functionality currently in Gymnasium.
+
+## Installing SuperSuit
+To install SuperSuit from pypi:
+
+```
+python3 -m venv env
+source env/bin/activate
+pip install --upgrade pip
+pip install supersuit
+```
+
+Alternatively, to install SuperSuit from source, clone this repo, `cd` to it, and then:
+
+```
+python3 -m venv env
+source env/bin/activate
+pip install --upgrade pip
+pip install -e .
+```
+
+
+
+%prep
+%autosetup -n SuperSuit-3.7.2
+
+%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-SuperSuit -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 3.7.2-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..6f14c0f
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+dd02499352a3489f807515eccdecc6f3  SuperSuit-3.7.2.tar.gz