tools/perf/measurements/loading_measurement_analyzer.py

   1 #!/usr/bin/env python
   2 # Copyright 2013 The Chromium Authors. All rights reserved.
   3 # Use of this source code is governed by a BSD-style license that can be
   4 # found in the LICENSE file.
   5
   6 """Parses CSV output from the loading_measurement and outputs interesting stats.
   7
   8 Example usage:
   9 $ tools/perf/run_measurement --browser=release \
  10     --output-format=csv --output=/path/to/loading_measurement_output.csv \
  11     loading_measurement tools/perf/page_sets/top_1m.json
  12 $ tools/perf/measurements/loading_measurement_analyzer.py \
  13     --num-slowest-urls=100 --rank-csv-file=/path/to/top-1m.csv \
  14     /path/to/loading_measurement_output.csv
  15 """
  16
  17 import collections
  18 import csv
  19 import heapq
  20 import optparse
  21 import os
  22 import re
  23 import sys
  24
  25
  26 class LoadingMeasurementAnalyzer(object):
  27
  28   def __init__(self, input_file, options):
  29     self.ranks = {}
  30     self.totals = collections.defaultdict(list)
  31     self.maxes = collections.defaultdict(list)
  32     self.avgs = collections.defaultdict(list)
  33     self.load_times = []
  34     self.cpu_times = []
  35     self.network_percents = []
  36     self.num_rows_parsed = 0
  37     self.num_slowest_urls = options.num_slowest_urls
  38     if options.rank_csv_file:
  39       self._ParseRankCsvFile(os.path.expanduser(options.rank_csv_file))
  40     self._ParseInputFile(input_file, options)
  41     self._display_zeros = options.display_zeros
  42
  43   def _ParseInputFile(self, input_file, options):
  44     with open(input_file, 'r') as csvfile:
  45       row_dict = csv.DictReader(csvfile)
  46       for row in row_dict:
  47         if (options.rank_limit and
  48             self._GetRank(row['url']) > options.rank_limit):
  49           continue
  50         cpu_time = 0
  51         load_time = float(row['load_time (ms)'])
  52         if load_time < 0:
  53           print 'Skipping %s due to negative load time' % row['url']
  54           continue
  55         for key, value in row.iteritems():
  56           if key in ('url', 'load_time (ms)', 'dom_content_loaded_time (ms)'):
  57             continue
  58           if not value or value == '-':
  59             continue
  60           value = float(value)
  61           if not value:
  62             continue
  63           if '_avg' in key:
  64             self.avgs[key].append((value, row['url']))
  65           elif '_max' in key:
  66             self.maxes[key].append((value, row['url']))
  67           else:
  68             self.totals[key].append((value, row['url']))
  69             cpu_time += value
  70         self.load_times.append((load_time, row['url']))
  71         self.cpu_times.append((cpu_time, row['url']))
  72         if options.show_network:
  73           network_time = load_time - cpu_time
  74           self.totals['Network (ms)'].append((network_time, row['url']))
  75           self.network_percents.append((network_time / load_time, row['url']))
  76         self.num_rows_parsed += 1
  77         if options.max_rows and self.num_rows_parsed == int(options.max_rows):
  78           break
  79
  80   def _ParseRankCsvFile(self, input_file):
  81     with open(input_file, 'r') as csvfile:
  82       for row in csv.reader(csvfile):
  83         assert len(row) == 2
  84         self.ranks[row[1]] = int(row[0])
  85
  86   def _GetRank(self, url):
  87     url = url.replace('http://', '')
  88     if url in self.ranks:
  89       return self.ranks[url]
  90     return len(self.ranks)
  91
  92   def PrintSummary(self, stdout):
  93     sum_totals = {}
  94     units = None
  95     for key, values in self.totals.iteritems():
  96       m = re.match('.* [(](.*)[)]', key)
  97       assert m, 'All keys should have units.'
  98       assert not units or units == m.group(1), 'All units should be the same.'
