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Module for automatic summarization of text documents and HTML pages.

Project Description

https://api.travis-ci.org/miso-belica/sumy.png?branch=master

Here are some other summarizers:

Installation

Make sure you have Python 2.6+/3.2+ and pip (Windows, Linux) installed. Run simply (preferred way):

$ [sudo] pip install sumy

Or for the fresh version:

$ [sudo] pip install git+git://github.com/miso-belica/sumy.git

Or if you have to:

$ wget https://github.com/miso-belica/sumy/archive/master.zip # download the sources
$ unzip master.zip # extract the downloaded file
$ cd sumy-master/
$ [sudo] python setup.py install # install the package

Usage

Sumy contains command line utility for quick summarization of documents.

$ sumy lex-rank --length=10 --url=http://en.wikipedia.org/wiki/Automatic_summarization # what's summarization?
$ sumy luhn --language=czech --url=http://www.zdrojak.cz/clanky/automaticke-zabezpeceni/
$ sumy edmundson --language=czech --length=3% --url=http://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:

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

Python API

Or you can use sumy like a library in your project.

# -*- coding: utf8 -*-

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

from sumy.parsers.html import HtmlParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lsa import LsaSummarizer
from sumy.nlp.stemmers.czech import stem_word
from sumy.utils import get_stop_words


if __name__ == "__main__":
    url = "http://www.zsstritezuct.estranky.cz/clanky/predmety/cteni/jak-naucit-dite-spravne-cist.html"
    parser = HtmlParser.from_url(url, Tokenizer("czech"))

    summarizer = LsaSummarizer(stem_word)
    summarizer.stop_words = get_stop_words("czech")

    for sentence in summarizer(parser.document, 20):
        print(sentence)

Tests

Run tests via

$ nosetests-2.6 && nosetests-3.2 && nosetests-2.7 && nosetests-3.3

Changelog

0.1.0 (2013-10-20)

  • First public release.

Release history Release notifications

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0.7.0

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0.6.0

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0.5.1

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0.5.0

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0.4.1

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0.4.0

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0.3.0

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0.2.1

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0.2.0

This version
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0.1.0

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0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
sumy-0.1.0.zip (43.7 kB) Copy SHA256 hash SHA256 Source None Oct 20, 2013

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