pyqueryvsrvest
PyQuery is a Python library for working with XML and HTML documents. It is similar to BeautifulSoup and is often used as a drop-in replacement for it.
PyQuery is inspired by javascript's jQuery and uses similar API allowing selecting of HTML nodes through CSS selectors. This makes it easy for developers who are already familiar with jQuery to use PyQuery in Python.
Unlike jQuery, PyQuery doesn't support XPath selectors and relies entirely on CSS selectors though offers similar HTML parsing features like selection of HTML elements, their attributes and text as well as html tree modification.
PyQuery also comes with a http client (through requests) so it can load and parse web URLs by itself.
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
Highlights
Example Use
from pyquery import PyQuery as pq
# 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>
"""
doc = pq(html)
# we can use CSS selectors:
print(doc('#product .price').text())
"$10"
# it's also possible to modify HTML tree in various ways:
# insert text into selected element:
print(doc('h1').append('<span>discounted</span>'))
"<h1>Product Title<span>discounted</span></h1>"
# or remove elements
doc('p').remove()
print(doc('#product').html())
"""
<h1>Product Title<span>discounted</span></h1>
<span class="price">$10</span>
"""
# pyquery can also retrieve web documents using requests:
doc = pq(url='http://httpbin.org/html', headers={"User-Agent": "webscraping.fyi"})
print(doc('h1').html())
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"