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parse5vsralger

MIT 34 6 3,658
183.2 million (month) Jul 03 2013 7.2.0(15 days ago)
156 1 3 MIT
Dec 22 2019 289 (month) 2.2.4(3 years ago)

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


const parse5 = require("parse5");

// parse string
const document = parse5.parse('<html><body>Hello World!</body></html>');
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('<p>New Element</p>');
body.appendChild(newElement.childNodes[0]);
console.log(parse5.serialize(document)); 
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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