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executable file
·78 lines (67 loc) · 2.29 KB
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#!/usr/bin/env python3
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
import collections
import io
import json
import os
import sys
from tabulate import tabulate
import matplotlib.pyplot as plt
LIBRARIES = ('orjson', 'ujson', 'rapidjson', 'json')
COLOR = ('blue', 'green', 'red', 'blue')
def aggregate():
benchmarks_dir = os.path.join('.benchmarks', os.listdir('.benchmarks')[0])
res = collections.defaultdict(dict)
for filename in os.listdir(benchmarks_dir):
with open(os.path.join(benchmarks_dir, filename), 'r') as fileh:
data = json.loads(fileh.read())
for each in data['benchmarks']:
res[each['group']][each['extra_info']['lib']] = {
'data': [
val * 1000 for val in each['stats']['data']
],
'median': each['stats']['median'] * 1000,
'ops': each['stats']['ops'],
}
return res
def box(obj):
for group, val in sorted(obj.items()):
data = []
for lib in LIBRARIES:
data.append(val[lib]['data'])
fig = plt.figure(1, figsize=(9, 6))
ax = fig.add_subplot(111)
bp = ax.boxplot(data, vert=False, labels=LIBRARIES)
ax.set_xlim(left=0)
ax.set_xlabel('milliseconds')
plt.title(group)
plt.savefig('doc/{}.png'.format(group.replace(' ', '_').replace('.json', '')))
plt.close()
def tab(obj):
buf = io.StringIO()
headers = ('Library', 'Median (milliseconds)', 'Operations per second', 'Relative (latency)')
for group, val in sorted(obj.items()):
buf.write('\n' + '#### ' + group + '\n\n')
table = []
for lib in LIBRARIES:
table.append(
[lib, val[lib]['median'], '%.1f' % val[lib]['ops'], 0]
)
baseline = table[0][1]
for each in table:
each[3] = '%.2f' % (each[1] / baseline)
each[1] = '%.2f' % each[1]
buf.write(tabulate(table, headers, tablefmt='grid') + '\n')
print(
buf.getvalue()
.replace('-', '')
.replace('=', '-')
.replace('+', '|')
.replace('|||||', '')
.replace('\n\n', '\n')
)
try:
locals()[sys.argv[1]](aggregate())
except KeyError:
sys.stderr.write("usage: graph (box|tab)\n")
sys.exit(1)