Very rough script to show EC2 spot prices

spot_prices.py

# -*- coding: utf-8 -*-

"""
Requires aws and spark (the sparkline charting tool, not apache spark)
brew install awscli spark
"""

import argparse
import datetime as dt
import json
import subprocess

SPARK_CMD = 'spark '

CMD = ' '.join(['aws ec2 describe-spot-price-history',
                '--instance-types {instance_type}',
                '--product-description "Linux/UNIX (Amazon VPC)"',
                "--start-time '{start_time:%Y-%m-%dT%H:%M:%S}'"])

OUTPUT_TMPL = u'{}: (min: {}, max: {} latest: {})\n{}'


def parse_datetime(d):
    return dt.datetime.strptime(
        d.replace('.000Z', ''), '%Y-%m-%dT%H:%M:%S').date()


def main():

    parser = argparse.ArgumentParser()
    parser.add_argument('instance_type', help='i.e. r3.8xlarge')
    parser.add_argument('--availability-zone', help='i.e. eu-central-1',
                        default=None)
    args = parser.parse_args()

    start_time = dt.datetime.utcnow() - dt.timedelta(days=1)
    cmd = CMD.format(instance_type=args.instance_type, start_time=start_time,
                     availability_zone=args.availability_zone)

    if args.availability_zone:
        cmd = cmd + '--availability-zone "{}"'.format(args.availability_zone)

    output = subprocess.check_output(cmd, shell=True)
    data = json.loads(output)
    prices = data['SpotPriceHistory']

    data = ((p['AvailabilityZone'], p['Timestamp'], p['SpotPrice'])
            for p in prices)
    # data = ((i[0], parse_datetime(i[1]), i[2]) for i in data)
    data = ((i[0], i[2]) for i in data)

    # Current prices
    # Max price in the last 24hrs
    # Min price in last 24hrs

    # Group by AvailabilityZone
    by_zone = {}
    for i in data:
        by_zone.setdefault(i[0], []).append(float(i[1]))

    # For each region, print stats and sparkline
    for region, prices in by_zone.iteritems():
        cmd = SPARK_CMD + ' '.join((str(p) for p in prices[:90]))
        s = subprocess.check_output(cmd, shell=True).decode('utf8')

        min_p = min(prices)
        max_p = max(prices)
        latest_p = prices[1]

        print(OUTPUT_TMPL.format(region, min_p, max_p, latest_p, s))


if __name__ == '__main__':
    main()