%global _empty_manifest_terminate_build 0 Name: python-nagisa Version: 0.2.8 Release: 1 Summary: A Japanese tokenizer based on recurrent neural networks License: MIT License URL: https://github.com/taishi-i/nagisa Source0: https://mirrors.nju.edu.cn/pypi/web/packages/af/81/2c61ffc4c532efc41e9fdd95109c3d844ff0627d212d95adee3744faa6dc/nagisa-0.2.8.tar.gz Requires: python3-six Requires: python3-numpy Requires: python3-DyNet %description [![Python package](https://github.com/taishi-i/nagisa/actions/workflows/python-package.yml/badge.svg)](https://github.com/taishi-i/nagisa/actions/workflows/python-package.yml) [![Build Status](https://app.travis-ci.com/taishi-i/nagisa.svg?branch=master)](https://app.travis-ci.com/taishi-i/nagisa) [![Build status](https://ci.appveyor.com/api/projects/status/6k35hmxl1juf1hqf?svg=true)](https://ci.appveyor.com/project/taishi-i/nagisa) [![Coverage Status](https://coveralls.io/repos/github/taishi-i/nagisa/badge.svg?branch=master)](https://coveralls.io/github/taishi-i/nagisa?branch=master) [![Documentation Status](https://readthedocs.org/projects/nagisa/badge/?version=latest)](https://nagisa.readthedocs.io/en/latest/?badge=latest) [![PyPI](https://img.shields.io/pypi/v/nagisa.svg)](https://pypi.python.org/pypi/nagisa) [![Downloads](https://pepy.tech/badge/nagisa)](https://pepy.tech/project/nagisa) Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following features. - Based on recurrent neural networks. - The word segmentation model uses character- and word-level features [[池田+]](http://www.anlp.jp/proceedings/annual_meeting/2017/pdf_dir/B6-2.pdf). - The POS-tagging model uses tag dictionary information [[Inoue+]](http://www.aclweb.org/anthology/K17-1042). For more details refer to the following links. - The presentation slide at PyCon JP (2019) is available [here](https://speakerdeck.com/taishii/pycon-jp-2019). - The article in Japanese is available [here](https://qiita.com/taishi-i/items/5b9275a606b392f7f58e). - The documentation is available [here](https://nagisa.readthedocs.io/en/latest/?badge=latest). - The presentation slide at NLP Hacks (2022) is available [here](https://speakerdeck.com/taishii/nlphacks). %package -n python3-nagisa Summary: A Japanese tokenizer based on recurrent neural networks Provides: python-nagisa BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip BuildRequires: python3-cffi BuildRequires: gcc BuildRequires: gdb %description -n python3-nagisa [![Python package](https://github.com/taishi-i/nagisa/actions/workflows/python-package.yml/badge.svg)](https://github.com/taishi-i/nagisa/actions/workflows/python-package.yml) [![Build Status](https://app.travis-ci.com/taishi-i/nagisa.svg?branch=master)](https://app.travis-ci.com/taishi-i/nagisa) [![Build status](https://ci.appveyor.com/api/projects/status/6k35hmxl1juf1hqf?svg=true)](https://ci.appveyor.com/project/taishi-i/nagisa) [![Coverage Status](https://coveralls.io/repos/github/taishi-i/nagisa/badge.svg?branch=master)](https://coveralls.io/github/taishi-i/nagisa?branch=master) [![Documentation Status](https://readthedocs.org/projects/nagisa/badge/?version=latest)](https://nagisa.readthedocs.io/en/latest/?badge=latest) [![PyPI](https://img.shields.io/pypi/v/nagisa.svg)](https://pypi.python.org/pypi/nagisa) [![Downloads](https://pepy.tech/badge/nagisa)](https://pepy.tech/project/nagisa) Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following features. - Based on recurrent neural networks. - The word segmentation model uses character- and word-level features [[池田+]](http://www.anlp.jp/proceedings/annual_meeting/2017/pdf_dir/B6-2.pdf). - The POS-tagging model uses tag dictionary information [[Inoue+]](http://www.aclweb.org/anthology/K17-1042). For more details refer to the following links. - The presentation slide at PyCon JP (2019) is available [here](https://speakerdeck.com/taishii/pycon-jp-2019). - The article in Japanese is available [here](https://qiita.com/taishi-i/items/5b9275a606b392f7f58e). - The documentation is available [here](https://nagisa.readthedocs.io/en/latest/?badge=latest). - The presentation slide at NLP Hacks (2022) is available [here](https://speakerdeck.com/taishii/nlphacks). %package help Summary: Development documents and examples for nagisa Provides: python3-nagisa-doc %description help [![Python package](https://github.com/taishi-i/nagisa/actions/workflows/python-package.yml/badge.svg)](https://github.com/taishi-i/nagisa/actions/workflows/python-package.yml) [![Build Status](https://app.travis-ci.com/taishi-i/nagisa.svg?branch=master)](https://app.travis-ci.com/taishi-i/nagisa) [![Build status](https://ci.appveyor.com/api/projects/status/6k35hmxl1juf1hqf?svg=true)](https://ci.appveyor.com/project/taishi-i/nagisa) [![Coverage Status](https://coveralls.io/repos/github/taishi-i/nagisa/badge.svg?branch=master)](https://coveralls.io/github/taishi-i/nagisa?branch=master) [![Documentation Status](https://readthedocs.org/projects/nagisa/badge/?version=latest)](https://nagisa.readthedocs.io/en/latest/?badge=latest) [![PyPI](https://img.shields.io/pypi/v/nagisa.svg)](https://pypi.python.org/pypi/nagisa) [![Downloads](https://pepy.tech/badge/nagisa)](https://pepy.tech/project/nagisa) Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following features. - Based on recurrent neural networks. - The word segmentation model uses character- and word-level features [[池田+]](http://www.anlp.jp/proceedings/annual_meeting/2017/pdf_dir/B6-2.pdf). - The POS-tagging model uses tag dictionary information [[Inoue+]](http://www.aclweb.org/anthology/K17-1042). For more details refer to the following links. - The presentation slide at PyCon JP (2019) is available [here](https://speakerdeck.com/taishii/pycon-jp-2019). - The article in Japanese is available [here](https://qiita.com/taishi-i/items/5b9275a606b392f7f58e). - The documentation is available [here](https://nagisa.readthedocs.io/en/latest/?badge=latest). - The presentation slide at NLP Hacks (2022) is available [here](https://speakerdeck.com/taishii/nlphacks). %prep %autosetup -n nagisa-0.2.8 %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-nagisa -f filelist.lst %dir %{python3_sitearch}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed Apr 12 2023 Python_Bot - 0.2.8-1 - Package Spec generated