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tadeuzagallofacebook-github-bot-7
tadeuzagallo
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Automatically save and convert JavaScript profile to chrome format
Summary: @​public Migrate scripts to open source and add new route on the packager to directly convert profiler outputs to a devtools compatible format. Reviewed By: @jspahrsummers Differential Revision: D2425740
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‎JSCLegacyProfiler/json2trace‎

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#!/usr/bin/env python
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import argparse
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import json
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import smap
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import trace_data
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import urllib
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SECONDS_TO_NANOSECONDS = (1000*1000)
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SAMPLE_DELTA_IN_SECONDS = 0.0001
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class Marker(object):
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def __init__(self, _name, _timestamp, _depth, _is_end, _ident, url, line, col):
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self.name = _name
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self.timestamp = _timestamp
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self.depth = _depth
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self.is_end = _is_end
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self.ident = _ident
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self.url = url
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self.line = line
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self.col = col
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# sort markers making sure they are ordered by timestamp then depth of function call
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# and finally that markers of the same ident are sorted in the order begin then end
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def __cmp__(self, other):
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if self.timestamp < other.timestamp:
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return -1
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if self.timestamp > other.timestamp:
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return 1
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if self.depth < other.depth:
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return -1
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if self.depth > other.depth:
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return 1
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if self.ident == other.ident:
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if self.is_end:
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return 1
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return 0
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# calculate marker name based on combination of function name and location
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def _calcname(entry):
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funcname = ""
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if "functionName" in entry:
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funcname = funcname + entry["functionName"]
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return funcname
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def _calcurl(mapcache, entry, map_file):
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if entry.url not in mapcache:
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map_url = entry.url.replace('.bundle', '.map')
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if map_url != entry.url:
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if map_file:
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print('Loading sourcemap from:' + map_file)
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map_url = map_file
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try:
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url_file = urllib.urlopen(map_url)
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if url_file != None:
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entries = smap.parse(url_file)
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mapcache[entry.url] = entries
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except Exception, e:
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mapcache[entry.url] = []
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if entry.url in mapcache:
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source_entry = smap.find(mapcache[entry.url], entry.line, entry.col)
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if source_entry:
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entry.url = 'file://' + source_entry.src
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entry.line = source_entry.src_line
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entry.col = source_entry.src_col
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def _compute_markers(markers, call_point, depth):
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name = _calcname(call_point)
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ident = len(markers)
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url = ""
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lineNumber = -1
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columnNumber = -1
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if "url" in call_point:
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url = call_point["url"]
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if "lineNumber" in call_point:
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lineNumber = call_point["lineNumber"]
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if "columnNumber" in call_point:
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columnNumber = call_point["columnNumber"]
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for call in call_point["calls"]:
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markers.append(Marker(name, call["startTime"], depth, 0, ident, url, lineNumber, columnNumber))
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markers.append(Marker(name, call["startTime"] + call["totalTime"], depth, 1, ident, url, lineNumber, columnNumber))
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ident = ident + 2
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if "children" in call_point:
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for child in call_point["children"]:
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_compute_markers(markers, child, depth+1);
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def _find_child(children, name):
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for child in children:
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if child['functionName'] == name:
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return child
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return None
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def _add_entry_cpuprofiler_program(newtime, cpuprofiler):
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curnode = _find_child(cpuprofiler['head']['children'], '(program)')
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if cpuprofiler['lastTime'] != None:
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lastTime = cpuprofiler['lastTime']
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while lastTime < newtime:
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curnode['hitCount'] += 1
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cpuprofiler['samples'].append(curnode['callUID'])
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cpuprofiler['timestamps'].append(int(lastTime*SECONDS_TO_NANOSECONDS))
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lastTime += SAMPLE_DELTA_IN_SECONDS
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cpuprofiler['lastTime'] = lastTime
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else:
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cpuprofiler['lastTime'] = newtime
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def _add_entry_cpuprofiler(stack, newtime, cpuprofiler):
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index = len(stack) - 1
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marker = stack[index]
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if marker.name not in cpuprofiler['markers']:
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cpuprofiler['markers'][marker.name] = cpuprofiler['id']
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cpuprofiler['callUID'] += 1
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callUID = cpuprofiler['markers'][marker.name]
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curnode = cpuprofiler['head']
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index = 0
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while index < len(stack):
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newnode = _find_child(curnode['children'], stack[index].name)
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if newnode == None:
