parse5vsralger
parse5 is a Node.js library for parsing and manipulating HTML and XML documents. It is designed to be fast and flexible, and it is commonly used in web scraping and web development projects.
parse5 is used by popular libraries such as Angular, Lit, Cheerio and many more. Unlike Cheerio parse5 is a low level html parsing library that might be useful directly in web scraping without higher level abstraction.
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
```javascript
const parse5 = require("parse5");
// parse string
const document = parse5.parse('Hello World!');
console.log(document);
// html tree can be traversed as javascript object:
const body = document.childNodes[1];
console.log(body.childNodes[0].value); // "Hello World!"
// and modified
const newElement = parse5.parseFragment('
New Element
'); body.appendChild(newElement.childNodes[0]); console.log(parse5.serialize(document)); ```
```r
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
#>
#> 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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