untanglevsrvest
untangle is a simple library for parsing XML documents in Python. It allows you to access data in an XML file as if it were a Python object, making it easy to work with the data in your code.
To use untangle, you first need to install it via pip by running pip install untangle``.
Once it is installed, you can use theuntangle.parse()`` function to parse an XML file and create a Python object.
For example:
import untangle
obj = untangle.parse("example.xml")
print(obj.root.element.child)
You can also pass a file-like object or a string containing XML data to the untangle.parse() function. Once you have an untangle object, you can access elements in the XML document using dot notation.
You can also access the attributes of an element by using attrib property, eg. `obj.root.element['attrib_name']`` untangle also supports xpath-like syntax to access the elements, obj.root.xpath("path/to/element")
It also supports iteration over the elements using obj.root.element.children
for child in obj.root.element.children:
print(child)
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
import untangle
obj = untangle.parse("example.xml")
print(obj.root.element.child)
# access attributes:
print(obj.root.element['attrib_name'])
# use xpath:
element = obj.root.xpath("path/to/element")
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"