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@@ -0,0 +1 @@ +/Orange-Bioinformatics-2.6.25.tar.gz diff --git a/python-orange-bioinformatics.spec b/python-orange-bioinformatics.spec new file mode 100644 index 0000000..1418955 --- /dev/null +++ b/python-orange-bioinformatics.spec @@ -0,0 +1,132 @@ +%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 @@ -0,0 +1 @@ +c39f769c0e2d1d6b795ed9b44f68201f Orange-Bioinformatics-2.6.25.tar.gz |