Add simple benchmark table creator. Signed-off-by: Vladimir Sementsov-Ogievskiy <vsementsov@virtuozzo.com> Reviewed-by: Aleksandar Markovic <amarkovic@wavecomp.com> Message-Id: <20200228071914.11746-2-vsementsov@virtuozzo.com> Signed-off-by: Eduardo Habkost <ehabkost@redhat.com>
129 lines
4.5 KiB
Python
129 lines
4.5 KiB
Python
#!/usr/bin/env python
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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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def bench_one(test_func, test_env, test_case, count=5, initial_run=True):
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"""Benchmark one test-case
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test_func -- benchmarking function with prototype
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test_func(env, case), which takes test_env and test_case
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arguments and returns {'seconds': int} (which is benchmark
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result) on success and {'error': str} on error. Returned
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dict may contain any other additional fields.
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test_env -- test environment - opaque first argument for test_func
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test_case -- test case - opaque second argument for test_func
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count -- how many times to call test_func, to calculate average
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initial_run -- do initial run of test_func, which don't get into result
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Returns dict with the following fields:
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'runs': list of test_func results
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'average': average seconds per run (exists only if at least one run
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succeeded)
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'delta': maximum delta between test_func result and the average
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(exists only if at least one run succeeded)
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'n-failed': number of failed runs (exists only if at least one run
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failed)
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"""
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if initial_run:
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print(' #initial run:')
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print(' ', test_func(test_env, test_case))
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runs = []
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for i in range(count):
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print(' #run {}'.format(i+1))
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res = test_func(test_env, test_case)
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print(' ', res)
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runs.append(res)
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result = {'runs': runs}
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successed = [r for r in runs if ('seconds' in r)]
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if successed:
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avg = sum(r['seconds'] for r in successed) / len(successed)
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result['average'] = avg
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result['delta'] = max(abs(r['seconds'] - avg) for r in successed)
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if len(successed) < count:
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result['n-failed'] = count - len(successed)
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return result
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def ascii_one(result):
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"""Return ASCII representation of bench_one() returned dict."""
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if 'average' in result:
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s = '{:.2f} +- {:.2f}'.format(result['average'], result['delta'])
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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 bench(test_func, test_envs, test_cases, *args, **vargs):
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"""Fill benchmark table
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test_func -- benchmarking function, see bench_one for description
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test_envs -- list of test environments, see bench_one
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test_cases -- list of test cases, see bench_one
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args, vargs -- additional arguments for bench_one
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Returns dict with the following fields:
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'envs': test_envs
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'cases': test_cases
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'tab': filled 2D array, where cell [i][j] is bench_one result for
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test_cases[i] for test_envs[j] (i.e., rows are test cases and
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columns are test environments)
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"""
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tab = {}
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results = {
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'envs': test_envs,
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'cases': test_cases,
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'tab': tab
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}
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n = 1
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n_tests = len(test_envs) * len(test_cases)
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for env in test_envs:
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for case in test_cases:
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print('Testing {}/{}: {} :: {}'.format(n, n_tests,
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env['id'], case['id']))
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if case['id'] not in tab:
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tab[case['id']] = {}
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tab[case['id']][env['id']] = bench_one(test_func, env, case,
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*args, **vargs)
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n += 1
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print('Done')
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return results
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def ascii(results):
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"""Return ASCII representation of bench() returned dict."""
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from tabulate import tabulate
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tab = [[""] + [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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for env in results['envs']:
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row.append(ascii_one(results['tab'][case['id']][env['id']]))
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tab.append(row)
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return tabulate(tab)
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