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rvestvsparsel

MIT 17 1 1,455
629.3 thousand (month) Nov 22 2014 1.0.4(1 year, 7 months ago)
1,067 8 36 BSD
1.9.0(22 days ago) Jul 26 2019 1.5 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

parsel is a library for parsing HTML and XML using selectors, similar to beautifulsoup. It is built on top of the lxml library and allows for easy extraction of data from HTML and XML files using selectors, similar to how you would use CSS selectors in web development. It is a light-weight library which is specifically designed for web scraping and parsing, so it is more efficient and faster than beautifulsoup in some use cases.

Some of the key features of parsel include:

  • CSS selector & XPath selector support:
    Two most common html parsing path languages are both supported in parsel. This allows selecting attributes, tags, text and complex matching rules that use regular expressions or XPath functions.
  • Modifying data:
    parsel allows you to modify the contents of an element, remove elements or add new elements to a document.
  • Support for both HTML and XML:
    parsel supports both HTML and XML documents and you can use the same selectors for both formats.

It is easy to use and less verbose than beautifulsoup, so it's quite popular among the developers who are working with Web scraping projects and parse data from large volume of web pages.

Highlights


css-selectorsxpath-selectors

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 parsel import Selector

# this is our HTML page:
html = """
<head>
  <title>Hello World!</title>
</head>
<body>
  <div id="product">
    <h1>Product Title</h1>
    <p>paragraph 1</p>
    <p>paragraph2</p>
    <span class="price">$10</span>
  </div>
</body>
"""

selector = Selector(html)

# we can use CSS selectors:
selector.css("#product .price::text").get()
"$10"

# or XPath:
selector.xpath('//span[@class="price"]').get()
"$10"

# or get all matching elements:
print(selector.css("#product p::text").getall())
["paragraph 1", "paragraph2"]

# parsel also comes with utility methods like regular expression parsing:
selector.xpath('//span[@class="price"]').re("\d+")
["10"]

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