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MIT 214 2 13,558
1.1 million (month) Feb 25 2018 0.10.0(5 years ago)
1,821 8 83 BSD-2-Clause
6.0.11(3 months ago) Jun 15 2007 3.4 million (month)

requests-html is a Python package that allows you to easily make HTTP requests and parse the HTML content of web pages. It is built on top of the popular requests package and uses the html parser from the lxml library, which makes it fast and efficient. This package is designed to provide a simple and convenient API for web scraping, and it supports features such as JavaScript rendering, CSS selectors, and form submissions.

It also offers a lot of functionalities such as cookie, session, and proxy support, which makes it an easy-to-use package for web scraping and web automation tasks.

In short requests-html offers:

  • Full JavaScript support!
  • CSS Selectors (a.k.a jQuery-style, thanks to PyQuery).
  • XPath Selectors, for the faint of heart.
  • Mocked user-agent (like a real web browser).
  • Automatic following of redirects.
  • Connection–pooling and cookie persistence.
  • The Requests experience you know and love, with magical parsing abilities.
  • Async Support

feedparser is a Python module for downloading and parsing syndicated feeds. It can handle 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, and CDF feeds. It also parses several popular extension modules, including Dublin Core and Apple’s iTunes extensions.

To use Universal Feed Parser, you will need Python 3.6 or later. Universal Feed Parser is not meant to run standalone; it is a module for you to use as part of a larger Python program.

feedparser can be used to scrape data feeds as it can download them and parse the XML structured data.

Example Use

from requests_html import HTMLSession

session = HTMLSession()
r = session.get('')

# print the HTML content of the page

# use CSS selectors to find specific elements on the page
title = r.html.find('title', first=True)
import feedparser

# the feed can be loaded from a remote URL
data = feedparser.parse('')
# local path
data = feedparser.parse('/home/user/data.xml')
# or raw string
data = feedparser.parse('<xml>...</xml>')

# the result dataset is a nested python dictionary containing feed data:

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