choppervsrvest
Chopper is a tool to extract elements from HTML by preserving ancestors and CSS rules.
Compared to other HTML parsers Chopper is designed to retain original HTML tree but eliminate elements that do not match parsing rules. Meaning, we can parse HTML elements and keep thei structure for machine learning or other tasks where data structure is needed as well as the data value.
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
HTML = """
<html>
<head>
<title>Test</title>
</head>
<body>
<div id="header"></div>
<div id="main">
<div class="iwantthis">
HELLO WORLD
<a href="/nope">Do not want</a>
</div>
</div>
<div id="footer"></div>
</body>
</html>
"""
CSS = """
div { border: 1px solid black; }
div#main { color: blue; }
div.iwantthis { background-color: red; }
a { color: green; }
div#footer { border-top: 2px solid red; }
"""
extractor = Extractor.keep('//div[@class="iwantthis"]').discard('//a')
html, css = extractor.extract(HTML, CSS)
# will result in:
html
"""
<html>
<body>
<div id="main">
<div class="iwantthis">
HELLO WORLD
</div>
</div>
</body>
</html>"""
css
"""
div{border:1px solid black;}
div#main{color:blue;}
div.iwantthis{background-color:red;}
"""
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"