Export AWS Route53 Domains as CSV for Excel people

If you have a fairly large list of domains in your AWS account and want to create an easily consumable format for external departments (finance, legal, etc) then this script might be of help.

The script requires a valid AWS session with permissions to read domain details.

➡️ Available as Gist on GitHub

Installation#

Copy the following script into a file domains.py (skip if you want to use wget).

# Export AWS Route53 Domains to a CSV for Excel people
#
# Usage:
#
#   python3 <(wget -q -O - https://gist.github.com/estahn/33ee9f0ecede6416a168489a7a24ee24/raw/5eef9122e573ff23bcd40732856565c37c708efd/domains.py)
#
from itertools import chain, starmap

import pandas as pd
from pandas.io.json import json_normalize #package for flattening json in pandas df

import boto3

listofdomains = []
client = boto3.client('route53domains', region_name='us-east-1')

p = client.get_paginator('list_domains')
for page in p.paginate():
    for domain in page['Domains']:
        domain_detail = client.get_domain_detail(DomainName=domain['DomainName'])

        # Remove response data, so it doesn't make it into the spreadsheet
        del domain_detail['ResponseMetadata']

        # Re-map "ExtraParams" to flatten the JSON for the spreadsheet
        for c in ['RegistrantContact', 'TechContact', 'AdminContact']:
            for p in domain_detail[c]['ExtraParams']:
                domain_detail[c][p['Name']] = p['Value']
            del domain_detail[c]['ExtraParams']

        listofdomains.append(domain_detail)

df = pd.json_normalize(listofdomains)
df.to_csv (r'domains.csv', index = False, header=True)

Usage#

Either run the script created during the installation step:

$ python3 domains.py

or run:

$ python3 <(wget -q -O - https://gist.github.com/estahn/33ee9f0ecede6416a168489a7a24ee24/raw/5eef9122e573ff23bcd40732856565c37c708efd/domains.py)

This will create a file domains.csv containing the required information.