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soupvsrvest

MIT 22 1 2,109
58.1 thousand (month) Apr 29 2017 v1.2.5(2 years ago)
1,453 1 18 MIT
1.0.4(1 year, 6 months ago) Nov 22 2014 579.0 thousand (month)

soup is a Go library for parsing and querying HTML documents.

It provides a simple and intuitive interface for extracting information from HTML pages. It's inspired by popular Python web scraping library BeautifulSoup and shares similar use API implementing functions like Find and FindAll.

soup can also use go's built-in http client to download HTML content.

Note that unlike beautifulsoup, soup does not support CSS selectors or XPath.

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


package main

import (
  "fmt"
  "log"

  "github.com/anaskhan96/soup"
)

func main() {

  url := "https://www.bing.com/search?q=weather+Toronto"

  # soup has basic HTTP client though it's not recommended for scraping:
  resp, err := soup.Get(url)
  if err != nil {
    log.Fatal(err)
  }

  # create soup object from HTML
  doc := soup.HTMLParse(resp)

  # html elements can be found using Find or FindStrict methods:
  # in this case find <div> elements where "class" attribute matches some values:
  grid := doc.FindStrict("div", "class", "b_antiTopBleed b_antiSideBleed b_antiBottomBleed")
  # note: to find all elements FindAll() method can be used the same way

  # elements can be further searched for descendents:
  heading := grid.Find("div", "class", "wtr_titleCtrn").Find("div").Text()
  conditions := grid.Find("div", "class", "wtr_condition")
  primaryCondition := conditions.Find("div")
  secondaryCondition := primaryCondition.FindNextElementSibling()
  temp := primaryCondition.Find("div", "class", "wtr_condiTemp").Find("div").Text()
  others := primaryCondition.Find("div", "class", "wtr_condiAttribs").FindAll("div")
  caption := secondaryCondition.Find("div").Text()

  fmt.Println("City Name : " + heading)
  fmt.Println("Temperature : " + temp + "˚C")
  for _, i := range others {
    fmt.Println(i.Text())
  }
  fmt.Println(caption)
}
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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