The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#) https://grpc.io/
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#!/usr/bin/env python2.7
# Copyright 2017, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following disclaimer
# in the documentation and/or other materials provided with the
# distribution.
# * Neither the name of Google Inc. nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
""" Computes the diff between two bm runs and outputs significant results """
import bm_constants
import bm_speedup
import sys
import os
sys.path.append(os.path.join(os.path.dirname(sys.argv[0]), '..'))
import bm_json
import json
import tabulate
import argparse
import collections
import subprocess
verbose = False
def _median(ary):
ary = sorted(ary)
n = len(ary)
if n % 2 == 0:
return (ary[n / 2] + ary[n / 2 + 1]) / 2.0
else:
return ary[n / 2]
def _args():
argp = argparse.ArgumentParser(
description='Perform diff on microbenchmarks')
argp.add_argument(
'-t',
'--track',
choices=sorted(bm_constants._INTERESTING),
nargs='+',
default=sorted(bm_constants._INTERESTING),
help='Which metrics to track')
argp.add_argument(
'-b',
'--benchmarks',
nargs='+',
choices=bm_constants._AVAILABLE_BENCHMARK_TESTS,
default=bm_constants._AVAILABLE_BENCHMARK_TESTS,
help='Which benchmarks to run')
argp.add_argument(
'-l',
'--loops',
type=int,
default=20,
help='Number of times to loops the benchmarks. Must match what was passed to bm_run.py'
)
argp.add_argument('-n', '--new', type=str, help='New benchmark name')
argp.add_argument('-o', '--old', type=str, help='Old benchmark name')
argp.add_argument(
'-v', '--verbose', type=bool, help='print details of before/after')
args = argp.parse_args()
global verbose
if args.verbose: verbose = True
assert args.new
assert args.old
return args
def _maybe_print(str):
if verbose: print str
class Benchmark:
def __init__(self):
self.samples = {
True: collections.defaultdict(list),
False: collections.defaultdict(list)
}
self.final = {}
def add_sample(self, track, data, new):
for f in track:
if f in data:
self.samples[new][f].append(float(data[f]))
def process(self, track, new_name, old_name):
for f in sorted(track):
new = self.samples[True][f]
old = self.samples[False][f]
if not new or not old: continue
mdn_diff = abs(_median(new) - _median(old))
_maybe_print('%s: %s=%r %s=%r mdn_diff=%r' %
(f, new_name, new, old_name, old, mdn_diff))
s = bm_speedup.speedup(new, old)
if abs(s) > 3 and mdn_diff > 0.5:
self.final[f] = '%+d%%' % s
return self.final.keys()
def skip(self):
return not self.final
def row(self, flds):
return [self.final[f] if f in self.final else '' for f in flds]
def _read_json(filename):
try:
with open(filename) as f:
return json.loads(f.read())
except ValueError, e:
return None
def diff(bms, loops, track, old, new):
benchmarks = collections.defaultdict(Benchmark)
for bm in bms:
for loop in range(0, loops):
for line in subprocess.check_output(['bm_diff_%s/opt/%s' % (old, bm),
'--benchmark_list_tests']).splitlines():
stripped_line = line.strip().replace("/","_").replace("<","_").replace(">","_")
js_new_ctr = _read_json('%s.%s.counters.%s.%d.json' % (bm, stripped_line, new, loop))
js_new_opt = _read_json('%s.%s.opt.%s.%d.json' % (bm, stripped_line, new, loop))
js_old_ctr = _read_json('%s.%s.counters.%s.%d.json' % (bm, stripped_line, old, loop))
js_old_opt = _read_json('%s.%s.opt.%s.%d.json' % (bm, stripped_line, old, loop))
if js_new_ctr:
for row in bm_json.expand_json(js_new_ctr, js_new_opt):
name = row['cpp_name']
if name.endswith('_mean') or name.endswith('_stddev'):
continue
benchmarks[name].add_sample(track, row, True)
if js_old_ctr:
for row in bm_json.expand_json(js_old_ctr, js_old_opt):
name = row['cpp_name']
if name.endswith('_mean') or name.endswith('_stddev'):
continue
benchmarks[name].add_sample(track, row, False)
really_interesting = set()
for name, bm in benchmarks.items():
_maybe_print(name)
really_interesting.update(bm.process(track, new, old))
fields = [f for f in track if f in really_interesting]
headers = ['Benchmark'] + fields
rows = []
for name in sorted(benchmarks.keys()):
if benchmarks[name].skip(): continue
rows.append([name] + benchmarks[name].row(fields))
if rows:
return tabulate.tabulate(rows, headers=headers, floatfmt='+.2f')
else:
return None
if __name__ == '__main__':
args = _args()
print diff(args.benchmarks, args.loops, args.track, args.old, args.new)