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newnode = {}
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newnode['callUID'] = callUID
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newnode['url'] = marker.url
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newnode['functionName'] = stack[index].name
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newnode['hitCount'] = 0
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newnode['lineNumber'] = marker.line
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newnode['columnNumber'] = marker.col
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newnode['scriptId'] = callUID
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newnode['positionTicks'] = []
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newnode['id'] = cpuprofiler['id']
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cpuprofiler['id'] += 1
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newnode['children'] = []
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curnode['children'].append(newnode)
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curnode['deoptReason'] = ''
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curnode = newnode
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index += 1
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if cpuprofiler['lastTime'] == None:
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cpuprofiler['lastTime'] = newtime
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if cpuprofiler['lastTime'] != None:
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lastTime = cpuprofiler['lastTime']
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while lastTime < newtime:
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curnode['hitCount'] += 1
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if len(curnode['positionTicks']) == 0:
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ticks = {}
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ticks['line'] = curnode['callUID']
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ticks['ticks'] = 0
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curnode['positionTicks'].append(ticks)
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curnode['positionTicks'][0]['ticks'] += 1
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cpuprofiler['samples'].append(curnode['callUID'])
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cpuprofiler['timestamps'].append(int(lastTime*1000*1000))
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lastTime += 0.0001
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cpuprofiler['lastTime'] = lastTime
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def _create_default_cpuprofiler_node(name, _id, _uid):
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return {'functionName': name,
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'scriptId':'0',
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'url':'',
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'lineNumber':0,
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'columnNumber':0,
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'positionTicks':[],
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'id':_id,
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'callUID':_uid,
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'children': [],
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'hitCount': 0,
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'deoptReason':''}
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def main():
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parser = argparse.ArgumentParser(description="Converts JSON profile format to fbsystrace text output")
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parser.add_argument(
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"-o",
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dest = "output_file",
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default = None,
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help = "Output file for trace data")
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parser.add_argument(
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"-cpuprofiler",
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dest = "output_cpuprofiler",
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default = None,
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help = "Output file for cpuprofiler data")
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parser.add_argument(
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"-map",
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dest = "map_file",
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default = None,
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help = "Map file for symbolicating")
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parser.add_argument( "file", help = "JSON trace input_file")
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args = parser.parse_args()
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markers = []
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with open(args.file, "r") as trace_file:
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trace = json.load(trace_file)
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for root_entry in trace["rootNodes"]:
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_compute_markers(markers, root_entry, 0)
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mapcache = {}
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for m in markers:
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_calcurl(mapcache, m, args.map_file)
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sorted_markers = list(sorted(markers));
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if args.output_cpuprofiler != None:
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cpuprofiler = {}
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cpuprofiler['startTime'] = None
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cpuprofiler['endTime'] = None
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cpuprofiler['lastTime'] = None
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cpuprofiler['id'] = 4
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cpuprofiler['callUID'] = 4
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cpuprofiler['samples'] = []
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cpuprofiler['timestamps'] = []
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cpuprofiler['markers'] = {}
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cpuprofiler['head'] = _create_default_cpuprofiler_node('(root)', 1, 1)
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cpuprofiler['head']['children'].append(_create_default_cpuprofiler_node('(root)', 2, 2))
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cpuprofiler['head']['children'].append(_create_default_cpuprofiler_node('(program)', 3, 3))
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marker_stack = []
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with open(args.output_cpuprofiler, 'w') as file_out:
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for marker in sorted_markers:
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if len(marker_stack):
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_add_entry_cpuprofiler(marker_stack, marker.timestamp, cpuprofiler)
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else:
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_add_entry_cpuprofiler_program(marker.timestamp, cpuprofiler)
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if marker.is_end:
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marker_stack.pop()
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else:
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marker_stack.append(marker)
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cpuprofiler['startTime'] = cpuprofiler['timestamps'][0] / 1000000.0
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cpuprofiler['endTime'] = cpuprofiler['timestamps'][len(cpuprofiler['timestamps']) - 1] / 1000000.0
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json.dump(cpuprofiler, file_out, sort_keys=False, indent=4, separators=(',', ': '))
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if args.output_file != None:
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with open(args.output_file,"w") as trace_file:
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for marker in sorted_markers:
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start_or_end = None
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if marker.is_end:
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start_or_end = "E"
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else:
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start_or_end = "B"
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#output with timestamp at high level of precision
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trace_file.write("json-0 [000] .... {0:.12f}: tracing_mark_write: {1}|0|{2}\n".format(
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marker.timestamp,
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start_or_end,
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marker.name))
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main()

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