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rvestvsgazpacho

MIT 18 1 1,450
555.9 thousand (month) Nov 22 2014 1.0.4(1 year, 6 months ago)
724 1 14 MIT
1.1(3 years ago) Dec 28 2012 10.3 thousand (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

gazpacho is a Python library for scraping web pages. It is designed to make it easy to extract information from a web page by providing a simple and intuitive API for working with the page's structure.

gazpacho uses the requests library to download the page and the lxml library to parse the HTML or XML code. It provides a way to search for elements in the page using CSS selectors, similar to BeautifulSoup.

To use gazpacho, you first need to install it via pip by running pip install gazpacho. Once it is installed, you can use the gazpacho.get() function to download a web page and create a gazpacho object. For example:

from gazpacho import get, Soup

url = "https://en.wikipedia.org/wiki/Web_scraping"
html = get(url)
soup = Soup(html)
print(soup.find('title').text)
You can also use gazpacho.get() with file-like objects, bytes or file paths.

Once you have a gazpacho object, you can use the find() and find_all() methods to search for elements in the page using CSS selectors, similar to BeautifulSoup.

gazpacho also supports searching using the select() method, which returns the first matching element, and the select_all() method, which returns all matching elements.

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 gazpacho import get, Soup

# gazpacho can retrieve web pages
url = "https://webscraping.fyi/"
html = get(url)
# and parse them:
soup = Soup(html)
print(soup.find('title').text)

# search for elements like beautifulsoup:
body = soup.find("div", {"class":"item"})
print(body.text)

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