automatic import of python-serveit

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diff --git a/.gitignore b/.gitignore
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+/ServeIt-0.0.9.tar.gz
diff --git a/python-serveit.spec b/python-serveit.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-ServeIt
+Version:	0.0.9
+Release:	1
+Summary:	Machine learning prediction serving
+License:	MIT License
+URL:		https://github.com/rtlee9/serveit
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/f6/83/bda15c52f95b802f7da9165d076e6f4d9601a385b278f81fb8a2706072cb/ServeIt-0.0.9.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-flask
+Requires:	python3-flask-restful
+Requires:	python3-meinheld
+Requires:	python3-check-manifest
+Requires:	python3-coverage
+
+%description
+|Build Status| |Codacy Grade Badge| |Codacy Coverage Badge| |PyPI
+version|
+ServeIt lets you serve model predictions and supplementary information
+from a RESTful API using your favorite Python ML library in as little as
+one line of code:
+    from serveit.server import ModelServer
+    from sklearn.linear_model import LogisticRegression
+    from sklearn.datasets import load_iris
+    # fit logistic regression on Iris data
+    clf = LogisticRegression()
+    data = load_iris()
+    clf.fit(data.data, data.target)
+    # initialize server with a model and start serving predictions
+    ModelServer(clf, clf.predict).serve()
+Your new API is now accepting ``POST`` requests at
+``localhost:5000/predictions``! Please see the `examples <examples>`__
+directory for detailed examples across domains (e.g., regression, image
+classification), including live examples.
+Features
+^^^^^^^^
+Current ServeIt features include:
+1. Model inference serving via RESTful API endpoint
+2. Extensible library for inference-time data loading, preprocessing,
+   input validation, and postprocessing
+3. Supplementary information endpoint creation
+4. Automatic JSON serialization of responses
+5. Configurable request and response logging (work in progress)
+Supported libraries
+^^^^^^^^^^^^^^^^^^^
+The following libraries are currently supported: \* Scikit-Learn \*
+Keras \* PyTorch
+
+%package -n python3-ServeIt
+Summary:	Machine learning prediction serving
+Provides:	python-ServeIt
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-ServeIt
+|Build Status| |Codacy Grade Badge| |Codacy Coverage Badge| |PyPI
+version|
+ServeIt lets you serve model predictions and supplementary information
+from a RESTful API using your favorite Python ML library in as little as
+one line of code:
+    from serveit.server import ModelServer
+    from sklearn.linear_model import LogisticRegression
+    from sklearn.datasets import load_iris
+    # fit logistic regression on Iris data
+    clf = LogisticRegression()
+    data = load_iris()
+    clf.fit(data.data, data.target)
+    # initialize server with a model and start serving predictions
+    ModelServer(clf, clf.predict).serve()
+Your new API is now accepting ``POST`` requests at
+``localhost:5000/predictions``! Please see the `examples <examples>`__
+directory for detailed examples across domains (e.g., regression, image
+classification), including live examples.
+Features
+^^^^^^^^
+Current ServeIt features include:
+1. Model inference serving via RESTful API endpoint
+2. Extensible library for inference-time data loading, preprocessing,
+   input validation, and postprocessing
+3. Supplementary information endpoint creation
+4. Automatic JSON serialization of responses
+5. Configurable request and response logging (work in progress)
+Supported libraries
+^^^^^^^^^^^^^^^^^^^
+The following libraries are currently supported: \* Scikit-Learn \*
+Keras \* PyTorch
+
+%package help
+Summary:	Development documents and examples for ServeIt
+Provides:	python3-ServeIt-doc
+%description help
+|Build Status| |Codacy Grade Badge| |Codacy Coverage Badge| |PyPI
+version|
+ServeIt lets you serve model predictions and supplementary information
+from a RESTful API using your favorite Python ML library in as little as
+one line of code:
+    from serveit.server import ModelServer
+    from sklearn.linear_model import LogisticRegression
+    from sklearn.datasets import load_iris
+    # fit logistic regression on Iris data
+    clf = LogisticRegression()
+    data = load_iris()
+    clf.fit(data.data, data.target)
+    # initialize server with a model and start serving predictions
+    ModelServer(clf, clf.predict).serve()
+Your new API is now accepting ``POST`` requests at
+``localhost:5000/predictions``! Please see the `examples <examples>`__
+directory for detailed examples across domains (e.g., regression, image
+classification), including live examples.
+Features
+^^^^^^^^
+Current ServeIt features include:
+1. Model inference serving via RESTful API endpoint
+2. Extensible library for inference-time data loading, preprocessing,
+   input validation, and postprocessing
+3. Supplementary information endpoint creation
+4. Automatic JSON serialization of responses
+5. Configurable request and response logging (work in progress)
+Supported libraries
+^^^^^^^^^^^^^^^^^^^
+The following libraries are currently supported: \* Scikit-Learn \*
+Keras \* PyTorch
+
+%prep
+%autosetup -n ServeIt-0.0.9
+
+%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-ServeIt -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.9-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..92984f8
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+1dd59f5c7739bf960217de0ec04c0462  ServeIt-0.0.9.tar.gz