calculate average runtimes of jenkins jobs

avgdur.py

#!/usr/bin/python2.7
"""Average DURRRRRR - get average runtime of a jenkins job.

This is obviously just an example - a plain average of the runtimes
isn't actually all that useful.  Use numpy, do something fancier.
"""

import datetime
import gflags
import json
import logging
import numpy
import urllib2
import sys

gflags.DEFINE_string('jobname', None, 'Name of jenkins job to query.')
gflags.DEFINE_string('baseurl', 'http://jenkins.cloudscaling.com',
                     'Base URL of jenkins server.')
FLAGS = gflags.FLAGS


def main(argv):
  logging.basicConfig(level=logging.INFO)
  try:
    argv = FLAGS(argv)
  except gflags.FlagsError as err:
    logging.error('%s\n\nUsage: %s\n%s', err, sys.argv[0], FLAGS)
    sys.exit(1)

  if not FLAGS.jobname:
    logging.error('Required flag not set: --jobname\n\nUsage: %s\n%s',
                  sys.argv[0], FLAGS)
    sys.exit(1)

  joburl = '%s/job/%s' % (FLAGS.baseurl, FLAGS.jobname)

  joblist = json.load(urllib2.urlopen('%s/api/json' % joburl))

  durations = []
  estimated_durations = []

  for builddata in joblist['builds']:
    jobdata = json.load(urllib2.urlopen('%s/api/json' % builddata['url']))
    durations.append(jobdata['duration'])
    estimated_durations.append(jobdata['estimatedDuration'])

  average_duration = datetime.timedelta(milliseconds=numpy.mean(durations))
  print 'Average duration: %s' % average_duration

  average_estimated_duration = datetime.timedelta(milliseconds=numpy.mean(
      estimated_durations))
  # Is this even remotely useful? It's how long jenkins guesses the job will
  # take before it starts, I think.
  print 'Average estimated duration: %s' % average_estimated_duration


if __name__ == '__main__':
  main(sys.argv)