A little script to convert https://ftp.lacnic.net/pub/stats/lacnic/delegated-lacnic-latest to an IP address list

lacnic-to-cidr.py

from requests import get
from io import StringIO
import pandas as pd

url = "https://ftp.lacnic.net/pub/stats/lacnic/delegated-lacnic-latest"
country = "br"

def nr_address_to_cidr(df):
    if df['address_type'] == "ipv4":
        mask = pow(2,32) | df['nr_address']
    elif df['address_type'] == "ipv6":
        mask = pow(2,128) | df['nr_address']
    else:
        return None

    return CountTrailingZerosIgnoringFirstOne(mask)

def CountTrailingZerosIgnoringFirstOne(n):
    bit = bin(n)[2:]
    bit = bit[::-1]
 
    zero = 0
    ignore = 1
 
    for i in range(len(bit)):
        if (bit[i] == '0'):
            if ignore == 0:
                zero += 1
             
        # if '1' comes then break
        else:
            if ignore == 1:
                ignore = 0
            else:
                break
    return zero + 1

lacnic_data = ''.join(get(url).text.splitlines(keepends=True)[4:])

df = pd.read_csv(
        StringIO(lacnic_data),
        names=["nic", "country", "address_type", "address", "nr_address","date", "status"],
        header=None,
        sep="|")

df['nr_address'] = pd.to_numeric(df['nr_address'])
# TODO: Write proper field creator. IPv4 needs to be calculated, IPv6 does not.
df[df['address_type'] == 'ipv4']['cidr'] = df[df['address_type'] == 'ipv4'].apply(nr_address_to_cidr, axis=1)
df[df['address_type'] == 'ipv6']['cidr'] = df[df['address_type'] == 'ipv6']['nr_address']

'''
Selective output for example: All BR country of family ipv6
'''
br_df = df[df['country'] == 'BR']
for index, row in br_df[df['address_type'] == 'ipv6'].iterrows():
    try:
        print(str(row['address']) + '/' +  str('%.0d' % row['cidr']) )
    except:
        pass