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diff --git a/python-skater.spec b/python-skater.spec new file mode 100644 index 0000000..cb0cb7e --- /dev/null +++ b/python-skater.spec @@ -0,0 +1,87 @@ +%global _empty_manifest_terminate_build 0 +Name: python-skater +Version: 1.1.2 +Release: 1 +Summary: Model Interpretation Library +License: MIT +URL: https://github.com/datascienceinc/skater/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/5a/99/aa0b52e709a621dfae9fbf8359c9f1ee6d2272e7f53cd2815284e088ec74/skater-1.1.2.tar.gz +BuildArch: noarch + + +%description +Skater is a python package for interpreting(via post-hoc evaluation/rule extraction) predictive models. +With Skater, you can unpack the internal mechanics of arbitrary models; as long +as you can obtain inputs, and use a function to obtain outputs, you can use +Skater to learn about the models internal decision policies. +The package was originally developed by Aaron Kramer, Pramit Choudhary and internal DataScience Team at DataScience.com +to help enable practitioners explain and interpret predictive "black boxes" preferably in a human interpretable way. + +%package -n python3-skater +Summary: Model Interpretation Library +Provides: python-skater +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-skater +Skater is a python package for interpreting(via post-hoc evaluation/rule extraction) predictive models. +With Skater, you can unpack the internal mechanics of arbitrary models; as long +as you can obtain inputs, and use a function to obtain outputs, you can use +Skater to learn about the models internal decision policies. +The package was originally developed by Aaron Kramer, Pramit Choudhary and internal DataScience Team at DataScience.com +to help enable practitioners explain and interpret predictive "black boxes" preferably in a human interpretable way. + +%package help +Summary: Development documents and examples for skater +Provides: python3-skater-doc +%description help +Skater is a python package for interpreting(via post-hoc evaluation/rule extraction) predictive models. +With Skater, you can unpack the internal mechanics of arbitrary models; as long +as you can obtain inputs, and use a function to obtain outputs, you can use +Skater to learn about the models internal decision policies. +The package was originally developed by Aaron Kramer, Pramit Choudhary and internal DataScience Team at DataScience.com +to help enable practitioners explain and interpret predictive "black boxes" preferably in a human interpretable way. + +%prep +%autosetup -n skater-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-skater -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.2-1 +- Package Spec generated |