Refactor stages 1, 2 and test_api overhaul.

scripts/slave/recipe_modules/bisect_tester/parse_metric.py

-import math
-import re
-from functools import reduce
-
-
-def _geom_mean_and_std_dev_from_histogram(histogram):  # pragma: no cover
-  # Copied from: https://code.google.com/p/chromium/codesearch#chromium/build/scripts/common/chromium_utils.py&l=222
-  # TODO(robertocn): Remove this code duplication from common.chromium_utils
-  if not 'buckets' in histogram:
-    return 0.0, 0.0
-  count = 0
-  sum_of_logs = 0
-  for bucket in histogram['buckets']:
-    if 'high' in bucket:
-      bucket['mean'] = (bucket['low'] + bucket['high']) / 2.0
-    else:
-      bucket['mean'] = bucket['low']
-    if bucket['mean'] > 0:
-      sum_of_logs += math.log(bucket['mean']) * bucket['count']
-      count += bucket['count']
-
-  if count == 0:
-    return 0.0, 0.0
-
-  sum_of_squares = 0
-  geom_mean = math.exp(sum_of_logs / count)
-  for bucket in histogram['buckets']:
-    if bucket['mean'] > 0:
-      sum_of_squares += (bucket['mean'] - geom_mean) ** 2 * bucket['count']
-  return geom_mean, math.sqrt(sum_of_squares / count)
-
-
-def parse_chartjson_metric(results, metric):  # pragma: no cover
-  """Interpret results-chart.json, finding the needed values.
-
-  Args:
-    results: The dictionary parsed from the chartjson file.
-    metric: A pair of strings indicating chart and trace names.
-
-  Returns:
-    A triple (valid_values, values, all_results) where valid_values is a
-    boolean, values is a list of floating point numbers, and all_results is a
-    dictionary containing all the results originally in results_str.
-  """
-  def escape_chars(original_string):
-    return re.sub(r'[\:|=/#&,]', '_', original_string)
-
-  chart_name, trace_name = metric
-  if trace_name == chart_name:
-    trace_name = 'summary'
-  try:
-    for chart in results['charts']:
-      if escape_chars(chart) == chart_name:
-        chart_name = chart  # Unescaping
-        break
-    for trace in results['charts'][chart_name]:
-      if escape_chars(trace) == trace_name:
-        trace_name = trace  # Unescaping
-        break
-    if (results['charts'][chart_name][trace_name]['type'] ==
-        'list_of_scalar_values'):
-      values = results['charts'][chart_name][trace_name]['values']
-      if values:
-        avg_value = [sum(values) / len(values)]
-        return True, avg_value, results
-    if results['charts'][chart_name][trace_name]['type'] == 'histogram':
-      return True, [_geom_mean_and_std_dev_from_histogram(
-          results['charts'][chart_name][trace_name])[0]], results
-  except KeyError:  # e.g. metric not found
-    pass
-  return False, [], results
-
-
-# The following has largely been copied from bisect_perf_regression.py
-def parse_metric(out, err, metric):  # pragma: no cover
-  """Tries to parse the output in RESULT line format or HISTOGRAM format.
-
-  Args:
-    metric: The metric as a list of [<trace>, <value>] string pairs.
-    out, err: stdout and stderr that may contain the output to be parsed
-
-  Returns:
-    A pair (valid_values, values) where valid_values is a boolean and values is
-    a list of floating point numbers.
-  """
-  text = (out or '') + (err or '')
-  result = _parse_result_values_from_output(metric, text)
-  if not result:
-    result = _parse_histogram_values_from_output(metric, text)
-  return bool(len(result)), result
-
-
-# TODO: Deprecate the text parsing approach to get results in favor of
-#       chartjson.
-def _parse_result_values_from_output(metric, text):  # pragma: no cover
-  """Attempts to parse a metric in the format RESULT <graph>: <trace>= ...
-
-  Args:
-    metric: The metric as a list of [<trace>, <value>] string pairs.
-    text: The text to parse the metric values from.
-
-  Returns:
-    A list of floating point numbers found.
-  """
-  if not text:
-    return [False, None]
-  # Format is: RESULT <graph>: <trace>= <value> <units>
-  metric_re = re.escape('RESULT %s: %s=' % (metric[0], metric[1]))
-
-  # The log will be parsed looking for format:
-  # <*>RESULT <graph_name>: <trace_name>= <value>
-  single_result_re = re.compile(
-      metric_re + r'\s*(?P<VALUE>[-]?\d*(\.\d*)?)')
-
-  # The log will be parsed looking for format:
-  # <*>RESULT <graph_name>: <trace_name>= [<value>,value,value,...]
-  multi_results_re = re.compile(
-      metric_re + r'\s*\[\s*(?P<VALUES>[-]?[\d\., ]+)\s*\]')
-
-  # The log will be parsed looking for format:
-  # <*>RESULT <graph_name>: <trace_name>= {<mean>, <std deviation>}
-  mean_stddev_re = re.compile(
-      metric_re +
-      r'\s*\{\s*(?P<MEAN>[-]?\d*(\.\d*)?),\s*(?P<STDDEV>\d+(\.\d*)?)\s*\}')
-
-  text_lines = text.split('\n')
-  values_list = []
-  for current_line in text_lines:
-    # Parse the output from the performance test for the metric we're
-    # interested in.
-    single_result_match = single_result_re.search(current_line)
-    multi_results_match = multi_results_re.search(current_line)
-    mean_stddev_match = mean_stddev_re.search(current_line)
-    if (single_result_match is not None and single_result_match.group('VALUE')):
-      values_list += [single_result_match.group('VALUE')]
-    elif (multi_results_match is not None and
-          multi_results_match.group('VALUES')):
-      metric_values = multi_results_match.group('VALUES')
-      values_list += metric_values.split(',')
-    elif (mean_stddev_match is not None and
-          mean_stddev_match.group('MEAN')):
-      values_list += [mean_stddev_match.group('MEAN')]
-
-  list_of_floats = []
-  # It seems the pythonic way to do this is to try to cast and catch the error.
-  for v in values_list:
-    try:
-      list_of_floats.append(float(v))
-    except ValueError:
-      pass
-  return list_of_floats
-
-
-def _parse_histogram_values_from_output(metric, text):  # pragma: no cover
-  """Attempts to parse a metric in the format HISTOGRAM <graph: <trace>.
-
-  Args:
-    metric: The metric as a list of [<trace>, <value>] strings.
-    text: The text to parse the metric values from.
-
-  Returns:
-    A list of floating point numbers found, [] if none were found.
-  """
-  metric_formatted = 'HISTOGRAM %s: %s= ' % (metric[0], metric[1])
-
-  text_lines = text.split('\n')
-  values_list = []
-
-  for current_line in text_lines:
-    if metric_formatted in current_line:
-      current_line = current_line[len(metric_formatted):]
-
-      try:
-        histogram_values = eval(current_line)
-
-        for b in histogram_values['buckets']:
-          average_for_bucket = float(b['high'] + b['low']) * 0.5
-          # Extends the list with N-elements with the average for that bucket.
-          values_list.extend([average_for_bucket] * b['count'])
-      except Exception:
-        pass
-
-  return values_list