json2trace

#!/usr/bin/env python
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

import argparse
import json
import smap
import trace_data
import urllib

SECONDS_TO_NANOSECONDS = (1000*1000)
SAMPLE_DELTA_IN_SECONDS = 0.0001

class Marker(object):
    def __init__(self, _name, _timestamp, _depth, _is_end, _ident, url, line, col):
        self.name = _name
        self.timestamp = _timestamp
        self.depth = _depth
        self.is_end = _is_end
        self.ident = _ident
        self.url = url
        self.line = line
        self.col = col

# sort markers making sure they are ordered by timestamp then depth of function call
# and finally that markers of the same ident are sorted in the order begin then end
    def __cmp__(self, other):
        if self.timestamp < other.timestamp:
            return -1
        if self.timestamp > other.timestamp:
            return 1
        if self.depth < other.depth:
            return -1
        if self.depth > other.depth:
            return 1
        if self.ident == other.ident:
            if self.is_end:
                return 1
        return 0

# calculate marker name based on combination of function name and location
def _calcname(entry):
    funcname = ""
    if "functionName" in entry:
        funcname = funcname + entry["functionName"]
    return funcname

def _calcurl(mapcache, entry, map_file):
    if entry.url not in mapcache:
        map_url = entry.url.replace('.bundle', '.map')

        if map_url != entry.url:
            if map_file:
                print('Loading sourcemap from:' + map_file)
                map_url = map_file

            try:
                url_file = urllib.urlopen(map_url)
                if url_file != None:
                    entries = smap.parse(url_file)
                    mapcache[entry.url] = entries
            except Exception, e:
                mapcache[entry.url] = []

    if entry.url in mapcache:
        source_entry = smap.find(mapcache[entry.url], entry.line, entry.col)
        if source_entry:
            entry.url = 'file://' + source_entry.src
            entry.line = source_entry.src_line
            entry.col = source_entry.src_col

def _compute_markers(markers, call_point, depth):
    name = _calcname(call_point)
    ident = len(markers)
    url = ""
    lineNumber = -1
    columnNumber = -1
    if "url" in call_point:
        url = call_point["url"]
    if "lineNumber" in call_point:
        lineNumber = call_point["lineNumber"]
    if "columnNumber" in call_point:
        columnNumber = call_point["columnNumber"]

    for call in call_point["calls"]:
        markers.append(Marker(name, call["startTime"], depth, 0, ident, url, lineNumber, columnNumber))
        markers.append(Marker(name, call["startTime"] + call["totalTime"], depth, 1, ident, url, lineNumber, columnNumber))
        ident = ident + 2
    if "children" in call_point:
        for child in call_point["children"]:
            _compute_markers(markers, child, depth+1);

def _find_child(children, name):
    for child in children:
        if child['functionName'] == name:
            return child
    return None

def _add_entry_cpuprofiler_program(newtime, cpuprofiler):
    curnode = _find_child(cpuprofiler['head']['children'], '(program)')
    if cpuprofiler['lastTime'] != None:
        lastTime = cpuprofiler['lastTime']
        while lastTime < newtime:
            curnode['hitCount'] += 1
            cpuprofiler['samples'].append(curnode['callUID'])
            cpuprofiler['timestamps'].append(int(lastTime*SECONDS_TO_NANOSECONDS))
            lastTime += SAMPLE_DELTA_IN_SECONDS
        cpuprofiler['lastTime'] = lastTime
    else:
        cpuprofiler['lastTime'] = newtime


def _add_entry_cpuprofiler(stack, newtime, cpuprofiler):
    index = len(stack) - 1
    marker = stack[index]

    if marker.name not in cpuprofiler['markers']:
        cpuprofiler['markers'][marker.name] = cpuprofiler['id']
        cpuprofiler['callUID'] += 1
    callUID = cpuprofiler['markers'][marker.name]

    curnode = cpuprofiler['head']
    index = 0
    while index < len(stack):
        newnode = _find_child(curnode['children'], stack[index].name)
        if newnode == None:
            newnode = {}
            newnode['callUID'] = callUID
            newnode['url'] = marker.url
            newnode['functionName'] = stack[index].name
            newnode['hitCount'] = 0
            newnode['lineNumber'] = marker.line
            newnode['columnNumber'] = marker.col
            newnode['scriptId'] = callUID
            newnode['positionTicks'] = []
            newnode['id'] = cpuprofiler['id']
            cpuprofiler['id'] += 1
            newnode['children'] = []
            curnode['children'].append(newnode)
            curnode['deoptReason'] = ''
        curnode = newnode
        index += 1

