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rvestvsselectolax

MIT 17 1 1,455
629.3 thousand (month) Nov 22 2014 1.0.4(1 year, 7 months ago)
946 1 15 MIT license
0.3.21(26 days ago) Mar 01 2018 112.3 thousand (month)

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

selectolax is a fast and lightweight library for parsing HTML and XML documents in Python. It is designed to be a drop-in replacement for the popular BeautifulSoup library, with significantly faster performance.

selectolax uses a Cython-based parser to quickly parse and navigate through HTML and XML documents. It provides a simple and intuitive API for working with the document's structure, similar to BeautifulSoup.

To use selectolax, you first need to install it via pip by running pip install selectolax``. Once it is installed, you can use theselectolax.html.fromstring()function to parse an HTML document and create a selectolax object. For example:

from selectolax.parser import HTMLParser

html_string = "<html><body>Hello, World!</body></html>"
root = HTMLParser(html_string).root
print(root.tag) # html
You can also useselectolax.html.fromstring()with file-like objects, bytes or file paths, as well asselectolax.xml.fromstring()`` for parsing XML documents.

Once you have a selectolax object, you can use the select() method to search for elements in the document using CSS selectors, similar to BeautifulSoup. For example:

body = root.select("body")[0]
print(body.text()) # "Hello, World!"

Like BeautifulSoups find and find_all methods selectolax also supports searching using the search()`` method, which returns the first matching element, and thesearch_all()`` method, which returns all matching elements.

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"
from selectolax.parser import HTMLParser

html_string = "<html><body>Hello, World!</body></html>"
root = HTMLParser(html_string).root
print(root.tag) # html

# use css selectors:
body = root.select("body")[0]
print(body.text()) # "Hello, World!"

# find first matching element:
body = root.search("body")
print(body.text()) # "Hello, World!"

# or all matching elements:
html_string = "<html><body><p>paragraph1</p><p>paragraph2</p></body></html>"
root = HTMLParser(html_string).root
for el in root.search_all("p"):
  print(el.text()) 
# will print:
# paragraph 1
# paragraph 2

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