ralgervsrequests
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.
The requests package is a popular library for making HTTP requests in Python.
It provides a simple, easy-to-use API for sending HTTP/1.1 requests, and it abstracts away many of the low-level details of working with HTTP.
One of the key features of requests is its simple API. You can send a GET request with a single line of code:
import requests
response = requests.get('https://webscraping.fyi/lib/requests/')
pip install requests
Highlights
syncease-of-useno-http2no-asyncpopular
Example Use
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
import requests
# get request:
response = requests.get("http://webscraping.fyi/")
response.status_code
200
response.text
"text"
response.content
b"bytes"
# requests can automatically convert json responses to Python dictionaries:
response = requests.get("http://httpbin.org/json")
print(response.json())
{'slideshow': {'author': 'Yours Truly', 'date': 'date of publication', 'slides': [{'title': 'Wake up to WonderWidgets!', 'type': 'all'}, {'items': ['Why <em>WonderWidgets</em> are great', 'Who <em>buys</em> WonderWidgets'], 'title': 'Overview', 'type': 'all'}], 'title': 'Sample Slide Show'}}
# for POST request it can ingest Python's dictionaries as JSON:
response = requests.post("http://httpbin.org/post", json={"query": "hello world"})
# or form data:
response = requests.post("http://httpbin.org/post", data={"query": "hello world"})
# Session object can be used to automatically keep track of cookies and set defaults:
from requests import Session
s = Session()
s.headers = {"User-Agent": "webscraping.fyi"}
s.get('http://httpbin.org/cookies/set/foo/bar')
print(s.cookies['foo'])
'bar'
print(s.get('http://httpbin.org/cookies').json())
{'cookies': {'foo': 'bar'}}