%global _empty_manifest_terminate_build 0
Name:		python-sumy
Version:	0.11.0
Release:	1
Summary:	Module for automatic summarization of text documents and HTML pages.
License:	Apache License, Version 2.0
URL:		https://github.com/miso-belica/sumy
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/df/fd/59098f716c39422d5ca47caa97ef44cd2829384bfdf22e1420e839fde3c1/sumy-0.11.0.tar.gz
BuildArch:	noarch

Requires:	python3-docopt
Requires:	python3-breadability
Requires:	python3-requests
Requires:	python3-pycountry
Requires:	python3-nltk
Requires:	python3-pyarabic
Requires:	python3-jieba
Requires:	python3-greek-stemmer-pos
Requires:	python3-hebrew-tokenizer
Requires:	python3-tinysegmenter
Requires:	python3-konlpy
Requires:	python3-numpy
Requires:	python3-numpy

%description
# Automatic text summarizer


[![image](https://github.com/miso-belica/sumy/actions/workflows/run-tests.yml/badge.svg)](https://github.com/miso-belica/sumy/actions/workflows/run-tests.yml)
[![GitPod Ready-to-Code](https://img.shields.io/badge/Gitpod-Ready--to--Code-blue?logo=gitpod)](https://gitpod.io/#https://github.com/miso-belica/sumy) 

Simple library and command line utility for extracting summary from HTML
pages or plain texts. The package also contains simple evaluation
framework for text summaries. Implemented summarization methods are described in the [documentation](docs/summarizators.md). I also maintain a list of [alternative implementations](docs/alternatives.md) of the summarizers in various programming languages.

## Is my natural language supported?
There is a [good chance](docs/index.md#Tokenizer) it is. But if not it is [not too hard to add](docs/how-to-add-new-language.md) it.

## Installation

Make sure you have [Python](http://www.python.org/) 3.6+ and
[pip](https://crate.io/packages/pip/)
([Windows](http://docs.python-guide.org/en/latest/starting/install/win/),
[Linux](http://docs.python-guide.org/en/latest/starting/install/linux/))
installed. Run simply (preferred way):

```sh
$ [sudo] pip install sumy
$ [sudo] pip install git+git://github.com/miso-belica/sumy.git  # for the fresh version
```

## Usage

Thanks to some good soul out there, the easiest way to try sumy is in your browser at https://huggingface.co/spaces/issam9/sumy_space

Sumy contains command line utility for quick summarization of documents.

```sh
$ sumy lex-rank --length=10 --url=https://en.wikipedia.org/wiki/Automatic_summarization # what's summarization?
$ sumy lex-rank --language=uk --length=30 --url=https://uk.wikipedia.org/wiki/Україна
$ sumy luhn --language=czech --url=https://www.zdrojak.cz/clanky/automaticke-zabezpeceni/
$ sumy edmundson --language=czech --length=3% --url=https://cs.wikipedia.org/wiki/Bitva_u_Lipan
$ sumy --help # for more info
```

Various evaluation methods for some summarization method can be executed
by commands below:

```sh
$ sumy_eval lex-rank reference_summary.txt --url=https://en.wikipedia.org/wiki/Automatic_summarization
$ sumy_eval lsa reference_summary.txt --language=czech --url=https://www.zdrojak.cz/clanky/automaticke-zabezpeceni/
$ sumy_eval edmundson reference_summary.txt --language=czech --url=https://cs.wikipedia.org/wiki/Bitva_u_Lipan
$ sumy_eval --help # for more info
```

If you don't want to bother by the installation, you can try it as a container.

```sh
$ docker run --rm misobelica/sumy lex-rank --length=10 --url=https://en.wikipedia.org/wiki/Automatic_summarization
```

## Python API

Or you can use sumy like a library in your project. Create file `sumy_example.py` ([don't name it `sumy.py`](https://stackoverflow.com/questions/41334622/python-sumy-no-module-named-sumy-parsers-html)) with the code below to test it.

```python
# -*- coding: utf-8 -*-

from __future__ import absolute_import
from __future__ import division, print_function, unicode_literals

from sumy.parsers.html import HtmlParser
from sumy.parsers.plaintext import PlaintextParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lsa import LsaSummarizer as Summarizer
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words


LANGUAGE = "english"
SENTENCES_COUNT = 10


if __name__ == "__main__":
    url = "https://en.wikipedia.org/wiki/Automatic_summarization"
    parser = HtmlParser.from_url(url, Tokenizer(LANGUAGE))
    # or for plain text files
    # parser = PlaintextParser.from_file("document.txt", Tokenizer(LANGUAGE))
    # parser = PlaintextParser.from_string("Check this out.", Tokenizer(LANGUAGE))
    stemmer = Stemmer(LANGUAGE)

    summarizer = Summarizer(stemmer)
    summarizer.stop_words = get_stop_words(LANGUAGE)

    for sentence in summarizer(parser.document, SENTENCES_COUNT):
        print(sentence)
```

