#!/usr/bin/env python # # 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 . # import statistics def bench_one(test_func, test_env, test_case, count=5, initial_run=True): """Benchmark one test-case test_func -- benchmarking function with prototype test_func(env, case), which takes test_env and test_case arguments and on success returns dict with 'seconds' or 'iops' (or both) fields, specifying the benchmark result. If both 'iops' and 'seconds' provided, the 'iops' is considered the main, and 'seconds' is just an additional info. On failure test_func should return {'error': str}. Returned dict may contain any other additional fields. test_env -- test environment - opaque first argument for test_func test_case -- test case - opaque second argument for test_func count -- how many times to call test_func, to calculate average initial_run -- do initial run of test_func, which don't get into result Returns dict with the following fields: 'runs': list of test_func results 'dimension': dimension of results, may be 'seconds' or 'iops' 'average': average value (iops or seconds) per run (exists only if at least one run succeeded) 'stdev': standard deviation of results (exists only if at least one run succeeded) 'n-failed': number of failed runs (exists only if at least one run failed) """ if initial_run: print(' #initial run:') print(' ', test_func(test_env, test_case)) runs = [] for i in range(count): print(' #run {}'.format(i+1)) res = test_func(test_env, test_case) print(' ', res) runs.append(res) result = {'runs': runs} succeeded = [r for r in runs if ('seconds' in r or 'iops' in r)] if succeeded: if 'iops' in succeeded[0]: assert all('iops' in r for r in succeeded) dim = 'iops' else: assert all('seconds' in r for r in succeeded) assert all('iops' not in r for r in succeeded) dim = 'seconds' result['dimension'] = dim result['average'] = statistics.mean(r[dim] for r in succeeded) result['stdev'] = statistics.stdev(r[dim] for r in succeeded) if len(succeeded) < count: result['n-failed'] = count - len(succeeded) return result def bench(test_func, test_envs, test_cases, *args, **vargs): """Fill benchmark table test_func -- benchmarking function, see bench_one for description test_envs -- list of test environments, see bench_one test_cases -- list of test cases, see bench_one args, vargs -- additional arguments for bench_one Returns dict with the following fields: 'envs': test_envs 'cases': test_cases 'tab': filled 2D array, where cell [i][j] is bench_one result for test_cases[i] for test_envs[j] (i.e., rows are test cases and columns are test environments) """ tab = {} results = { 'envs': test_envs, 'cases': test_cases, 'tab': tab } n = 1 n_tests = len(test_envs) * len(test_cases) for env in test_envs: for case in test_cases: print('Testing {}/{}: {} :: {}'.format(n, n_tests, env['id'], case['id'])) if case['id'] not in tab: tab[case['id']] = {} tab[case['id']][env['id']] = bench_one(test_func, env, case, *args, **vargs) n += 1 print('Done') return results