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ralgervswombat

MIT 3 1 153
1.2 thousand (month) Dec 22 2019 2.2.4(3 years ago)
1,300 2 24 MIT
3.0.0(1 year, 7 months ago) Dec 27 2011 1.6 thousand (month)

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.

Wombat is a Ruby gem that makes it easy to scrape websites and extract structured data from HTML pages. It is built on top of Nokogiri, a popular Ruby gem for parsing and searching HTML and XML documents, and it provides a simple and intuitive API for defining and running web scraping operations.

One of the main features of Wombat is its ability to extract structured data from HTML pages using a simple, CSS-like syntax. It allows you to define a set of rules for extracting data from a page, and then automatically applies those rules to the page's HTML to extract the desired data. This makes it easy to extract data from even complex and dynamic pages, without having to write a lot of custom code.

In addition to its data extraction capabilities, Wombat also provides a variety of other features that can simplify the web scraping process. It can automatically follow links and scrape multiple pages, it can handle pagination and AJAX requests, and it can handle cookies and authentication. It also provides a built-in support for parallelism and queueing to speed up the scraping process.

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 'wombat'

Wombat.crawl do
  base_url "https://www.github.com"
  path "/"

  headline xpath: "//h1"
  subheading css: "p.alt-lead"

  what_is({ css: ".one-fourth h4" }, :list)

  links do
    explore xpath: '/html/body/header/div/div/nav[1]/a[4]' do |e|
      e.gsub(/Explore/, "Love")
    end

    features css: '.nav-item-opensource'
    business css: '.nav-item-business'
  end
end
will result in:
{
  "headline"=>"How people build software",
  "subheading"=>"Millions of developers use GitHub to build personal projects, support their businesses, and work together on open source technologies.",
  "what_is"=>[
    "For everything you build",
    "A better way to work",
    "Millions of projects",
    "One platform, from start to finish"
  ],
  "links"=>{
    "explore"=>"Love",
    "features"=>"Open source",
    "business"=>"Business"
  }
}

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