%global _empty_manifest_terminate_build 0
Name:		python-category-encoders
Version:	2.6.0
Release:	1
Summary:	A collection of sklearn transformers to encode categorical variables as numeric
License:	BSD
URL:		https://github.com/scikit-learn-contrib/category_encoders
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/06/e4/1a8dabdeb9ef909a1fc7bd69a0c1c88bf300ec025339fb8323d5f0c696cf/category_encoders-2.6.0.tar.gz
BuildArch:	noarch

Requires:	python3-numpy
Requires:	python3-scikit-learn
Requires:	python3-scipy
Requires:	python3-statsmodels
Requires:	python3-pandas
Requires:	python3-patsy

%description
[![Downloads](https://pepy.tech/badge/category-encoders)](https://pepy.tech/project/category-encoders)
[![Downloads](https://pepy.tech/badge/category-encoders/month)](https://pepy.tech/project/category-encoders)
![Test Suite and Linting](https://github.com/scikit-learn-contrib/category_encoders/workflows/Test%20Suite%20and%20Linting/badge.svg)
[![DOI](https://zenodo.org/badge/47077067.svg)](https://zenodo.org/badge/latestdoi/47077067)
A set of scikit-learn-style transformers for encoding categorical 
variables into numeric by means of different techniques.

%package -n python3-category-encoders
Summary:	A collection of sklearn transformers to encode categorical variables as numeric
Provides:	python-category-encoders
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-category-encoders
[![Downloads](https://pepy.tech/badge/category-encoders)](https://pepy.tech/project/category-encoders)
[![Downloads](https://pepy.tech/badge/category-encoders/month)](https://pepy.tech/project/category-encoders)
![Test Suite and Linting](https://github.com/scikit-learn-contrib/category_encoders/workflows/Test%20Suite%20and%20Linting/badge.svg)
[![DOI](https://zenodo.org/badge/47077067.svg)](https://zenodo.org/badge/latestdoi/47077067)
A set of scikit-learn-style transformers for encoding categorical 
variables into numeric by means of different techniques.

%package help
Summary:	Development documents and examples for category-encoders
Provides:	python3-category-encoders-doc
%description help
[![Downloads](https://pepy.tech/badge/category-encoders)](https://pepy.tech/project/category-encoders)
[![Downloads](https://pepy.tech/badge/category-encoders/month)](https://pepy.tech/project/category-encoders)
![Test Suite and Linting](https://github.com/scikit-learn-contrib/category_encoders/workflows/Test%20Suite%20and%20Linting/badge.svg)
[![DOI](https://zenodo.org/badge/47077067.svg)](https://zenodo.org/badge/latestdoi/47077067)
A set of scikit-learn-style transformers for encoding categorical 
variables into numeric by means of different techniques.

%prep
%autosetup -n category-encoders-2.6.0

%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-category-encoders -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 2.6.0-1
- Package Spec generated