%global _empty_manifest_terminate_build 0
Name:		python-text-normalizer
Version:	0.1.3
Release:	1
Summary:	Yoctol Natural Language Text Normalizer
License:	MIT
URL:		https://github.com/Yoctol/text-normalizer
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b7/98/b49628d90d5793e7369e25d6a84f9ca4a1fc6472d848d15daa9bf9129ad7/text-normalizer-0.1.3.tar.gz
BuildArch:	noarch


%description
# text-normalizer

[![travis][travis-image]][travis-url]
[![pypi][pypi-image]][pypi-url]

[travis-image]: https://img.shields.io/travis/Yoctol/text-normalizer.svg?style=flat
[travis-url]: https://travis-ci.org/Yoctol/text-normalizer
[pypi-image]: https://img.shields.io/pypi/v/text-normalizer.svg?style=flat
[pypi-url]: https://pypi.python.org/pypi/text-normalizer

Normalize your Text String. 
It is a python package that help you normalize your text data and recover it.

## Install
Use Python3
```
> pip install text-normalizer
```
## Usage
```python
from text_normalizer.text_normalizer_collection_library import chinese_charactor_text_normalizer_collection_2


input_sentence = "   我在85.33度C買了一杯900──1000元的咖啡    《ohoh》？？ m_m"
nor_sentence, meta = chinese_charactor_text_normalizer_collection_2.normalize(input_sentence)
print(nor_sentence)
> "我在_float_度c買了一杯_int_-_int_元的咖啡 <ohoh>?? m_m"

de_sentence = chinese_charactor_text_normalizer_collection_2.denormalize(nor_sentence, meta)
print(de_sentence)
> "我在85.33度C買了一杯900──1000元的咖啡 《ohoh》？？ m_m",

```

%package -n python3-text-normalizer
Summary:	Yoctol Natural Language Text Normalizer
Provides:	python-text-normalizer
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-text-normalizer
# text-normalizer

[![travis][travis-image]][travis-url]
[![pypi][pypi-image]][pypi-url]

[travis-image]: https://img.shields.io/travis/Yoctol/text-normalizer.svg?style=flat
[travis-url]: https://travis-ci.org/Yoctol/text-normalizer
[pypi-image]: https://img.shields.io/pypi/v/text-normalizer.svg?style=flat
[pypi-url]: https://pypi.python.org/pypi/text-normalizer

Normalize your Text String. 
It is a python package that help you normalize your text data and recover it.

## Install
Use Python3
```
> pip install text-normalizer
```
## Usage
```python
from text_normalizer.text_normalizer_collection_library import chinese_charactor_text_normalizer_collection_2


input_sentence = "   我在85.33度C買了一杯900──1000元的咖啡    《ohoh》？？ m_m"
nor_sentence, meta = chinese_charactor_text_normalizer_collection_2.normalize(input_sentence)
print(nor_sentence)
> "我在_float_度c買了一杯_int_-_int_元的咖啡 <ohoh>?? m_m"

de_sentence = chinese_charactor_text_normalizer_collection_2.denormalize(nor_sentence, meta)
print(de_sentence)
> "我在85.33度C買了一杯900──1000元的咖啡 《ohoh》？？ m_m",

```

%package help
Summary:	Development documents and examples for text-normalizer
Provides:	python3-text-normalizer-doc
%description help
# text-normalizer

[![travis][travis-image]][travis-url]
[![pypi][pypi-image]][pypi-url]

[travis-image]: https://img.shields.io/travis/Yoctol/text-normalizer.svg?style=flat
[travis-url]: https://travis-ci.org/Yoctol/text-normalizer
[pypi-image]: https://img.shields.io/pypi/v/text-normalizer.svg?style=flat
[pypi-url]: https://pypi.python.org/pypi/text-normalizer

Normalize your Text String. 
It is a python package that help you normalize your text data and recover it.

## Install
Use Python3
```
> pip install text-normalizer
```
## Usage
```python
from text_normalizer.text_normalizer_collection_library import chinese_charactor_text_normalizer_collection_2


input_sentence = "   我在85.33度C買了一杯900──1000元的咖啡    《ohoh》？？ m_m"
nor_sentence, meta = chinese_charactor_text_normalizer_collection_2.normalize(input_sentence)
print(nor_sentence)
> "我在_float_度c買了一杯_int_-_int_元的咖啡 <ohoh>?? m_m"

de_sentence = chinese_charactor_text_normalizer_collection_2.denormalize(nor_sentence, meta)
print(de_sentence)
> "我在85.33度C買了一杯900──1000元的咖啡 《ohoh》？？ m_m",

```

%prep
%autosetup -n text-normalizer-0.1.3

%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-text-normalizer -f filelist.lst
%dir %{python3_sitelib}/*

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

%changelog
* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.3-1
- Package Spec generated