The Tor Browser / file comparison
comparison: media/webrtc/trunk/build/android/pylib/json_perf_parser.py
media/webrtc/trunk/build/android/pylib/json_perf_parser.py
- branch
- TOR_BUG_3246
- changeset 6
- 8bccb770b82d
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| -1:000000000000 | 0:8a859af22138 |
|---|---|
| 1 # Copyright (c) 2012 The Chromium Authors. All rights reserved. | |
| 2 # Use of this source code is governed by a BSD-style license that can be | |
| 3 # found in the LICENSE file. | |
| 4 | |
| 5 | |
| 6 """A helper module for parsing JSON objects from perf tests results.""" | |
| 7 | |
| 8 import json | |
| 9 | |
| 10 | |
| 11 def GetAverageRunInfo(json_data, name): | |
| 12 """Summarizes TraceEvent JSON data for performance metrics. | |
| 13 | |
| 14 Example JSON Inputs (More tags can be added but these are required): | |
| 15 Measuring Duration: | |
| 16 [ | |
| 17 { "cat": "Java", | |
| 18 "ts": 10000000000, | |
| 19 "ph": "S", | |
| 20 "name": "TestTrace" | |
| 21 }, | |
| 22 { "cat": "Java", | |
| 23 "ts": 10000004000, | |
| 24 "ph": "F", | |
| 25 "name": "TestTrace" | |
| 26 }, | |
| 27 ... | |
| 28 ] | |
| 29 | |
| 30 Measuring Call Frequency (FPS): | |
| 31 [ | |
| 32 { "cat": "Java", | |
| 33 "ts": 10000000000, | |
| 34 "ph": "I", | |
| 35 "name": "TestTraceFPS" | |
| 36 }, | |
| 37 { "cat": "Java", | |
| 38 "ts": 10000004000, | |
| 39 "ph": "I", | |
| 40 "name": "TestTraceFPS" | |
| 41 }, | |
| 42 ... | |
| 43 ] | |
| 44 | |
| 45 Args: | |
| 46 json_data: A list of dictonaries each representing a JSON object. | |
| 47 name: The 'name' tag to filter on in the JSON file. | |
| 48 | |
| 49 Returns: | |
| 50 A dictionary of result data with the following tags: | |
| 51 min: The minimum value tracked. | |
| 52 max: The maximum value tracked. | |
| 53 average: The average of all the values tracked. | |
| 54 count: The number of times the category/name pair was tracked. | |
| 55 type: The type of tracking ('Instant' for instant tags and 'Span' for | |
| 56 begin/end tags. | |
| 57 category: The passed in category filter. | |
| 58 name: The passed in name filter. | |
| 59 data_points: A list of all of the times used to generate this data. | |
| 60 units: The units for the values being reported. | |
| 61 | |
| 62 Raises: | |
| 63 Exception: if entry contains invalid data. | |
| 64 """ | |
| 65 | |
| 66 def EntryFilter(entry): | |
| 67 return entry['cat'] == 'Java' and entry['name'] == name | |
| 68 filtered_entries = filter(EntryFilter, json_data) | |
| 69 | |
| 70 result = {} | |
| 71 | |
| 72 result['min'] = -1 | |
| 73 result['max'] = -1 | |
| 74 result['average'] = 0 | |
| 75 result['count'] = 0 | |
| 76 result['type'] = 'Unknown' | |
| 77 result['category'] = 'Java' | |
| 78 result['name'] = name | |
| 79 result['data_points'] = [] | |
| 80 result['units'] = '' | |
| 81 | |
| 82 total_sum = 0 | |
| 83 | |
| 84 last_val = 0 | |
| 85 val_type = None | |
| 86 for entry in filtered_entries: | |
| 87 if not val_type: | |
| 88 if 'mem' in entry: | |
| 89 val_type = 'mem' | |
| 90 | |
| 91 def GetVal(entry): | |
| 92 return entry['mem'] | |
| 93 | |
| 94 result['units'] = 'kb' | |
| 95 elif 'ts' in entry: | |
| 96 val_type = 'ts' | |
| 97 | |
| 98 def GetVal(entry): | |
| 99 return float(entry['ts']) / 1000.0 | |
| 100 | |
| 101 result['units'] = 'ms' | |
| 102 else: | |
| 103 raise Exception('Entry did not contain valid value info: %s' % entry) | |
| 104 | |
| 105 if not val_type in entry: | |
| 106 raise Exception('Entry did not contain expected value type "%s" ' | |
| 107 'information: %s' % (val_type, entry)) | |
| 108 val = GetVal(entry) | |
| 109 if (entry['ph'] == 'S' and | |
| 110 (result['type'] == 'Unknown' or result['type'] == 'Span')): | |
| 111 result['type'] = 'Span' | |
| 112 last_val = val | |
| 113 elif ((entry['ph'] == 'F' and result['type'] == 'Span') or | |
| 114 (entry['ph'] == 'I' and (result['type'] == 'Unknown' or | |
| 115 result['type'] == 'Instant'))): | |
| 116 if last_val > 0: | |
| 117 delta = val - last_val | |
| 118 if result['min'] == -1 or result['min'] > delta: | |
| 119 result['min'] = delta | |
| 120 if result['max'] == -1 or result['max'] < delta: | |
| 121 result['max'] = delta | |
| 122 total_sum += delta | |
| 123 result['count'] += 1 | |
| 124 result['data_points'].append(delta) | |
| 125 if entry['ph'] == 'I': | |
| 126 result['type'] = 'Instant' | |
| 127 last_val = val | |
| 128 if result['count'] > 0: result['average'] = total_sum / result['count'] | |
| 129 | |
| 130 return result | |
| 131 | |
| 132 | |
| 133 def GetAverageRunInfoFromJSONString(json_string, name): | |
| 134 """Returns the results from GetAverageRunInfo using a JSON string. | |
| 135 | |
| 136 Args: | |
| 137 json_string: The string containing JSON. | |
| 138 name: The 'name' tag to filter on in the JSON file. | |
| 139 | |
| 140 Returns: | |
| 141 See GetAverageRunInfo Returns section. | |
| 142 """ | |
| 143 return GetAverageRunInfo(json.loads(json_string), name) | |
| 144 | |
| 145 | |
| 146 def GetAverageRunInfoFromFile(json_file, name): | |
| 147 """Returns the results from GetAverageRunInfo using a JSON file. | |
| 148 | |
| 149 Args: | |
| 150 json_file: The path to a JSON file. | |
| 151 name: The 'name' tag to filter on in the JSON file. | |
| 152 | |
| 153 Returns: | |
| 154 See GetAverageRunInfo Returns section. | |
| 155 """ | |
| 156 with open(json_file, 'r') as f: | |
| 157 data = f.read() | |
| 158 perf = json.loads(data) | |
| 159 | |
| 160 return GetAverageRunInfo(perf, name) |
