ralgervsnokogiri
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.
Nokogiri is a Ruby gem that provides a simple and powerful way to parse and search XML and HTML documents. It is built on top of the underlying C library libxml2, which is known for its speed and reliability.
Nokogiri provides a simple and intuitive API for parsing and searching XML and HTML documents, and it is widely used in the Ruby ecosystem for web scraping and data extraction.
One of the main features of Nokogiri is its ability to search and navigate through XML and HTML documents using a CSS or XPath selectors.
Nokogiri also provides a variety of other features that can simplify the process of working with XML and HTML documents. It can automatically handle character encodings and normalize documents, it can parse and search large documents with low memory usage, and it can validate documents against a DTD or schema.
Highlights
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
require 'nokogiri'
html_string = '<html><head><title>Page Title</title></head><body><h1 class="header-class">Hello World!</h1><p>This is a sample webpage.</p></body></html>'
# Parse the HTML string
doc = Nokogiri::HTML(html_string)
# Extract the class attribute of h1 tag using CSS selector
h1_class = doc.css("h1")[0]['class']
# or XPath
h1_class = doc.xpath("//h1")[0]['class']
puts "H1 class: #{h1_class}"