node-crawlervsralger
node-crawler is a popular web scraping library for Node.js that allows you to easily navigate and extract data from websites. It has a simple API and supports concurrency, making it efficient for scraping large numbers of pages.
Features:
- Server-side DOM & automatic jQuery insertion with Cheerio (default) or JSDOM,
- Configurable pool size and retries,
- Control rate limit,
- Priority queue of requests,
- forceUTF8 mode to let crawler deal for you with charset detection and conversion,
- Compatible with 4.x or newer version.
- Http2 support
- Proxy support
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 Crawler = require('crawler');
const c = new Crawler({
maxConnections: 10,
// This will be called for each crawled page
callback: (error, res, done) => {
if (error) {
console.log(error);
} else {
const $ = res.$;
// $ is Cheerio by default
//a lean implementation of core jQuery designed specifically for the server
console.log($('title').text());
}
done();
}
});
// Queue just one URL, with default callback
c.queue('http://www.amazon.com');
// Queue a list of URLs
c.queue(['http://www.google.com/','http://www.yahoo.com']);
// Queue URLs with custom callbacks & parameters
c.queue([{
uri: 'http://parishackers.org/',
jQuery: false,
// The global callback won't be called
callback: (error, res, done) => {
if (error) {
console.log(error);
} else {
console.log('Grabbed', res.body.length, 'bytes');
}
done();
}
}]);
// Queue some HTML code directly without grabbing (mostly for tests)
c.queue([{
html: '<p>This is a <strong>test</strong></p>'
}]);
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