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@trjordan
Last active December 12, 2015 08:09
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matplotlib script to create a couple of charts from AppNeta TraceView's API.
#!/usr/bin/env python
#
# Unwrap the data from the Data API, and make a couple of plots.
# 1) Plot of volume and latency
# 2) Plot of scalability of the current application
#
# Assumes data from the week-long view (i.e., 4-hour chunks of data). If this
# isn't true, the labels will be wrong.
#
# Try running it like this:
# API_KEY=YOUR_API_KEY
# curl "https://api.tracelytics.com/api-v1/latency/Default/server/series?key=$API_KEY&time_window=week" | python extract.py
import sys
import simplejson as json
from pylab import *
from datetime import datetime
def main():
data = ''.join(sys.stdin.readlines())
rows = [r for r in json.loads(data)['data'] if r[2]] # Only plot valid data
columns = transpose(rows)
# Format
dates = [datetime.utcfromtimestamp(v) for v in columns[0]]
traffic = [v / 4 for v in columns[1]]
times = [v / 1000 for v in columns[2]]
# Latency and Volume
figure()
subplot(2, 1, 1)
plot(dates, traffic)
title('Volume (# of requests)')
subplot(2, 1, 2)
plot(dates, times)
title('Latency (ms)')
# Latency vs. Volume
figure()
plot(traffic, times, '*')
title('Capacity')
xlabel('Volume (# of requests / hour)')
ylabel('Latency (ms)')
# Display all
show()
if __name__ == '__main__':
main()
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