wideload_calc

#!/usr/bin/env python

"""
this script runs after a wideload run, and computes results for bees based
on the information in wideload's "detailed-results.csv" file.
"""

import csv
import sys

results = csv.reader(file('detailed-results.csv'))
headers = results.next()

failures = 0
num_bytes = 0

events = []
timings = []

absolute_start = sys.maxint
absolute_end = 0

for line in results:
    line = dict(zip(headers, line))

    status = int(line['status'])
    if status >= 400:
        failures += 1
        continue

    time_start = float(line['time_start'])
    time_finish = float(line['time_finish'])

    absolute_start = min(time_start, absolute_start)
    absolute_end = max(time_finish, absolute_end)

    events.append((1, time_start))
    events.append((-1, time_finish))

    timings.append(1000 * (time_finish - time_start))

    num_bytes += int(line['bytes_received'])

events.sort(key=lambda ev: ev[1])
timings.sort()

# compute concurrency by scanning the "events" list
# and tracking the running sum of the first field
concurrency = []
counter = 0
for event in events:
    counter += event[0]
    concurrency.append(counter)

# print summary statistics for bees to pick up
print "ms_per_request: %.2f" % (sum(timings) / len(timings))
print "pctile_50: %.2f" % timings[len(timings) / 2]
print "pctile_75: %.2f" % timings[int(len(timings) * 0.75)]
print "pctile_90: %.2f" % timings[int(len(timings) * 0.90)]
print "pctile_95: %.2f" % timings[int(len(timings) * 0.95)]
print "pctile_99: %.2f" % timings[int(len(timings) * 0.99)]
print "concurrency: %.2f" % (float(sum(concurrency)) / len(concurrency))
print "time_taken: %.2f" % (absolute_end - absolute_start)
print "requests_per_second: %.2f" % (len(timings) / (absolute_end - absolute_start))
print "complete_requests: %d" % len(timings)
print "failed_requests: %d" % failures
print "non_2xx_responses: %d" % failures
print "total_transferred: %d" % num_bytes