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htmlqueryvsralger

MIT 8 1 701
58.1 thousand (month) Feb 07 2019 v1.3.1(a month ago)
152 1 3 MIT
2.2.4(3 years ago) Dec 22 2019 1.1 thousand (month)

htmlquery is a Go library that allows you to parse and extract data from HTML documents using XPath expressions. It provides a simple and intuitive API for traversing and querying the HTML tree structure, and it is built on top of the popular Goquery library.

ralger is a small web scraping framework for R based on rvest and xml2.

It's goal to simplify basic web scraping and it provides a convenient and easy to use API.

It offers functions for retrieving pages, parsing HTML using CSS selectors, automatic table parsing and auto link, title, image and paragraph extraction.

Example Use


package main

import (
  "fmt"
  "log"

  "github.com/antchfx/htmlquery"
)

func main() {
  // Parse the HTML string
  doc, err := htmlquery.Parse([]byte(`
    <html>
      <body>
        <h1>Hello, World!</h1>
        <ul>
          <li>Item 1</li>
          <li>Item 2</li>
          <li>Item 3</li>
        </ul>
      </body>
    </html>
  `))
  if err != nil {
    log.Fatal(err)
  }

  // Extract the text of the first <h1> element
  h1 := htmlquery.FindOne(doc, "//h1")
  fmt.Println(htmlquery.InnerText(h1)) // "Hello, World!"

  // Extract the text of all <li> elements
  lis := htmlquery.Find(doc, "//li")
  for _, li := range lis {
    fmt.Println(htmlquery.InnerText(li))
  }
  // "Item 1"
  // "Item 2"
  // "Item 3"
}
library("ralger")

url <- "http://www.shanghairanking.com/rankings/arwu/2021"

# retrieve HTML and select elements using CSS selectors:
best_uni <- scrap(link = url, node = "a span", clean = TRUE)
head(best_uni, 5)
#>  [1] "Harvard University"
#>  [2] "Stanford University"
#>  [3] "University of Cambridge"
#>  [4] "Massachusetts Institute of Technology (MIT)"
#>  [5] "University of California, Berkeley"

# ralger can also parse HTML attributes
attributes <- attribute_scrap(
  link = "https://ropensci.org/",
  node = "a", # the a tag
  attr = "class" # getting the class attribute
)

head(attributes, 10) # NA values are a tags without a class attribute
#>  [1] "navbar-brand logo" "nav-link"          NA
#>  [4] NA                  NA                  "nav-link"
#>  [7] NA                  "nav-link"          NA
#> [10] NA
#

# ralger can automatically scrape tables:
data <- table_scrap(link ="https://www.boxofficemojo.com/chart/top_lifetime_gross/?area=XWW")

head(data)
#> # A tibble: 6 × 4
#>    Rank Title                                      `Lifetime Gross`  Year
#>   <int> <chr>                                      <chr>            <int>
#> 1     1 Avatar                                     $2,847,397,339    2009
#> 2     2 Avengers: Endgame                          $2,797,501,328    2019
#> 3     3 Titanic                                    $2,201,647,264    1997
#> 4     4 Star Wars: Episode VII - The Force Awakens $2,069,521,700    2015
#> 5     5 Avengers: Infinity War                     $2,048,359,754    2018
#> 6     6 Spider-Man: No Way Home                    $1,901,216,740    2021

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