extractnetvsreadability
ExtractNet is an automated web data extraction tool using machine learning to parse HTML and text data.
This tool can be used in web scraping to automatically extract details from scraped HTML documents. While it's not as accurate as structured extraction using HTML parsing tools like CSS selectors or XPath it can still parse a lot of details.
python-readability is a python package that allows developers to extract the main content of a web page, removing any unnecessary or unwanted elements, such as ads, navigation, and sidebars.
It is based on the algorithm used by the popular web-based service, Readability, and it uses the beautifulsoup4 package to parse the HTML and extract the main content.
Readability is similar to Newspaper in terms that it's extracting HTML data
Example Use
import requests
from extractnet import Extractor
raw_html = requests.get('https://currentsapi.services/en/blog/2019/03/27/python-microframework-benchmark/.html').text
results = Extractor().extract(raw_html)
{'phone_number': '555-555-5555', 'email': 'example@example.com'}
import requests
from readability import document
response = requests.get('http://example.com')
doc = document(response.content)
doc.title()
'example domain'
doc.summary()
"""<html><body><div><body id="readabilitybody">\n<div>\n <h1>example domain</h1>\n
<p>this domain is established to be used for illustrative examples in documents. you may
use this\n domain in examples without prior coordination or asking for permission.</p>
\n <p><a href="http://www.iana.org/domains/example">more information...</a></p>\n</div>
\n</body>\n</div></body></html>"""