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needlevsralger

MIT 86 4 1,624
32.1 million (month) Dec 11 2011 3.3.1(10 months ago)
156 1 3 MIT
Dec 22 2019 289 (month) 2.2.4(3 years ago)

needle is an HTTP client library for Node.js that provides a simple, flexible, and powerful API for making HTTP requests. It supports all major HTTP methods and has a clean and easy-to-use interface for handling responses and errors.

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 needle = require('needle');

// needle supports both Promises and async/await
needle.get('https://httpbin.org/get', (err, res) => {
    if (err) {
        console.error(err);
        return;
    }
    console.log(res.body);
});

const response = await needle.get('https://httpbin.org/get')

// concurrent requests can be sent using Promise.all
const results = await Promise.all([
  needle.get('http://httpbin.org/html'),
  needle.get('http://httpbin.org/html'),
  needle.get('http://httpbin.org/html'),
])

// POST requests
const data = { name: 'John Doe' };
await needle.post('https://api.example.com', data)

// proxy
const options = {
    proxy: 'http://proxy.example.com:8080'
};
await needle.get('https://httpbin.org/ip', options)

// headers and cookies
const options = {
  headers: {
      'Cookie': 'myCookie=123',
      'X-My-Header': 'myValue'
  }
};
await needle.get('https://httpbin.org/headers', options)
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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