Random network IP-address generator, fast IP-network tree builder and long prefix match (LPM) function

ipatree.py

# This script is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

from numpy import random, iinfo, uint32
import ipaddress as ipa, functools as ft

count = 99
cidr = 16, 24
def rand_net(f, t, c=-1):
    while c:
        yield ipa.IPv4Address(int(random.randint(0, iinfo(uint32).max>>f, dtype='uint32')).to_bytes(4, byteorder='big'))
        c = c - 1

def ipnp(t, i=0):
    for n in t:
        print(' '*i*4, str(n), sep='')
        ipnp(t[n], i+1)

def ipnm(ns, t):
    for n in t:
        m = ipnm(ns, t[n])
        if m:
            return m
        if ns.subnet_of(n):
            return n
                                                                                                    
ipn = ft.partial(ipa.ip_network, strict=False)

ns = list(sorted(set(map(ipn, ('/'.join(map(str, (ip, random.randint(*cidr)))) for ip in rand_net(*cidr, count))))))                                                                                                 
ns.reverse()
ft = []
t = {}
while ns:
    nf = ns.pop()
    for i in range(len(ft)):
        np, st = ft[i]
        if nf.subnet_of(np):
            assert nf not in st # Debug
            st[nf] = {}
            ft.insert(i, (nf, st[nf]))
            break
    else:
        t[nf] = {}
        ft.append((nf, t[nf]))

ipnp(t)
for a in map(ipa.ip_network, map(int, random.choice(2**cidr[0], count//10))):
    print('Address', str(a.network_address), 'matches', ipnm(a, t))

output

0.0.0.0/16
    0.0.0.0/17
        0.0.0.0/18
            0.0.0.0/19
                0.0.0.0/20
                    0.0.0.0/21
                0.0.16.0/20
                    0.0.24.0/22
            0.0.32.0/20
                0.0.32.0/21
                    0.0.32.0/22
                    0.0.36.0/22
                0.0.40.0/21
            0.0.56.0/22
                0.0.56.0/23
        0.0.64.0/18
            0.0.64.0/19
                0.0.64.0/21
                0.0.72.0/21
                    0.0.72.0/22
                0.0.80.0/21
                    0.0.84.0/22
            0.0.96.0/19
                0.0.96.0/20
                    0.0.96.0/21
                        0.0.96.0/22
                        0.0.102.0/23
                    0.0.104.0/21
                        0.0.106.0/23
                0.0.112.0/21
                0.0.124.0/22
    0.0.128.0/17
        0.0.128.0/18
            0.0.128.0/19
                0.0.128.0/20
                    0.0.128.0/21
                0.0.144.0/22
                0.0.148.0/22
                0.0.156.0/22
                    0.0.156.0/23
            0.0.160.0/19
                0.0.160.0/20
                    0.0.168.0/21
                        0.0.174.0/23
                0.0.176.0/21
                    0.0.176.0/23
                    0.0.182.0/23
        0.0.192.0/18
            0.0.192.0/19
                0.0.192.0/20
                    0.0.192.0/21
                        0.0.196.0/22
                    0.0.200.0/23
                    0.0.204.0/22
                        0.0.206.0/23
                0.0.208.0/20
                    0.0.208.0/21
                    0.0.216.0/22
            0.0.224.0/20
                0.0.230.0/23
            0.0.240.0/20
                0.0.248.0/21
Network 0.0.88.13/32 matches 0.0.64.0/19
Network 0.0.242.131/32 matches 0.0.240.0/20
Network 0.0.82.32/32 matches 0.0.80.0/21
Network 0.0.59.1/32 matches 0.0.56.0/22
Network 0.0.198.87/32 matches 0.0.196.0/22
Network 0.0.144.181/32 matches 0.0.144.0/22
Network 0.0.11.226/32 matches 0.0.0.0/20
Network 0.0.250.201/32 matches 0.0.248.0/21
Network 0.0.208.27/32 matches 0.0.208.0/21