#Elegant URL handling with urltools URLs are treated, by base R, as nothing more than components of a data retrieval process: they exist to create connections to retrieve datasets. This is an essential feature for the language to have, but it also means that URL handlers are designed for situations where URLs get you to the data - not situations where URLs are the data.
There is no support for encoding or decoding URLs en-masse, and no support for parsing and
interpreting them. urltools provides this support!
Base R provides two functions - URLdecode and URLencode - for taking percentage-encoded
URLs and turning them into regular strings, or vice versa. As discussed, these are primarily designed to
enable connections, and so they have several inherent limitations, including a lack of vectorisation, that
make them unsuitable for large datasets.
Not only are they not vectorised, they also have several particularly idiosyncratic bugs and limitations:
URLdecode, for example, breaks if the decoded value is out of range:
URLdecode("test%gIL")
Error in rawToChar(out) : embedded nul in string: '\0L'
In addition: Warning message:
In URLdecode("%gIL") : out-of-range values treated as 0 in coercion to raw
URLencode, on the other hand, encodes slashes on its most strict setting - without paying attention to where those slashes are: if we attempt to URLencode an entire URL, we get:
URLencode("https://en.wikipedia.org/wiki/Article", reserved = TRUE)
[1] "https%3a%2f%2fen.wikipedia.org%2fwiki%2fArticle"
That's a completely unusable URL (or ewRL, if you will).
urltools replaces both functions with url_decode and url_encode respectively:
library(urltools)
url_decode("test%gIL")
[1] "test"
url_encode("https://en.wikipedia.org/wiki/Article")
[1] "https://en.wikipedia.org%2fwiki%2fArticle"
As you can see, url_decode simply excludes out-of-range characters from consideration, while url_encode detects characters that make up part of the URLs scheme, and leaves them unencoded. Both are extremely fast; with urltools, you can
decode a vector of 1,000,000 URLs in 0.9 seconds.
Once you've got your nicely decoded (or encoded) URLs, it's time to do something with them - and, most of the time, you won't actually care about most of the URL. You'll want to look at the scheme, or the domain, or the path, but not the entire thing as one string.
The solution is url_parse, which takes a URL and breaks it out into its RfC 3986 components: scheme, domain, port, path, query string and fragment identifier. This is,
again, fully vectorised, and can happily be run over hundreds of thousands of URLs, rapidly processing them. The
results are provided as a data.frame, since most people use data.frames to store data.
> str(url_parse("https://en.wikipedia.org/wiki/Article"))
'data.frame': 1 obs. of 6 variables:
$ scheme : chr "https"
$ domain : chr "en.wikipedia.org"
$ port : chr ""
$ path : chr "wiki/article"
$ parameter: chr ""
$ fragment : chr ""
Once a URL is parsed, it's sometimes useful to get the value associated with a particular query parameter. As
an example, take the URL http://en.wikipedia.org/wiki/api.php?action=parse&pageid=1023&export=json. What
pageID is being used? What is the export format? We can find out with url_parameters.
> str(url_parameters(urls = "http://en.wikipedia.org/wiki/api.php?action=parse&pageid=1023&export=json",
parameter_names = c("pageid","export")))
'data.frame': 1 obs. of 2 variables:
$ pageid: chr "1023"
$ export: chr "json"
With the inclusion of a URL parser, we suddenly have the opportunity for lubridate-style component getting
and setting. Syntax is identical to that of lubridate, but uses URL components as function names.
url <- "https://en.wikipedia.org/wiki/Article"
scheme(url)
"https"
scheme(url) <- "ftp"
url
"ftp://en.wikipedia.org/wiki/Article"
Fields that can be extracted or set are scheme, domain, port, path,
query and fragment.
If you have ideas for other URL handlers that would make your data processing easier, the best approach is to either request it or add it!