ralgervsxml2
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 xml2 package is a binding to libxml2, making it easy to work with HTML and XML from R. The API is somewhat inspired by jQuery.
xml2 can be used to parse HTML documents using XPath selectors and is a successor to R's XML package with a few improvements:
- xml2 takes care of memory management for you. It will automatically free the memory used by an XML document as soon as the last reference to it goes away.
- xml2 has a very simple class hierarchy so don't need to think about exactly what type of object you have, xml2 will just do the right thing.
- More convenient handling of namespaces in Xpath expressions - see xml_ns() and xml_ns_strip() to get started.
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
library("xml2")
x <- read_xml("<foo> <bar> text <baz/> </bar> </foo>")
x
xml_name(x)
xml_children(x)
xml_text(x)
xml_find_all(x, ".//baz")
h <- read_html("<html><p>Hi <b>!")
h
xml_name(h)