This vignette demonstrates some typical example usage and recipes when learning about ipaddress.
Although IPv4 addresses are usually displayed in a human-readable
192.168.0.1), they are often saved to disk as
integers to reduce storage requirements. R is unable to store the entire
range of IPv4 addresses in its integer data type, but they can instead
be stored in its numeric data type. More details are found under
Given this, it’s quite possible that you’ll receive IPv4 addresses
represented as integers, and we’ll want to convert them to the
ip_address() vector type. Here’s an example of how to do
There are multiple equivalent ways to represent an IP network:
ip_network() function can handle the first
3 options, we use the
common_network() function for the
tibble( start = ip_address(c("192.168.0.0", "2001:db8::")), end = ip_address(c("192.168.0.15", "2001:db8::ffff:ffff:ffff")) ) %>% mutate(network = common_network(start, end)) #> # A tibble: 2 × 3 #> start end network #> <ip_addr> <ip_addr> <ip_netwk> #> 1 192.168.0.0 192.168.0.15 192.168.0.0/28 #> 2 2001:db8:: 2001:db8::ffff:ffff:ffff 2001:db8::/80
Note that this approach assumes the two addresses do actually
correspond to the first and last addresses of the network, otherwise an
expanded network will be returned (see
help("common_network") for details).
A very common task is to check if an address is within a network, so
the ipaddress package provides a couple of different functions to help
with this workflow:
is_within_any(). We also provide
is_supernet() to test if a network is within another
To see how these functions can be used in practice, let’s consider a couple of IP networks:
and a handful of addresses:
First, we’ll check if each address is in any of our networks.
But what if we need to know which of our networks the
address was found in? We can do that using the excellent fuzzyjoin
package together with the
my_addresses %>% fuzzyjoin::fuzzy_left_join(my_networks, c("address" = "network"), is_within) #> # A tibble: 4 × 3 #> address network label #> <ip_addr> <ip_netwk> <chr> #> 1 192.168.100.1 192.168.0.0/16 Private #> 2 126.96.36.199 NA <NA> #> 3 2001:db8::8a2e:370:7334 2001:db8::/32 Documentation #> 4 ::1 NA <NA>
ipaddress provides functions to sample from a specific network
sample_network()) or the entire address space
sample_ipv6()). However, it
can be more difficult to sample from the majority of address space,
while excluding certain networks.
A good example is sampling public IPv4 addresses. The simplest solution is to use an accept-reject algorithm – sampling the entire IPv4 address space and rejecting addresses that are reserved.
We now sample 10 addresses and make sure they are all public addresses.
tibble(address = sample_public(10)) %>% mutate(is_public = is_global(address)) #> # A tibble: 10 × 2 #> address is_public #> <ip_addr> <lgl> #> 1 188.8.131.52 TRUE #> 2 184.108.40.206 TRUE #> 3 220.127.116.11 TRUE #> 4 18.104.22.168 TRUE #> 5 22.214.171.124 TRUE #> 6 126.96.36.199 TRUE #> 7 188.8.131.52 TRUE #> 8 184.108.40.206 TRUE #> 9 220.127.116.11 TRUE #> 10 18.104.22.168 TRUE