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httrvsrvest

MIT 1 9 979
710.2 thousand (month) May 06 2012 1.4.7(10 months ago)
1,455 1 17 MIT
1.0.4(1 year, 7 months ago) Nov 22 2014 629.3 thousand (month)

The aim of httr is to provide a wrapper for the curl package, customised to the demands of modern web APIs.

Key features:

  • Functions for the most important http verbs: GET(), HEAD(), PATCH(), PUT(), DELETE() and POST().
  • Automatic connection sharing across requests to the same website (by default, curl handles are managed automatically), cookies are maintained across requests, and a up-to-date root-level SSL certificate store is used.
  • Requests return a standard reponse object that captures the http status line, headers and body, along with other useful information.
  • Response content is available with content() as a raw vector (as = "raw"), a character vector (as = "text"), or parsed into an R object (as = "parsed"), currently for html, xml, json, png and jpeg.
  • You can convert http errors into R errors with stop_for_status().
  • Config functions make it easier to modify the request in common ways: set_cookies(), add_headers(), authenticate(), use_proxy(), verbose(), timeout(), content_type(), accept(), progress().
  • Support for OAuth 1.0 and 2.0 with oauth1.0_token() and oauth2.0_token(). The demo directory has eight OAuth demos: four for 1.0 (twitter, vimeo, withings and yahoo) and four for 2.0 (facebook, github, google, linkedin). OAuth credentials are automatically cached within a project.

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


library(httr)

# GET requests:
resp <- GET("http://httpbin.org/get")
status_code(resp)  # status code
headers(resp)  # headers
str(content(resp))  # body

# POST requests: 
# Form encoded
resp <- POST(url, body = body, encode = "form")
# Multipart encoded
resp <- POST(url, body = body, encode = "multipart")
# JSON encoded
resp <- POST(url, body = body, encode = "json")

# setting cookies:
resp <- GET("http://httpbin.org/cookies", set_cookies("MeWant" = "cookies"))
content(r)$cookies  # get response cookies
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"

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