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rvestvsxmltodict

MIT 17 1 1,455
629.3 thousand (month) Nov 22 2014 1.0.4(1 year, 7 months ago)
5,361 1 94 MIT
0.13.0(1 year, 10 months ago) Jul 30 2007 44.7 million (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

xmltodict is a Python library that allows you to work with XML data as if it were JSON. It allows you to parse XML documents and convert them to dictionaries, which can then be easily manipulated using standard dictionary operations.

You can also use the library to convert a dictionary back into an XML document. xmltodict is built on top of the popular lxml library and provides a simple, intuitive API for working with XML data.

Note that despite using lxml conversion speeds can be quite slow for large XML documents and in web scraping this should be used to parse specific snippets instead of whole HTML documents.

xmltodict pairs well with JSON parsing tools like jmespath or jsonpath. Alternatively, it can be used in reverse mode to parse JSON documents using HTML parsing tools like CSS selectors and XPath.

It can be installed via pip by running pip install xmltodict command.

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"
import xmltodict

xml_string = """
<book>
    <title>The Great Gatsby</title>
    <author>F. Scott Fitzgerald</author>
    <publisher>Charles Scribner's Sons</publisher>
    <publication_date>1925</publication_date>
</book>
"""

book_dict = xmltodict.parse(xml_string)
print(book_dict)
{'book': {'title': 'The Great Gatsby',
'author': 'F. Scott Fitzgerald',
'publisher': "Charles Scribner's Sons",
'publication_date': '1925'}}

# and to reverse:
book_xml = xmltodict.unparse(book_dict)
print(book_xml)

# the xml can be loaded and parsed using parsel or beautifulsoup:
from parsel import Selector
sel = Selector(book_xml)
print(sel.css('publication_date::text').get())
'1925'

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