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ralgervsphpscraper

MIT 3 1 152
1.4 thousand (month) Dec 22 2019 2.2.4(2 years ago)
472 2 21 GPL-3.0-or-later
2.0.0(8 months ago) May 04 2020 127 (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.

PHPScraper is a universal web-util for PHP. The main goal is to get stuff done instead of getting distracted with selectors, preparing & converting data structures, etc. Instead, you can just go to a website and get the relevant information for your project.

PHPScraper is a minimalistic scraper framework that is built on top of other popular scraping tools.

Features:

  • Direct access to page basic features like: Meta data, Links, Images, Headings, Content, Keywords etc.
  • File downloading.
  • RSS, Sitemap and other feed processing.
  • CSV, XML and JSON file processing.

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
// create scraper object
$web = new \Spekulatius\PHPScraper\PHPScraper;
// go to URL
$web->go('https://test-pages.phpscraper.de/content/selectors.html');

// elements can be found using XPath:
echo $web->filter("//*[@id='by-id']")->text();   // "Content by ID"

// or pre-defined variables covering basic page data:
$web->links;  // for all links
$web->headings;
$web->images;
$web->contentKeywords;
$web->orderedLists;
$web->unorderedLists;
$web->paragraphs;
$web->outline;  // basic page outline
$web->cleanOutlineWithParagraphs;  // basic page outline

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