  99       units = m.group(1)
 100       sum_totals[key] = sum([v[0] for v in values])
 101     total_cpu_time = sum([v[0] for v in self.cpu_times])
 102     total_page_load_time = sum([v[0] for v in self.load_times])
 103
 104     print >> stdout
 105     print >> stdout, 'Total URLs:', self.num_rows_parsed
 106     print >> stdout, 'Total page load time: %ds' % int(round(
 107         total_page_load_time / 1000))
 108     print >> stdout, 'Average page load time: %dms' % int(round(
 109         total_page_load_time / self.num_rows_parsed))
 110     if units == 'ms':
 111       print >> stdout, 'Total CPU time: %ds' % int(round(total_cpu_time / 1000))
 112       print >> stdout, 'Average CPU time: %dms' % int(round(
 113           total_cpu_time / self.num_rows_parsed))
 114     print >> stdout
 115     for key, value in sorted(sum_totals.iteritems(), reverse=True,
 116                              key=lambda i: i[1]):
 117       if not self._display_zeros and not int(value / 100.):
 118         break
 119       output_key = '%60s: ' % re.sub(' [(].*[)]', '', key)
 120       if units == 'ms':
 121         output_value = '%10ds ' % (value / 1000)
 122         output_percent = '%.1f%%' % (100 * value / total_page_load_time)
 123       else:
 124         output_value = '%10d%s ' % (value, units)
 125         output_percent = '%.1f%%' % (100 * value / total_cpu_time)
 126       print >> stdout, output_key, output_value, output_percent
 127
 128     if not self.num_slowest_urls:
 129       return
 130
 131     for key, values in sorted(self.totals.iteritems(), reverse=True,
 132                               key=lambda i: sum_totals[i[0]]):
 133       if not self._display_zeros and not int(sum_totals[key] / 100.):
 134         break
 135       print >> stdout
 136       print >> stdout, 'Top %d slowest %s:' % (self.num_slowest_urls,
 137                                                re.sub(' [(].*[)]', '', key))
 138       slowest = heapq.nlargest(self.num_slowest_urls, values)
 139       for value, url in slowest:
 140         print >> stdout, '%10d%s\t%s (#%s)' % (value, units, url,
 141                                                self._GetRank(url))
 142
 143     if self.network_percents:
 144       print >> stdout
 145       print >> stdout, 'Top %d highest network to CPU time ratios:' % (
 146           self.num_slowest_urls)
 147       for percent, url in sorted(
 148           self.network_percents, reverse=True)[:self.num_slowest_urls]:
 149         percent *= 100
 150         print >> stdout, '\t', '%.1f%%' % percent, url, '(#%s)' % (
 151             self._GetRank(url))
 152
 153
 154 def main(arguments, stdout=sys.stdout):
 155   prog_desc = 'Parses CSV output from the loading_measurement'
 156   parser = optparse.OptionParser(usage=('%prog [options]' + '\n\n' + prog_desc))
 157
 158   parser.add_option('--max-rows', type='int',
 159                     help='Only process this many rows')
 160   parser.add_option('--num-slowest-urls', type='int',
 161                     help='Output this many slowest URLs for each category')
 162   parser.add_option('--rank-csv-file', help='A CSV file of <rank,url>')
 163   parser.add_option('--rank-limit', type='int',
 164                     help='Only process pages higher than this rank')
 165   parser.add_option('--show-network', action='store_true',
 166                     help='Whether to display Network as a category')
 167   parser.add_option('--display-zeros', action='store_true',
 168                     help='Whether to display categories with zero time')
 169
 170   options, args = parser.parse_args(arguments)
 171
 172   assert len(args) == 1, 'Must pass exactly one CSV file to analyze'
 173   if options.rank_limit and not options.rank_csv_file:
 174     print 'Must pass --rank-csv-file with --rank-limit'
 175     return 1
 176
 177   LoadingMeasurementAnalyzer(args[0], options).PrintSummary(stdout)
 178
 179   return 0
 180
 181
 182 if __name__ == '__main__':
 183   sys.exit(main(sys.argv[1:]))