newspapervssumy
newspaper is a Python package that allows developers to easily extract text, images, and videos from articles on the web.
It is designed to be fast, easy to use, and compatible with a wide variety of websites. It uses advanced algorithms to extract relevant information and metadata from articles, and it also supports several languages.
newspaper includes a http client or can ingest pre-scraped HTML documents.
sumy is a Python library for automatic summarization of text documents. It can be used to extract summaries from various input formats such as plaintext, HTML, and URLs. It supports multiple languages and multiple summarization algorithms, including Latent Semantic Analysis (LSA), Luhn, Edmundson, TextRank, and SumBasic.
Example Use
from newspaper import Article
# Create a new article object
article = Article('https://www.example.com/article')
# Download the article
article.download()
# Parse the article
article.parse()
# Print the article text
print(article.text)
# Print the article title
print(article.title)
# Print the article authors
print(article.authors)
# Print the article publication date
print(article.publish_date)
# -*- 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)