cheeriovsralger
cheerio is a popular JavaScript library that allows you to interact with and manipulate HTML and XML documents in a similar way to how you would with jQuery in a browser. It is a fast, flexible, and lean implementation of core jQuery designed specifically for the server.
One of the main benefits of using cheerio is that it allows you to use jQuery-like syntax to navigate and m anipulate the Document Object Model (DOM) of an HTML or XML document, making it easy to work with.
cheerio supports CSS selectors though not XPath.
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
const cheerio = require('cheerio');
const $ = cheerio.load('<html><head><title>My title</title></head><body><h1 class='name'>Hello World!</h1></body></html>');
// use css selectors
console.log($('title').text()); // My title
console.log($('.name').text()); // Hello World!
// select multiple elements
const $ = cheerio.load('<html><body><ul><li>item 1</li><li>item 2</li></ul></body></html>');
$('li').each(function(i, elem) {
console.log($(this).text());
});
// modify elements
const $ = cheerio.load('<html><body><h1>Hello World!</h1></body></html>');
$('h1').text('Hello, Cheerio!');
console.log($.html());
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