181f60c8c7
Make results_to_text a tool to dump results saved in JSON file. Signed-off-by: Vladimir Sementsov-Ogievskiy <vsementsov@virtuozzo.com> Message-Id: <20201021145859.11201-21-vsementsov@virtuozzo.com> Reviewed-by: Max Reitz <mreitz@redhat.com> Signed-off-by: Max Reitz <mreitz@redhat.com>
127 lines
3.7 KiB
Python
Executable File
127 lines
3.7 KiB
Python
Executable File
#!/usr/bin/env python3
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#
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# Simple benchmarking framework
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#
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# Copyright (c) 2019 Virtuozzo International GmbH.
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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#
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import math
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import tabulate
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# We want leading whitespace for difference row cells (see below)
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tabulate.PRESERVE_WHITESPACE = True
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def format_value(x, stdev):
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stdev_pr = stdev / x * 100
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if stdev_pr < 1.5:
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# don't care too much
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return f'{x:.2g}'
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else:
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return f'{x:.2g} ± {math.ceil(stdev_pr)}%'
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def result_to_text(result):
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"""Return text representation of bench_one() returned dict."""
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if 'average' in result:
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s = format_value(result['average'], result['stdev'])
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if 'n-failed' in result:
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s += '\n({} failed)'.format(result['n-failed'])
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return s
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else:
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return 'FAILED'
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def results_dimension(results):
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dim = None
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for case in results['cases']:
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for env in results['envs']:
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res = results['tab'][case['id']][env['id']]
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if dim is None:
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dim = res['dimension']
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else:
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assert dim == res['dimension']
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assert dim in ('iops', 'seconds')
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return dim
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def results_to_text(results):
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"""Return text representation of bench() returned dict."""
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n_columns = len(results['envs'])
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named_columns = n_columns > 2
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dim = results_dimension(results)
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tab = []
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if named_columns:
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# Environment columns are named A, B, ...
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tab.append([''] + [chr(ord('A') + i) for i in range(n_columns)])
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tab.append([''] + [c['id'] for c in results['envs']])
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for case in results['cases']:
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row = [case['id']]
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case_results = results['tab'][case['id']]
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for env in results['envs']:
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res = case_results[env['id']]
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row.append(result_to_text(res))
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tab.append(row)
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# Add row of difference between columns. For each column starting from
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# B we calculate difference with all previous columns.
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row = ['', ''] # case name and first column
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for i in range(1, n_columns):
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cell = ''
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env = results['envs'][i]
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res = case_results[env['id']]
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if 'average' not in res:
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# Failed result
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row.append(cell)
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continue
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for j in range(0, i):
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env_j = results['envs'][j]
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res_j = case_results[env_j['id']]
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cell += ' '
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if 'average' not in res_j:
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# Failed result
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cell += '--'
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continue
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col_j = tab[0][j + 1] if named_columns else ''
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diff_pr = round((res['average'] - res_j['average']) /
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res_j['average'] * 100)
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cell += f' {col_j}{diff_pr:+}%'
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row.append(cell)
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tab.append(row)
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return f'All results are in {dim}\n\n' + tabulate.tabulate(tab)
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if __name__ == '__main__':
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import sys
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import json
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if len(sys.argv) < 2:
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print(f'USAGE: {sys.argv[0]} results.json')
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exit(1)
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with open(sys.argv[1]) as f:
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print(results_to_text(json.load(f)))
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