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benchplot.py
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#!/usr/bin/env python
import argparse # for ArgumentParser
import subprocess # for Popen
import tempfile # for NamedTemporaryFile
import os # for remove
class gnuplot(object):
output = "result.png"
script = """
set terminal png size 1024, 768
set output "{}.png"
set title "re2 benchlog"
set datafile separator ";"
set grid x y
set ylabel "MB/s"
set autoscale
plot """
template = """'{}' using 1:5:xticlabels(2) with linespoints linewidth 3 title "{}",\\\n"""
benchdata = dict()
tempfiles = []
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
"""
remove all temporary files
"""
for filename in self.tempfiles:
os.remove(filename)
def parse_re2_benchlog(self, filename):
"""
parse the input benchlog and return a dictionary contain bench data
"""
benchdata = self.benchdata
with open(filename) as f:
for raw in f.readlines():
data = raw.split('\t')
if len(data) == 4:
data = data[0].split('/') + data[1:]
data = list(map(str.strip, data))
if not benchdata.get(data[0]):
benchdata[data[0]] = [ data[1:] ]
else:
benchdata[data[0]].append(data[1:])
def gen_csv(self):
"""
generate temporary csv files
"""
for name, data in self.benchdata.items():
with tempfile.NamedTemporaryFile(delete=False) as f:
for index, line in enumerate(data):
f.write('{};{}\n'.format(index, ';'.join(line)).encode())
self.tempfiles.append(f.name)
self.script = self.script + self.template.format(f.name, name)
def run(self):
self.gen_csv()
script = self.script[:-3].format(self.output)
command = subprocess.Popen(['gnuplot'], stdin=subprocess.PIPE)
command.communicate(script.encode())
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='generate plots for benchlog')
parser.add_argument('benchlog', type=str, help='benchlog generated by re2')
args = parser.parse_args()
try:
subprocess.Popen(['gnuplot'], stdin=subprocess.PIPE)
except FileNotFoundError:
print('you can install "gnuplot" to generate plots automatically')
exit(1)
with gnuplot() as plot:
plot.output = args.benchlog
plot.parse_re2_benchlog(args.benchlog)
plot.run()