    if cpuprofiler['lastTime'] == None:
        cpuprofiler['lastTime'] = newtime

    if cpuprofiler['lastTime'] != None:
        lastTime = cpuprofiler['lastTime']
        while lastTime < newtime:
            curnode['hitCount'] += 1
            if len(curnode['positionTicks']) == 0:
                ticks = {}
                ticks['line'] = curnode['callUID']
                ticks['ticks'] = 0
                curnode['positionTicks'].append(ticks)
            curnode['positionTicks'][0]['ticks'] += 1
            cpuprofiler['samples'].append(curnode['callUID'])
            cpuprofiler['timestamps'].append(int(lastTime*1000*1000))
            lastTime += 0.0001
        cpuprofiler['lastTime'] = lastTime

def _create_default_cpuprofiler_node(name, _id, _uid):
    return {'functionName': name,
            'scriptId':'0',
            'url':'',
            'lineNumber':0,
            'columnNumber':0,
            'positionTicks':[],
            'id':_id,
            'callUID':_uid,
            'children': [],
            'hitCount': 0,
            'deoptReason':''}

def main():
    parser = argparse.ArgumentParser(description="Converts JSON profile format to fbsystrace text output")

    parser.add_argument(
        "-o",
        dest = "output_file",
        default = None,
        help = "Output file for trace data")
    parser.add_argument(
        "-cpuprofiler",
        dest = "output_cpuprofiler",
        default = None,
        help = "Output file for cpuprofiler data")
    parser.add_argument(
        "-map",
        dest = "map_file",
        default = None,
        help = "Map file for symbolicating")
    parser.add_argument( "file", help = "JSON trace input_file")

    args = parser.parse_args()

    markers = []
    with open(args.file, "r") as trace_file:
        trace = json.load(trace_file)
        for root_entry in trace["rootNodes"]:
            _compute_markers(markers, root_entry, 0)

    mapcache = {}
    for m in markers:
        _calcurl(mapcache, m, args.map_file)

    sorted_markers = list(sorted(markers));

    if args.output_cpuprofiler != None:
        cpuprofiler = {}
        cpuprofiler['startTime'] = None
        cpuprofiler['endTime'] = None
        cpuprofiler['lastTime'] = None
        cpuprofiler['id'] = 4
        cpuprofiler['callUID'] = 4
        cpuprofiler['samples'] = []
        cpuprofiler['timestamps'] = []
        cpuprofiler['markers'] = {}
        cpuprofiler['head'] = _create_default_cpuprofiler_node('(root)', 1, 1)
        cpuprofiler['head']['children'].append(_create_default_cpuprofiler_node('(root)', 2, 2))
        cpuprofiler['head']['children'].append(_create_default_cpuprofiler_node('(program)', 3, 3))
        marker_stack = []
        with open(args.output_cpuprofiler, 'w') as file_out:
            for marker in sorted_markers:
                if len(marker_stack):
                    _add_entry_cpuprofiler(marker_stack, marker.timestamp, cpuprofiler)
                else:
                    _add_entry_cpuprofiler_program(marker.timestamp, cpuprofiler)
                if marker.is_end:
                    marker_stack.pop()
                else:
                    marker_stack.append(marker)
            cpuprofiler['startTime'] = cpuprofiler['timestamps'][0] / 1000000.0
            cpuprofiler['endTime'] = cpuprofiler['timestamps'][len(cpuprofiler['timestamps']) - 1] / 1000000.0
            json.dump(cpuprofiler, file_out, sort_keys=False, indent=4, separators=(',', ': '))


    if args.output_file != None:
      with open(args.output_file,"w") as trace_file:
        for marker in sorted_markers:
            start_or_end = None
            if marker.is_end:
                start_or_end = "E"
            else:
                start_or_end = "B"
            #output with timestamp at high level of precision
            trace_file.write("json-0 [000] .... {0:.12f}: tracing_mark_write: {1}|0|{2}\n".format(
                             marker.timestamp,
                             start_or_end,
                             marker.name))

main()