## Interesting projects using sumy

I found some interesting projects while browsing the internet or sometimes people wrote me an e-mail with questions, and I was curious how they use the sumy :)

* [Learning to generate questions from text](https://software.intel.com/en-us/articles/using-natural-language-processing-for-smart-question-generation) - https://github.com/adityasarvaiya/Automatic_Question_Generation
* Summarize your video to any duration - https://github.com/aswanthkoleri/VideoMash and similar https://github.com/OpenGenus/vidsum
* Tool for collectively summarizing large discussions - https://github.com/amyxzhang/wikum


%package -n python3-sumy
Summary:	Module for automatic summarization of text documents and HTML pages.
Provides:	python-sumy
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-sumy
# Automatic text summarizer


[![image](https://github.com/miso-belica/sumy/actions/workflows/run-tests.yml/badge.svg)](https://github.com/miso-belica/sumy/actions/workflows/run-tests.yml)
[![GitPod Ready-to-Code](https://img.shields.io/badge/Gitpod-Ready--to--Code-blue?logo=gitpod)](https://gitpod.io/#https://github.com/miso-belica/sumy) 

Simple library and command line utility for extracting summary from HTML
pages or plain texts. The package also contains simple evaluation
framework for text summaries. Implemented summarization methods are described in the [documentation](docs/summarizators.md). I also maintain a list of [alternative implementations](docs/alternatives.md) of the summarizers in various programming languages.

## Is my natural language supported?
There is a [good chance](docs/index.md#Tokenizer) it is. But if not it is [not too hard to add](docs/how-to-add-new-language.md) it.

## Installation

Make sure you have [Python](http://www.python.org/) 3.6+ and
[pip](https://crate.io/packages/pip/)
([Windows](http://docs.python-guide.org/en/latest/starting/install/win/),
[Linux](http://docs.python-guide.org/en/latest/starting/install/linux/))
installed. Run simply (preferred way):

```sh
$ [sudo] pip install sumy
$ [sudo] pip install git+git://github.com/miso-belica/sumy.git  # for the fresh version
```

## Usage

Thanks to some good soul out there, the easiest way to try sumy is in your browser at https://huggingface.co/spaces/issam9/sumy_space

Sumy contains command line utility for quick summarization of documents.

```sh
$ sumy lex-rank --length=10 --url=https://en.wikipedia.org/wiki/Automatic_summarization # what's summarization?
$ sumy lex-rank --language=uk --length=30 --url=https://uk.wikipedia.org/wiki/Україна
$ sumy luhn --language=czech --url=https://www.zdrojak.cz/clanky/automaticke-zabezpeceni/
$ sumy edmundson --language=czech --length=3% --url=https://cs.wikipedia.org/wiki/Bitva_u_Lipan
$ sumy --help # for more info
```

Various evaluation methods for some summarization method can be executed
by commands below:

```sh
$ sumy_eval lex-rank reference_summary.txt --url=https://en.wikipedia.org/wiki/Automatic_summarization
$ sumy_eval lsa reference_summary.txt --language=czech --url=https://www.zdrojak.cz/clanky/automaticke-zabezpeceni/
$ sumy_eval edmundson reference_summary.txt --language=czech --url=https://cs.wikipedia.org/wiki/Bitva_u_Lipan
$ sumy_eval --help # for more info
```

If you don't want to bother by the installation, you can try it as a container.

```sh
$ docker run --rm misobelica/sumy lex-rank --length=10 --url=https://en.wikipedia.org/wiki/Automatic_summarization
```

## Python API

Or you can use sumy like a library in your project. Create file `sumy_example.py` ([don't name it `sumy.py`](https://stackoverflow.com/questions/41334622/python-sumy-no-module-named-sumy-parsers-html)) with the code below to test it.

```python
# -*- coding: utf-8 -*-

from __future__ import absolute_import
from __future__ import division, print_function, unicode_literals

from sumy.parsers.html import HtmlParser
from sumy.parsers.plaintext import PlaintextParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lsa import LsaSummarizer as Summarizer
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words


LANGUAGE = "english"
SENTENCES_COUNT = 10


if __name__ == "__main__":
    url = "https://en.wikipedia.org/wiki/Automatic_summarization"
    parser = HtmlParser.from_url(url, Tokenizer(LANGUAGE))
    # or for plain text files
    # parser = PlaintextParser.from_file("document.txt", Tokenizer(LANGUAGE))
    # parser = PlaintextParser.from_string("Check this out.", Tokenizer(LANGUAGE))
    stemmer = Stemmer(LANGUAGE)

    summarizer = Summarizer(stemmer)
    summarizer.stop_words = get_stop_words(LANGUAGE)

    for sentence in summarizer(parser.document, SENTENCES_COUNT):
        print(sentence)
```

## Interesting projects using sumy

I found some interesting projects while browsing the internet or sometimes people wrote me an e-mail with questions, and I was curious how they use the sumy :)

