phpscrapervsralger
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.
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.
Example Use
// 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
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