From 014a207d21076c6e9584a332c800bbc885a695b4 Mon Sep 17 00:00:00 2001
From: CoprDistGit <infra@openeuler.org>
Date: Wed, 10 May 2023 05:11:49 +0000
Subject: automatic import of python-targeted

---
 python-targeted.spec | 129 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 129 insertions(+)
 create mode 100644 python-targeted.spec

(limited to 'python-targeted.spec')

diff --git a/python-targeted.spec b/python-targeted.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-targeted
+Version:	0.0.30
+Release:	1
+Summary:	Python package for targeted inference.
+License:	Apache Software License
+URL:		https://targetlib.org/python/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/69/41/eb97302d2ab4912cfb04c6f4bb29e690321e4c52490c314ee5b4808df1c3/targeted-0.0.30.tar.gz
+BuildArch:	noarch
+
+
+%description
+# Targeted Learning Library
+
+Python package for targeted inference.
+
+**targeted** provides a number of methods for semi-parametric
+estimation.  The library also contains implementations of various
+parametric models (including different discrete choice models) and
+model diagnostics tools.
+
+The implemention currently includes
+- **Risk regression models** with binary exposure
+  (Richardson et al., 2017, doi:10.1080/01621459.2016.1192546)
+- **Augmented Inverse Probability Weighted** estimators for missing
+  data and causal inference (Bang and Robins, 2005,
+  doi:10.1111/j.1541-0420.2005.00377.x)
+- Model diagnostics based on **cumulative residuals** methods
+- Efficient weighted **Pooled Adjacent Violator Algorithms**
+- **Nested multinomial logit** models
+
+Documentation and tutorials can be found at https://targetlib.org/python/.
+
+%package -n python3-targeted
+Summary:	Python package for targeted inference.
+Provides:	python-targeted
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-targeted
+# Targeted Learning Library
+
+Python package for targeted inference.
+
+**targeted** provides a number of methods for semi-parametric
+estimation.  The library also contains implementations of various
+parametric models (including different discrete choice models) and
+model diagnostics tools.
+
+The implemention currently includes
+- **Risk regression models** with binary exposure
+  (Richardson et al., 2017, doi:10.1080/01621459.2016.1192546)
+- **Augmented Inverse Probability Weighted** estimators for missing
+  data and causal inference (Bang and Robins, 2005,
+  doi:10.1111/j.1541-0420.2005.00377.x)
+- Model diagnostics based on **cumulative residuals** methods
+- Efficient weighted **Pooled Adjacent Violator Algorithms**
+- **Nested multinomial logit** models
+
+Documentation and tutorials can be found at https://targetlib.org/python/.
+
+%package help
+Summary:	Development documents and examples for targeted
+Provides:	python3-targeted-doc
+%description help
+# Targeted Learning Library
+
+Python package for targeted inference.
+
+**targeted** provides a number of methods for semi-parametric
+estimation.  The library also contains implementations of various
+parametric models (including different discrete choice models) and
+model diagnostics tools.
+
+The implemention currently includes
+- **Risk regression models** with binary exposure
+  (Richardson et al., 2017, doi:10.1080/01621459.2016.1192546)
+- **Augmented Inverse Probability Weighted** estimators for missing
+  data and causal inference (Bang and Robins, 2005,
+  doi:10.1111/j.1541-0420.2005.00377.x)
+- Model diagnostics based on **cumulative residuals** methods
+- Efficient weighted **Pooled Adjacent Violator Algorithms**
+- **Nested multinomial logit** models
+
+Documentation and tutorials can be found at https://targetlib.org/python/.
+
+%prep
+%autosetup -n targeted-0.0.30
+
+%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-targeted -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.30-1
+- Package Spec generated
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