Add data processing scripts for chrome-speed-metrics

experimental/chrome_speed_metrics/scripts/parse_ctp_results.py

Index: experimental/chrome_speed_metrics/scripts/parse_ctp_results.py
diff --git a/experimental/chrome_speed_metrics/scripts/parse_ctp_results.py b/experimental/chrome_speed_metrics/scripts/parse_ctp_results.py
new file mode 100644
index 0000000000000000000000000000000000000000..68c81661ac4ff7094af0c6d748defa3a61263c52
--- /dev/null
+++ b/experimental/chrome_speed_metrics/scripts/parse_ctp_results.py
@@ -0,0 +1,134 @@
+"""Helper functions to parse result file produced by Chrome Trace Processor. We
+usually have to have a more specialized version of this file when we modify a
+tbmv2 metric for an analysis.
+"""
+
+# TODO(dproy): Make this file pylint compatible.
+# pylint: skip-file
+
+import csv
+import json
+import sys
+
+# Quick and dirty debug logging.
+debug_mode = False
+def log_debug(*args, **kwargs):
+  if debug_mode:
+    for arg in args:
+      print args
+    for k, v in kwargs.items():
+      print v
+
+def load_json_results_from_file(filename):
+  results = [];
+  with open(filename) as f:
+    for line in f:
+      try:
+        results.append(json.loads(line))
+      except:
+        log_debug("----------------------")
+        log_debug("Could not parse json: ")
+        log_debug(line)
+        log_debug("----------------------")
+  print "Loaded " + filename
+  return results
+
+def get_unique_histogram_value(histogram):
+  """If histogram has a unique value, returns that value. Otherwise returns a
+  string of the format "Not Unique. {count: <number of values>,
+  sampleValues: <a representative sample of values>}". If no value is found,
+  returns an empty string.
+
+  The decision to return a string instead of raising an exception in these
+  failure cases is intentional. The json results produced by cluster telemetry
+  / chrome trace processor pipeline often has all kinds of errors, and we don't
+  want to choke on them, but we also want to be aware of their presence so we
+  can fix the errors if possible.
+  """
+  if 'running' in histogram:
+    running_stats = histogram['running']
+    running_max = running_stats[1]
+    running_min = running_stats[4]
+    if running_min == running_max:
+      return running_min
+    else:
+      return "Not Unique. {count: {count}, sampleValues: {samples}}".format(
+        count=running_stats[0], sampleValues=histogram.get('sampleValues', []))
+  return ''
+
+def parse_results_json_list(result_json_list):
+  """
+  Produces a list of trace_data dicts. A trace_data dict contains information
+  about a single trace. It's format is
+  {
+    telemetry_info: <metadata about the run>
+    metrics: <dict of all histograms gathered from the run>
+  }
+  """
+  results = []
+  for result_json in result_json_list:
+    trace_data = {}
+    metrics_dict = {}
+    trace_data['metrics'] = metrics_dict
+    histograms = result_json['pairs']['histograms']
+    for histogram in histograms:
+      if histogram.get('type', '') == 'TelemetryInfo':
+        trace_data['telemetry_info'] = histogram
+      if 'name' in histogram:
+        metrics_dict[histogram['name']] = get_unique_histogram_value(histogram)
+    results.append(trace_data)
+  return results
+
+def get_csv_dicts(trace_data_list):
+  """
+  Converts list of trace_data to list of csv_dict, a flat dictionary that will
+  be written out to the csv file.
+  """
+  csv_dicts = []
+  for trace_data in trace_data_list:
+    csv_dict = {}
+    csv_dict['site'] = trace_data['telemetry_info']['storyDisplayName']
+    csv_dict['cache_temperature'] = (trace_data['telemetry_info']
+                                     ['storyGroupingKeys']
+                                     ['cache_temperature'])
+    csv_dict.update(trace_data['metrics'])
+    csv_dicts.append(csv_dict)
+  return csv_dicts
+
+
+def write_csv(trace_data_list, output_filename):
+  csv_dicts = get_csv_dicts(trace_data_list)
+
+  # Not all histograms contain all metrics so we need to gather all the
+  # possible fieldnames first.
+  fieldnames = set()
+  for d in csv_dicts:
+    fieldnames = fieldnames.union(d.keys())
+
+  with open(output_filename, 'w') as f:
+    writer = csv.DictWriter(f, list(fieldnames), extrasaction='ignore')
+    writer.writeheader()
+    writer.writerows(csv_dicts)
+
+def main():
+  # TODO(dproy): It may eventually make sense to use a real argument parser.
+  if len(sys.argv) < 2:
+    print "Usage: {0} <ctp-results> [output-filename]".format(sys.argv[0])
+    print "<ctp-results> is the results file produced by chrome trace processor."
+    print "[output-filename] is the produced csv file. Defaults to out.csv."
+
+  input_filename = sys.argv[1]
+  if len(sys.argv) > 2:
+    output_filename = sys.argv[2]
+  else:
+    output_filename = "out.csv"
+
+  result_json_list = load_json_results_from_file(input_filename)
+  trace_data_list = parse_results_json_list(result_json_list)
+  write_csv(trace_data_list, output_filename)
+
+  print "Wrote csv output to " + output_filename
+  print "Total results processed:", len(result_json_list)
+
+if __name__ == '__main__':
+  main()