blob: d561e5e2dbe03c97d2e89740d5bcfdbbf067d341 [file] [log] [blame]
#!/usr/bin/env python3
#
# Simple benchmarking framework
#
# Copyright (c) 2019 Virtuozzo International GmbH.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
import math
import tabulate
# We want leading whitespace for difference row cells (see below)
tabulate.PRESERVE_WHITESPACE = True
def format_value(x, stdev):
stdev_pr = stdev / x * 100
if stdev_pr < 1.5:
# don't care too much
return f'{x:.2g}'
else:
return f'{x:.2g} ± {math.ceil(stdev_pr)}%'
def result_to_text(result):
"""Return text representation of bench_one() returned dict."""
if 'average' in result:
s = format_value(result['average'], result['stdev'])
if 'n-failed' in result:
s += '\n({} failed)'.format(result['n-failed'])
return s
else:
return 'FAILED'
def results_dimension(results):
dim = None
for case in results['cases']:
for env in results['envs']:
res = results['tab'][case['id']][env['id']]
if dim is None:
dim = res['dimension']
else:
assert dim == res['dimension']
assert dim in ('iops', 'seconds')
return dim
def results_to_text(results):
"""Return text representation of bench() returned dict."""
n_columns = len(results['envs'])
named_columns = n_columns > 2
dim = results_dimension(results)
tab = []
if named_columns:
# Environment columns are named A, B, ...
tab.append([''] + [chr(ord('A') + i) for i in range(n_columns)])
tab.append([''] + [c['id'] for c in results['envs']])
for case in results['cases']:
row = [case['id']]
case_results = results['tab'][case['id']]
for env in results['envs']:
res = case_results[env['id']]
row.append(result_to_text(res))
tab.append(row)
# Add row of difference between columns. For each column starting from
# B we calculate difference with all previous columns.
row = ['', ''] # case name and first column
for i in range(1, n_columns):
cell = ''
env = results['envs'][i]
res = case_results[env['id']]
if 'average' not in res:
# Failed result
row.append(cell)
continue
for j in range(0, i):
env_j = results['envs'][j]
res_j = case_results[env_j['id']]
cell += ' '
if 'average' not in res_j:
# Failed result
cell += '--'
continue
col_j = tab[0][j + 1] if named_columns else ''
diff_pr = round((res['average'] - res_j['average']) /
res_j['average'] * 100)
cell += f' {col_j}{diff_pr:+}%'
row.append(cell)
tab.append(row)
return f'All results are in {dim}\n\n' + tabulate.tabulate(tab)
if __name__ == '__main__':
import sys
import json
if len(sys.argv) < 2:
print(f'USAGE: {sys.argv[0]} results.json')
exit(1)
with open(sys.argv[1]) as f:
print(results_to_text(json.load(f)))