In etsakl/DasyMapR: Geographical ETRS-LAEA Grid Based Dasymetric Mapping

knitr::opts_chunk$set(comment = "")
library(curl)

The curl package provides bindings to the libcurl C library for R. The package supports retrieving data in-memory, downloading to disk, or streaming using the R "connection" interface. Some knowledge of curl is recommended to use this package. For a more user-friendly HTTP client, have a look at the httr package which builds on curl with HTTP specific tools and logic.

Download in memory

The curl package implements three ways to retrieve data from a URL. The curl_fetch_memory function is a synchronous interface which returns a list with contents of the server response.

req <- curl_fetch_memory("https://httpbin.org/get")
str(req)
parse_headers(req$headers)
cat(rawToChar(req$content))

The curl_fetch_memory interface is the easiest interface and most powerful for buidling API clients. However because it is fully in-memory, it is not suitable for downloading really large files. If you are expecting 100G of data, you probably need one of the other interfaces.

Download to disk

The second method is curl_download, which has been designed as a drop-in replacement for download.file in r-base. It writes the response straight to disk, which is useful for downloading (large) files.

tmp <- tempfile()
curl_download("https://httpbin.org/get", tmp)
cat(readLines(tmp), sep = "\n")

Streaming

The most flexible interface is the curl function, which has been designed as a drop-in replacement for base url. It will create a so-called connection object, which allows for incremental (asynchronous) reading of the response.

con <- curl("https://httpbin.org/get")
open(con)

# Get 3 lines
out <- readLines(con, n = 3)
cat(out, sep = "\n")

# Get 3 more lines
out <- readLines(con, n = 3)
cat(out, sep = "\n")

# Get remaining lines
out <- readLines(con)
close(con)
cat(out, sep = "\n")

The example shows how to use readLines on an opened connection to read n lines at a time. Similarly readBin is used to read n bytes at a time for stream parsing binary data.

Status codes

It is important to note that curl_fetch_memory will not automatically raise an error if the request was completed but returned a non-200 status code. When using curl_fetch_memory you need to implement the application logic yourself.

req <- curl_fetch_memory("https://httpbin.org/status/418")
print(req$status_code)

The curl and curl_download functions on the other hand will automatically raise an error if the HTTP response was non successful, as would the base functions url and download.file do.

curl_download("https://httpbin.org/status/418", tempfile())
con <- curl("https://httpbin.org/status/418")
open(con)

invisible(gc())

Handles

By default libcurl uses HTTP GET to issue a request to an HTTP url. To send a customized request, we first need to create and configure a curl handle object that is passed to the specific download interface.

Configuring a handle

Creating a new handle is done using new_handle. After creating a handle object, we can set the libcurl options and http request headers.

h <- new_handle()
handle_setopt(h, copypostfields = "moo=moomooo");
handle_setheaders(h,
  "Content-Type" = "text/moo",
  "Cache-Control" = "no-cache",
  "User-Agent" = "A cow"
)

Use the curl_options() function to get a list of the options supported by your version of libcurl. The libcurl documentation explains what each option does. Option names are not case sensitive.

After the handle has been configured, it can be used with any of the download interfaces to perform the request. For example curl_fetch_memory will load store the output of the request in memory:

req <- curl_fetch_memory("http://httpbin.org/post", handle = h)
cat(rawToChar(req$content))

Alternatively we can use curl() to read the data of via a connetion interface:

con <- curl("http://httpbin.org/post", handle = h)
cat(readLines(con), sep = "\n")

Or we can use curl_download to write the response to disk:

tmp <- tempfile()
curl_download("http://httpbin.org/post", destfile = tmp, handle = h)
cat(readLines(tmp), sep = "\n")

invisible(gc())

Cookies

Curl handles automatically keep track of cookies set by the server. At any given point we can use handle_cookies to see a list of current cookies in the handle.

# Start with a fresh handle
h <- new_handle()

# Ask server to set some cookies
req <- curl_fetch_memory("http://httpbin.org/cookies/set?foo=123&bar=ftw", handle = h)
req <- curl_fetch_memory("http://httpbin.org/cookies/set?baz=moooo", handle = h)
handle_cookies(h)

# Unset a cookie
req <- curl_fetch_memory("http://httpbin.org/cookies/delete?foo", handle = h)
handle_cookies(h)

The handle_cookies function returns a data frame with 7 columns as specified in the netscape cookie file format.

On re-using handles

As we have already seen, curl allows for reusing a single handle for multiple requests. However it is not always a good idea to do so. The performance overhead of creating and configuring a new handle object is usually negligible. The safest way to issue mutiple requests, either to a single server or multiple servers is by using a separate handle for each request.

req1 <- curl_fetch_memory("https://httpbin.org/get", handle = new_handle())
req2 <- curl_fetch_memory("http://www.r-project.org", handle = new_handle())

There are two reasons why you might want to reuse a handle for multiple requests. The first one is that it will automatically keep track of cookies set by the server. This might be useful if your host requires use of a session cookies.

The other reason is to take advantage of http Keep-Alive. Curl automatically maintains a pool of open http connections within each handle. When using a single handle to issue many requests to the same server, curl uses existing connections when possible. This eliminites a little bit of connection overhead, although on a decent network this might not be very significant.

h <- new_handle()
system.time(curl_fetch_memory("https://api.github.com/users/ropensci", handle = h))
system.time(curl_fetch_memory("https://api.github.com/users/rstudio", handle = h))

The argument against reusing handles is that curl does not cleanup the handle after each request. All of the options and internal fields will linger around for all future request until explicitly reset or overwritten. This can sometimes leads to unexpected behavior.

handle_reset(h)

The handle_reset function will reset all curl options and request headers to the default values. It will not erease cookies and it will still keep alive the connections. Therefore it is good practice to call handle_reset after performing a request if you want to reuse the handle for a subsequent request. Still it is always safer to create a new fresh handle when possible, rather than recycling old ones.

Forms

The handle_setform function is used to perform a multipart/form-data HTTP POST request (a.k.a. posting a form). Values can be either strings, raw vectors (for binary data) or files.

# Posting multipart
h <- new_handle()
handle_setform(h,
  foo = "blabla",
  bar = charToRaw("boeboe"),
  description = form_file(system.file("DESCRIPTION")),
  logo = form_file(file.path(Sys.getenv("R_DOC_DIR"), "html/logo.jpg"), "image/jpeg")
)
req <- curl_fetch_memory("http://httpbin.org/post", handle = h)

The form_file function is used to upload files with the form post. It has two arguments: a file path, and optionally a content-type value. If no content-type is set, curl will guess the content type of the file based on the file extention.

Using pipes

All of the handle_xxx functions return the handle object so that function calls can be chained using the popular pipe operators:

library(magrittr)

new_handle() %>% 
  handle_setopt(copypostfields = "moo=moomooo") %>% 
  handle_setheaders("Content-Type" = "text/moo", "Cache-Control" = "no-cache", "User-Agent" = "A cow") %>%
  curl_fetch_memory(url = "http://httpbin.org/post") %$% content %>% rawToChar %>% cat