* [Learning to generate questions from text](https://software.intel.com/en-us/articles/using-natural-language-processing-for-smart-question-generation) - https://github.com/adityasarvaiya/Automatic_Question_Generation
* Summarize your video to any duration - https://github.com/aswanthkoleri/VideoMash and similar https://github.com/OpenGenus/vidsum
* Tool for collectively summarizing large discussions - https://github.com/amyxzhang/wikum


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


[![image](https://github.com/miso-belica/sumy/actions/workflows/run-tests.yml/badge.svg)](https://github.com/miso-belica/sumy/actions/workflows/run-tests.yml)
[![GitPod Ready-to-Code](https://img.shields.io/badge/Gitpod-Ready--to--Code-blue?logo=gitpod)](https://gitpod.io/#https://github.com/miso-belica/sumy) 

Simple library and command line utility for extracting summary from HTML
pages or plain texts. The package also contains simple evaluation
framework for text summaries. Implemented summarization methods are described in the [documentation](docs/summarizators.md). I also maintain a list of [alternative implementations](docs/alternatives.md) of the summarizers in various programming languages.

## Is my natural language supported?
There is a [good chance](docs/index.md#Tokenizer) it is. But if not it is [not too hard to add](docs/how-to-add-new-language.md) it.

## Installation

Make sure you have [Python](http://www.python.org/) 3.6+ and
[pip](https://crate.io/packages/pip/)
([Windows](http://docs.python-guide.org/en/latest/starting/install/win/),
[Linux](http://docs.python-guide.org/en/latest/starting/install/linux/))
installed. Run simply (preferred way):

```sh
$ [sudo] pip install sumy
$ [sudo] pip install git+git://github.com/miso-belica/sumy.git  # for the fresh version
```

## Usage

Thanks to some good soul out there, the easiest way to try sumy is in your browser at https://huggingface.co/spaces/issam9/sumy_space

Sumy contains command line utility for quick summarization of documents.

```sh
$ sumy lex-rank --length=10 --url=https://en.wikipedia.org/wiki/Automatic_summarization # what's summarization?
$ sumy lex-rank --language=uk --length=30 --url=https://uk.wikipedia.org/wiki/Україна
$ sumy luhn --language=czech --url=https://www.zdrojak.cz/clanky/automaticke-zabezpeceni/
$ sumy edmundson --language=czech --length=3% --url=https://cs.wikipedia.org/wiki/Bitva_u_Lipan
$ sumy --help # for more info
```

Various evaluation methods for some summarization method can be executed
by commands below:

```sh
$ sumy_eval lex-rank reference_summary.txt --url=https://en.wikipedia.org/wiki/Automatic_summarization
$ sumy_eval lsa reference_summary.txt --language=czech --url=https://www.zdrojak.cz/clanky/automaticke-zabezpeceni/
$ sumy_eval edmundson reference_summary.txt --language=czech --url=https://cs.wikipedia.org/wiki/Bitva_u_Lipan
$ sumy_eval --help # for more info
```

If you don't want to bother by the installation, you can try it as a container.

```sh
$ docker run --rm misobelica/sumy lex-rank --length=10 --url=https://en.wikipedia.org/wiki/Automatic_summarization
```

## Python API

Or you can use sumy like a library in your project. Create file `sumy_example.py` ([don't name it `sumy.py`](https://stackoverflow.com/questions/41334622/python-sumy-no-module-named-sumy-parsers-html)) with the code below to test it.

```python
# -*- coding: utf-8 -*-

from __future__ import absolute_import
from __future__ import division, print_function, unicode_literals

from sumy.parsers.html import HtmlParser
from sumy.parsers.plaintext import PlaintextParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lsa import LsaSummarizer as Summarizer
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words


LANGUAGE = "english"
SENTENCES_COUNT = 10


if __name__ == "__main__":
    url = "https://en.wikipedia.org/wiki/Automatic_summarization"
    parser = HtmlParser.from_url(url, Tokenizer(LANGUAGE))
    # or for plain text files
    # parser = PlaintextParser.from_file("document.txt", Tokenizer(LANGUAGE))
    # parser = PlaintextParser.from_string("Check this out.", Tokenizer(LANGUAGE))
    stemmer = Stemmer(LANGUAGE)

    summarizer = Summarizer(stemmer)
    summarizer.stop_words = get_stop_words(LANGUAGE)

    for sentence in summarizer(parser.document, SENTENCES_COUNT):
        print(sentence)
```

## Interesting projects using sumy

I found some interesting projects while browsing the internet or sometimes people wrote me an e-mail with questions, and I was curious how they use the sumy :)

* [Learning to generate questions from text](https://software.intel.com/en-us/articles/using-natural-language-processing-for-smart-question-generation) - https://github.com/adityasarvaiya/Automatic_Question_Generation
* Summarize your video to any duration - https://github.com/aswanthkoleri/VideoMash and similar https://github.com/OpenGenus/vidsum
* Tool for collectively summarizing large discussions - https://github.com/amyxzhang/wikum


%prep
%autosetup -n sumy-0.11.0

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

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

%changelog
* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.11.0-1
- Package Spec generated