extractnetvsphoton
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.
Photon is a Python library for web scraping. It is designed to be lightweight and fast, and can be used to extract data from websites and web pages. Photon can extract the following data while crawling:
- URLs (in-scope & out-of-scope)
- URLs with parameters (example.com/gallery.php?id=2)
- Intel (emails, social media accounts, amazon buckets etc.)
- Files (pdf, png, xml etc.)
- Secret keys (auth/API keys & hashes)
- JavaScript files & Endpoints present in them
- Strings matching custom regex pattern
- Subdomains & DNS related data
The extracted information is saved in an organized manner or can be exported as json.
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 photon import Photon
#Create a new Photon instance
ph = Photon()
#Extract data from a specific element of the website
url = "https://www.example.com"
selector = "div.main"
data = ph.get_data(url, selector)
#Print the extracted data
print(data)
#Extract data from multiple websites asynchronously
urls = ["https://www.example1.com", "https://www.example2.com"]
data = ph.get_data_async(urls)