htmlqueryvsralger
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