requests-htmlvsrvest
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
rvest is a popular R library for web scraping and parsing HTML and XML documents. It is built on top of the xml2 and httr libraries and provides a simple and consistent API for interacting with web pages.
One of the main advantages of using rvest is its simplicity and ease of use. It provides a number of functions that make it easy to extract information from web pages, even for those who are not familiar with web scraping. The html_nodes and html_node functions allow you to select elements from an HTML document using CSS selectors, similar to how you would select elements in JavaScript.
rvest also provides functions for interacting with forms, including html_form, set_values, and submit_form functions. These functions make it easy to navigate through forms and submit data to the server, which can be useful when scraping sites that require authentication or when interacting with dynamic web pages.
rvest also provides functions for parsing XML documents. It includes xml_nodes and xml_node functions, which also use CSS selectors to select elements from an XML document, as well as xml_attrs and xml_attr functions to extract attributes from elements.
Another advantage of rvest is that it provides a way to handle cookies, so you can keep the session alive while scraping a website, and also you can handle redirections with handle_redirects
Example Use
from requests_html import HTMLSession
session = HTMLSession()
r = session.get('https://www.example.com')
# print the HTML content of the page
print(r.html.html)
# use CSS selectors to find specific elements on the page
title = r.html.find('title', first=True)
print(title.text)
library("rvest")
# Rvest can use basic HTTP client to download remote HTML:
tree <- read_html("http://webscraping.fyi/lib/r/rvest")
# or read from string:
tree <- read_html('
<div class="products">
<a href="/product/1">Cat Food</a>
<a href="/product/2">Dog Food</a>
</div>
')
# to parse HTML trees with rvest we use r pipes (the %>% symbol) and html_element function:
# we can use css selectors:
print(tree %>% html_element(".products>a") %>% html_text())
# "[1] "\nCat Food\nDog Food\n""
# or XPath:
print(tree %>% html_element(xpath="//div[@class='products']/a") %>% html_text())
# "[1] "\nCat Food\nDog Food\n""
# Additionally rvest offers many quality of life functions:
# html_text2 - removes trailing and leading spaces and joins values
print(tree %>% html_element("div") %>% html_text2())
# "[1] "Cat Food Dog Food""
# html_attr - selects element's attribute:
print(tree %>% html_element("div") %>% html_attr('class'))
# "products"