gofeedvssumy
The gofeed library is a robust feed parser that supports parsing both RSS, Atom and JSON feeds. The library provides a universal gofeed.Parser that will parse and convert all feed types into a hybrid gofeed.Feed model.
You also have the option of utilizing the feed specific atom.Parser or rss.Parser or json.Parser parsers which generate atom. Feed , rss.Feed and json.Feed respectively.
Supported feed types:
- RSS 0.90
- Netscape RSS 0.91
- Userland RSS 0.91
- RSS 0.92
- RSS 0.93
- RSS 0.94
- RSS 1.0
- RSS 2.0
- Atom 0.3
- Atom 1.0
- JSON 1.0
- JSON 1.1
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
// parse feed from URL
fp := gofeed.NewParser()
fp.UserAgent = "MyCustomAgent 1.0" // we can modify http client with custom headers etc.
feed, _ := fp.ParseURL("http://feeds.twit.tv/twit.xml")
fmt.Println(feed.Title)
// parse feed from string
feedData := `<rss version="2.0">
<channel>
<title>Sample Feed</title>
</channel>
</rss>`
fp := gofeed.NewParser()
feed, _ := fp.ParseString(feedData)
fmt.Println(feed.Title)
// or file
file, _ := os.Open("/path/to/a/file.xml")
defer file.Close()
fp := gofeed.NewParser()
feed, _ := fp.Parse(file)
fmt.Println(feed.Title)
# -*- 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)