automatic import of python-orange-bioinformatics

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diff --git a/.gitignore b/.gitignore
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+/Orange-Bioinformatics-2.6.25.tar.gz
diff --git a/python-orange-bioinformatics.spec b/python-orange-bioinformatics.spec
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+++ b/python-orange-bioinformatics.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-Orange-Bioinformatics
+Version:	2.6.25
+Release:	1
+Summary:	Orange Bioinformatics add-on for Orange data mining software package.
+License:	GPLv3
+URL:		http://orange.biolab.si/download
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/f1/63/b483a205a7e89d3ec1bd0e42f9b72d47b9a5ad868dcd94b118b62cad7d97/Orange-Bioinformatics-2.6.25.tar.gz
+BuildArch:	noarch
+
+
+%description
+Orange Bioinformatics extends Orange_, a data mining software
+package, with common functionality for bioinformatics. The provided
+functionality can be accessed as a Python library or through a visual
+programming interface (Orange Canvas). The latter is also suitable for
+non-programmers.
+In Orange Canvas the analyst connects basic computational units, called
+widgets, into data flow analytics schemas. Two units-widgets can be
+connected if they share a data type. Compared to other popular tools like
+Taverna, Orange widgets are high-level, integrated potentially complex
+tasks, but are specific enough to be used independently. Even elaborate
+analyses rarely consist of more than ten widgets; while tasks such as
+clustering and enrichment analysis could be executed with up to five
+widgets. While building the schema each widget is independently controlled
+with settings, the settings do not conceptually burden the analyst.
+Orange Bioinformatics provides access to publicly available data,
+like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx
+database. As for the analytics, there is gene selection, quality control,
+scoring distances between experiments with multiple factors. All features
+can be combined with powerful visualization, network exploration and
+data mining techniques from the Orange data mining framework.
+Documentation: http://orange-bioinformatics.readthedocs.org/
+
+%package -n python3-Orange-Bioinformatics
+Summary:	Orange Bioinformatics add-on for Orange data mining software package.
+Provides:	python-Orange-Bioinformatics
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-Orange-Bioinformatics
+Orange Bioinformatics extends Orange_, a data mining software
+package, with common functionality for bioinformatics. The provided
+functionality can be accessed as a Python library or through a visual
+programming interface (Orange Canvas). The latter is also suitable for
+non-programmers.
+In Orange Canvas the analyst connects basic computational units, called
+widgets, into data flow analytics schemas. Two units-widgets can be
+connected if they share a data type. Compared to other popular tools like
+Taverna, Orange widgets are high-level, integrated potentially complex
+tasks, but are specific enough to be used independently. Even elaborate
+analyses rarely consist of more than ten widgets; while tasks such as
+clustering and enrichment analysis could be executed with up to five
+widgets. While building the schema each widget is independently controlled
+with settings, the settings do not conceptually burden the analyst.
+Orange Bioinformatics provides access to publicly available data,
+like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx
+database. As for the analytics, there is gene selection, quality control,
+scoring distances between experiments with multiple factors. All features
+can be combined with powerful visualization, network exploration and
+data mining techniques from the Orange data mining framework.
+Documentation: http://orange-bioinformatics.readthedocs.org/
+
+%package help
+Summary:	Development documents and examples for Orange-Bioinformatics
+Provides:	python3-Orange-Bioinformatics-doc
+%description help
+Orange Bioinformatics extends Orange_, a data mining software
+package, with common functionality for bioinformatics. The provided
+functionality can be accessed as a Python library or through a visual
+programming interface (Orange Canvas). The latter is also suitable for
+non-programmers.
+In Orange Canvas the analyst connects basic computational units, called
+widgets, into data flow analytics schemas. Two units-widgets can be
+connected if they share a data type. Compared to other popular tools like
+Taverna, Orange widgets are high-level, integrated potentially complex
+tasks, but are specific enough to be used independently. Even elaborate
+analyses rarely consist of more than ten widgets; while tasks such as
+clustering and enrichment analysis could be executed with up to five
+widgets. While building the schema each widget is independently controlled
+with settings, the settings do not conceptually burden the analyst.
+Orange Bioinformatics provides access to publicly available data,
+like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx
+database. As for the analytics, there is gene selection, quality control,
+scoring distances between experiments with multiple factors. All features
+can be combined with powerful visualization, network exploration and
+data mining techniques from the Orange data mining framework.
+Documentation: http://orange-bioinformatics.readthedocs.org/
+
+%prep
+%autosetup -n Orange-Bioinformatics-2.6.25
+
+%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-Orange-Bioinformatics -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 2.6.25-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..4032105
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+c39f769c0e2d1d6b795ed9b44f68201f  Orange-Bioinformatics-2.6.25.tar.gz