Skip to content

rvestvsscrapydweb

MIT 17 1 1,455
629.3 thousand (month) Nov 22 2014 1.0.4(1 year, 7 months ago)
2,983 1 59 GNU General Public License v3.0
1.5.0(a month ago) Sep 30 2018 1.6 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

ScrapydWeb is a web-based management tool for the Scrapyd service. It is built using the Python Flask framework and allows you to easily manage and monitor your Scrapy spider projects through a web interface.

ScrapydWeb allows you to view the status of your running spiders, view the logs of completed spiders, schedule new spider runs, and manage spider settings and configurations.

ScrapydWeb provides a simple way to manage your scraping tasks and allows you to schedule and run multiple spiders simultaneously. It also provides a user-friendly web interface that makes it easy to view the status of your spiders and monitor their progress.

You can install the package via pip by running pip install scrapydweb and then you can run the package by running scrapydweb command in your command prompt.

It will start a web server that you can access through your web browser at http://localhost:6800/ You will need to have Scrapyd running in order to use ScrapydWeb, Scrapyd is a service for running Scrapy spiders, it allows you to schedule spiders to run at regular intervals and also allows you to run spiders on remote machines.

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"

Alternatives / Similar