Quick analysis of cloudping to identify regions that match a specific inter-region latency

analyze-cloudping.py

#!/usr/bin/env python3
import sys
# data extracted from cloudping : https://www.cloudping.co/grid/p_90/timeframe/1D

rows = []

try:
    max_latency = int(sys.argv[1])
except (IndexError, ValueError):
    max_latency = 20
    print(f'\n- defaulting to {max_latency}ms\n')

with open('./cloud_ping_data.csv') as f:
    raw = f.readlines()
header = raw[0]
rows = raw[1:]

locations = header.rstrip().replace('"', '').split(',')[1:]

compatible_regions = []
region_set = set()

for row in rows:
    data = row.rstrip().replace('"', '').split(',')
    region = data[0]
    samples = [float(sample) for sample in data[1:]]
    for ptr in range(len(samples)):
        if (samples[ptr] <= max_latency):
            if (region == locations[ptr]):
                continue
            region_set.add(region)
            compatible_regions.append(f'{region} to {locations[ptr]} : {samples[ptr]}ms')

if compatible_regions:
    print(f'{len(compatible_regions)} compatible region combinations with {max_latency}ms or less latency:')
    for region in compatible_regions:
        print(f'\t- {region}')

    print(f'\nUnique regions: {len(region_set)}')
    for r in sorted(list(region_set)):
        print(f'\t- {r}')
else:
    print(f"no compatible regions found for {max_latency}ms latency")