# Copyright 2016 Google Inc. All Rights Reserved.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

import argparse

import csv

import json

import os

import sys

def generate_csv(filename, tag):

"""Extract function name, time used and memory usage from the metadata and write to the output CSV file.

Args:

filename (str): Filename of the performance json file to read

tag (str): Tag of the docker container

"""

with open(filename) as input:

data = json.load(input)

benchmarks = data["benchmarks"]

runtime_version = os.path.basename(filename).split(".json")[0]

# Write data to CSV file

with open("{}.csv".format(os.path.splitext(filename)[0]), "wb") as output:

csv_writer = csv.writer(output, delimiter=',')

for benchmark in benchmarks:

try:

# Get the function name

func_name = benchmark["metadata"]["name"]

# Get the time used for this function, convert to millisecond

time_used = float(benchmark["runs"][0]["values"][0]) * 1000

# Get the memory usage, convert to MB

mem_usage = float(benchmark["metadata"]["mem_max_rss"]) / float(1<<20)

line = [tag, runtime_version, func_name, time_used, mem_usage]

# Write to CSV file

csv_writer.writerow(line)

except KeyError:

# Skip the benchmark result if it does not contain the fields we want

pass

def get_averages(filename, tag):

"""Calculate the averages of time_used and memory_usage and append to CSV file.

Args:

filename (str): Filename of the performance json file to read

tag (str): Tag of the docker container

"""

with open("{}.csv".format(os.path.splitext(filename)[0]), "rb") as input:

lines = input.readlines()

# Get the two columns of times_used and mem_usage

rows_of_data = [map(float, line.split(',')[-2:]) for line in lines]

# Calculate the sum of the two columns

col_sums = map(sum, zip(*rows_of_data))

# Calculate the average of the two columns by using the sum divided by the total number of lines

averages = [col_sum / len(lines) for col_sum in col_sums]

# Get the runtime version from filename

runtime_version = os.path.basename(filename).split(".json")[0]

# Write the averages to CSV file in appending mode

with open("{}/averages.csv".format(tag), "a+") as output:

try:

csv_writer = csv.writer(output, delimiter=',')

csv_writer.writerow([tag, runtime_version] + averages)

except IOError:

print "Could not write averages to file."

def parse_args(argv):

"""Parse and validate command line flags"""

parser = argparse.ArgumentParser(

description='Read the python performance json file and extract data to genarate CSV file.'

)

parser.add_argument(

'--filename',

help='Filename of the performance json file to read'

)

parser.add_argument(

'--tag',

help='Tag of the docker container'

)

args = parser.parse_args(argv[1:])

return args

def main():

args = parse_args(sys.argv)

generate_csv(args.filename, args.tag)

get_averages(args.filename, args.tag)

if __name__ == '__main__':

main()