automatic import of python-string-kernels

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+/string-kernels-1.1.2.tar.gz
diff --git a/python-string-kernels.spec b/python-string-kernels.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-string-kernels
+Version:	1.1.2
+Release:	1
+Summary:	Polynomial String Kernel and linear time String Kernel. Supports multithreading and is compatible with Scikit-Learn SVMs.
+License:	Academic Free License (AFL)
+URL:		https://github.com/weekend37/string-kernels
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/ff/e7/04765217cdeced887f495c6833a93227d89f8342b1254f8979d294cb8874/string-kernels-1.1.2.tar.gz
+BuildArch:	noarch
+
+
+%description
+# String Kernels
+
+This package contains an implementation of the **Polynomial String Kernel** and a linear time **String Kernel** algorithm as described in our paper, [High Resolution Ancestry Deconvolution for Next Generation Genomic Data](https://www.biorxiv.org/content/10.1101/2021.09.19.460980v1). <br/><br/>
+
+<img caption="String Kernel Computations" src="https://raw.githubusercontent.com/weekend37/string-kernels/master/doc/fig/triangular_numbers.png">
+
+It offers
+
+- Linear time computation of two effective string kernels.
+
+- Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
+
+- Multithreading.
+
+## Usage
+
+To install the package, execute from the command line
+
+```
+pip install string-kernels
+```
+
+And then you're all set!
+
+Assuming you have [Scikit-Learn](https://scikit-learn.org/) already installed, you can use Lodhi's string kernel via
+
+```python
+from sklearn import svm
+from stringkernels.kernels import string_kernel
+model = svm.SVC(kernel=string_kernel())
+```
+
+and the polynomial string kernel,
+
+```python
+from sklearn import svm
+from stringkernels.kernels import polynomial_string_kernel
+model = svm.SVC(kernel=polynomial_string_kernel())
+```
+
+For morer information read the [docs](https://github.com/weekend37/string-kernels/blob/master/doc/docs.md) or take a look at the notebook [example.ipynb](https://github.com/weekend37/string-kernels/blob/master/example.ipynb) for further demonstration of usage.
+
+If you end up using this in your research we kindly ask you to cite us! :)
+
+
+
+
+%package -n python3-string-kernels
+Summary:	Polynomial String Kernel and linear time String Kernel. Supports multithreading and is compatible with Scikit-Learn SVMs.
+Provides:	python-string-kernels
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-string-kernels
+# String Kernels
+
+This package contains an implementation of the **Polynomial String Kernel** and a linear time **String Kernel** algorithm as described in our paper, [High Resolution Ancestry Deconvolution for Next Generation Genomic Data](https://www.biorxiv.org/content/10.1101/2021.09.19.460980v1). <br/><br/>
+
+<img caption="String Kernel Computations" src="https://raw.githubusercontent.com/weekend37/string-kernels/master/doc/fig/triangular_numbers.png">
+
+It offers
+
+- Linear time computation of two effective string kernels.
+
+- Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
+
+- Multithreading.
+
+## Usage
+
+To install the package, execute from the command line
+
+```
+pip install string-kernels
+```
+
+And then you're all set!
+
+Assuming you have [Scikit-Learn](https://scikit-learn.org/) already installed, you can use Lodhi's string kernel via
+
+```python
+from sklearn import svm
+from stringkernels.kernels import string_kernel
+model = svm.SVC(kernel=string_kernel())
+```
+
+and the polynomial string kernel,
+
+```python
+from sklearn import svm
+from stringkernels.kernels import polynomial_string_kernel
+model = svm.SVC(kernel=polynomial_string_kernel())
+```
+
+For morer information read the [docs](https://github.com/weekend37/string-kernels/blob/master/doc/docs.md) or take a look at the notebook [example.ipynb](https://github.com/weekend37/string-kernels/blob/master/example.ipynb) for further demonstration of usage.
+
+If you end up using this in your research we kindly ask you to cite us! :)
+
+
+
+
+%package help
+Summary:	Development documents and examples for string-kernels
+Provides:	python3-string-kernels-doc
+%description help
+# String Kernels
+
+This package contains an implementation of the **Polynomial String Kernel** and a linear time **String Kernel** algorithm as described in our paper, [High Resolution Ancestry Deconvolution for Next Generation Genomic Data](https://www.biorxiv.org/content/10.1101/2021.09.19.460980v1). <br/><br/>
+
+<img caption="String Kernel Computations" src="https://raw.githubusercontent.com/weekend37/string-kernels/master/doc/fig/triangular_numbers.png">
+
+It offers
+
+- Linear time computation of two effective string kernels.
+
+- Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
+
+- Multithreading.
+
+## Usage
+
+To install the package, execute from the command line
+
+```
+pip install string-kernels
+```
+
+And then you're all set!
+
+Assuming you have [Scikit-Learn](https://scikit-learn.org/) already installed, you can use Lodhi's string kernel via
+
+```python
+from sklearn import svm
+from stringkernels.kernels import string_kernel
+model = svm.SVC(kernel=string_kernel())
+```
+
+and the polynomial string kernel,
+
+```python
+from sklearn import svm
+from stringkernels.kernels import polynomial_string_kernel
+model = svm.SVC(kernel=polynomial_string_kernel())
+```
+
+For morer information read the [docs](https://github.com/weekend37/string-kernels/blob/master/doc/docs.md) or take a look at the notebook [example.ipynb](https://github.com/weekend37/string-kernels/blob/master/example.ipynb) for further demonstration of usage.
+
+If you end up using this in your research we kindly ask you to cite us! :)
+
+
+
+
+%prep
+%autosetup -n string-kernels-1.1.2
+
+%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-string-kernels -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.2-1
+- Package Spec generated
diff --git a/sources b/sources
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+5d0c76313c841b7c0bc869cb19b431f8  string-kernels-1.1.2.tar.gz