rvestvsnokogiri
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
Nokogiri is a Ruby gem that provides a simple and powerful way to parse and search XML and HTML documents. It is built on top of the underlying C library libxml2, which is known for its speed and reliability.
Nokogiri provides a simple and intuitive API for parsing and searching XML and HTML documents, and it is widely used in the Ruby ecosystem for web scraping and data extraction.
One of the main features of Nokogiri is its ability to search and navigate through XML and HTML documents using a CSS or XPath selectors.
Nokogiri also provides a variety of other features that can simplify the process of working with XML and HTML documents. It can automatically handle character encodings and normalize documents, it can parse and search large documents with low memory usage, and it can validate documents against a DTD or schema.
Highlights
Example Use
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"
require 'nokogiri'
html_string = '<html><head><title>Page Title</title></head><body><h1 class="header-class">Hello World!</h1><p>This is a sample webpage.</p></body></html>'
# Parse the HTML string
doc = Nokogiri::HTML(html_string)
# Extract the class attribute of h1 tag using CSS selector
h1_class = doc.css("h1")[0]['class']
# or XPath
h1_class = doc.xpath("//h1")[0]['class']
puts "H1 class: #{h1_class}"