automatic import of python-cluster

3 files changed, 113 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..b7d2afc 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/cluster-1.4.1.post3.linux-x86_64.tar.gz
diff --git a/python-cluster.spec b/python-cluster.spec
new file mode 100644
index 0000000..b5012e3
--- /dev/null
+++ b/python-cluster.spec
@@ -0,0 +1,111 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-cluster
+Version:	1.4.1.post3
+Release:	1
+Summary:	please add a summary manually as the author left a blank one
+License:	LGPL
+URL:		https://github.com/exhuma/python-cluster
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/78/6e/ce37ab112e7f704df2c0b61cee544c3b1d49c54b9e43a1beff03a4a03d71/cluster-1.4.1.post3.linux-x86_64.tar.gz
+BuildArch:	noarch
+
+
+%description
+python-cluster is a "simple" package that allows to create several groups
+(clusters) of objects from a list. It's meant to be flexible and able to
+cluster any object. To ensure this kind of flexibility, you need not only to
+supply the list of objects, but also a function that calculates the similarity
+between two of those objects. For simple datatypes, like integers, this can be
+as simple as a subtraction, but more complex calculations are possible. Right
+now, it is possible to generate the clusters using a hierarchical clustering
+and the popular K-Means algorithm. For the hierarchical algorithm there are
+different "linkage" (single, complete, average and uclus) methods available.
+Algorithms are based on the document found at
+http://www.elet.polimi.it/upload/matteucc/Clustering/tutorial_html/
+    The above site is no longer avaialble, but you can still view it in the
+    internet archive at:
+    https://web.archive.org/web/20070912040206/http://home.dei.polimi.it//matteucc/Clustering/tutorial_html/
+
+%package -n python3-cluster
+Summary:	please add a summary manually as the author left a blank one
+Provides:	python-cluster
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-cluster
+python-cluster is a "simple" package that allows to create several groups
+(clusters) of objects from a list. It's meant to be flexible and able to
+cluster any object. To ensure this kind of flexibility, you need not only to
+supply the list of objects, but also a function that calculates the similarity
+between two of those objects. For simple datatypes, like integers, this can be
+as simple as a subtraction, but more complex calculations are possible. Right
+now, it is possible to generate the clusters using a hierarchical clustering
+and the popular K-Means algorithm. For the hierarchical algorithm there are
+different "linkage" (single, complete, average and uclus) methods available.
+Algorithms are based on the document found at
+http://www.elet.polimi.it/upload/matteucc/Clustering/tutorial_html/
+    The above site is no longer avaialble, but you can still view it in the
+    internet archive at:
+    https://web.archive.org/web/20070912040206/http://home.dei.polimi.it//matteucc/Clustering/tutorial_html/
+
+%package help
+Summary:	Development documents and examples for cluster
+Provides:	python3-cluster-doc
+%description help
+python-cluster is a "simple" package that allows to create several groups
+(clusters) of objects from a list. It's meant to be flexible and able to
+cluster any object. To ensure this kind of flexibility, you need not only to
+supply the list of objects, but also a function that calculates the similarity
+between two of those objects. For simple datatypes, like integers, this can be
+as simple as a subtraction, but more complex calculations are possible. Right
+now, it is possible to generate the clusters using a hierarchical clustering
+and the popular K-Means algorithm. For the hierarchical algorithm there are
+different "linkage" (single, complete, average and uclus) methods available.
+Algorithms are based on the document found at
+http://www.elet.polimi.it/upload/matteucc/Clustering/tutorial_html/
+    The above site is no longer avaialble, but you can still view it in the
+    internet archive at:
+    https://web.archive.org/web/20070912040206/http://home.dei.polimi.it//matteucc/Clustering/tutorial_html/
+
+%prep
+%autosetup -n cluster-1.4.1.post3
+
+%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-cluster -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 1.4.1.post3-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..57a9bdc
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+266d943ab9c0623bee189e1532bedbeb  cluster-1.4.1.post3.linux-x86_64.tar.gz