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wreckvsralger

BSD-3-Clause 4 7 383
193.0 thousand (month) Aug 06 2011 18.1.0(2 months ago)
156 1 3 MIT
Dec 22 2019 289 (month) 2.2.4(3 years ago)

Wreck is an HTTP client library for Node.js. It provides a simple, consistent API for making HTTP requests, including support for both the client and server side of an HTTP transaction.

Wreck is a very minimal but stable as it's part of Hapi web framework project. For web scraping, it doesn't offer required features like proxy configuration or http2 support so it's not recommended.

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 Wreck = require('wreck');

// get request
Wreck.get('http://example.com', (err, res, payload) => {
    if (err) {
        throw err;
    }
    console.log(payload.toString());
});

// post request
const options = {
    headers: { 'content-type': 'application/json' },
    payload: JSON.stringify({ name: 'John Doe' })
};

Wreck.post('http://example.com', options, (err, res, payload) => {
    if (err) {
        throw err;
    }
    console.log(payload.toString());
});
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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