superagentvsralger
superagent 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.
what differentiates superagent from other http clients is its simple declarative API.
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.
Highlights
declarativeproxypopular
Example Use
```javascript
const superagent = require('superagent');
// superagent supports both Promises and async/await
superagent.get('https://httpbin.org/get')
.then(res => console.log(res.text))
.catch(err => console.error(err));
const response = superagent.get('https://httpbin.org/get')
// post requests:
superagent.post('https://httpbin.org/post').send({ name: 'John Doe' })
// setting proxy
superagent.get('https://httpbin.org/ip').proxy('http://proxy.example.com:8080')
// settings headers and proxies
superagent.get('https://httpbin.org/headers').set('Cookie', 'myCookie=123').set('X-My-Header', 'myValue')
```
```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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