extractnetvsnewspaper
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.
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.
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'}
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)