simplebench.py (5159B)
1 #!/usr/bin/env python 2 # 3 # Simple benchmarking framework 4 # 5 # Copyright (c) 2019 Virtuozzo International GmbH. 6 # 7 # This program is free software; you can redistribute it and/or modify 8 # it under the terms of the GNU General Public License as published by 9 # the Free Software Foundation; either version 2 of the License, or 10 # (at your option) any later version. 11 # 12 # This program is distributed in the hope that it will be useful, 13 # but WITHOUT ANY WARRANTY; without even the implied warranty of 14 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 15 # GNU General Public License for more details. 16 # 17 # You should have received a copy of the GNU General Public License 18 # along with this program. If not, see <http://www.gnu.org/licenses/>. 19 # 20 21 import statistics 22 import subprocess 23 import time 24 25 26 def do_drop_caches(): 27 subprocess.run('sync; echo 3 > /proc/sys/vm/drop_caches', shell=True, 28 check=True) 29 30 31 def bench_one(test_func, test_env, test_case, count=5, initial_run=True, 32 slow_limit=100, drop_caches=False): 33 """Benchmark one test-case 34 35 test_func -- benchmarking function with prototype 36 test_func(env, case), which takes test_env and test_case 37 arguments and on success returns dict with 'seconds' or 38 'iops' (or both) fields, specifying the benchmark result. 39 If both 'iops' and 'seconds' provided, the 'iops' is 40 considered the main, and 'seconds' is just an additional 41 info. On failure test_func should return {'error': str}. 42 Returned dict may contain any other additional fields. 43 test_env -- test environment - opaque first argument for test_func 44 test_case -- test case - opaque second argument for test_func 45 count -- how many times to call test_func, to calculate average 46 initial_run -- do initial run of test_func, which don't get into result 47 slow_limit -- stop at slow run (that exceedes the slow_limit by seconds). 48 (initial run is not measured) 49 drop_caches -- drop caches before each run 50 51 Returns dict with the following fields: 52 'runs': list of test_func results 53 'dimension': dimension of results, may be 'seconds' or 'iops' 54 'average': average value (iops or seconds) per run (exists only if at 55 least one run succeeded) 56 'stdev': standard deviation of results 57 (exists only if at least one run succeeded) 58 'n-failed': number of failed runs (exists only if at least one run 59 failed) 60 """ 61 if initial_run: 62 print(' #initial run:') 63 do_drop_caches() 64 print(' ', test_func(test_env, test_case)) 65 66 runs = [] 67 for i in range(count): 68 t = time.time() 69 70 print(' #run {}'.format(i+1)) 71 do_drop_caches() 72 res = test_func(test_env, test_case) 73 print(' ', res) 74 runs.append(res) 75 76 if time.time() - t > slow_limit: 77 print(' - run is too slow, stop here') 78 break 79 80 count = len(runs) 81 82 result = {'runs': runs} 83 84 succeeded = [r for r in runs if ('seconds' in r or 'iops' in r)] 85 if succeeded: 86 if 'iops' in succeeded[0]: 87 assert all('iops' in r for r in succeeded) 88 dim = 'iops' 89 else: 90 assert all('seconds' in r for r in succeeded) 91 assert all('iops' not in r for r in succeeded) 92 dim = 'seconds' 93 result['dimension'] = dim 94 result['average'] = statistics.mean(r[dim] for r in succeeded) 95 if len(succeeded) == 1: 96 result['stdev'] = 0 97 else: 98 result['stdev'] = statistics.stdev(r[dim] for r in succeeded) 99 100 if len(succeeded) < count: 101 result['n-failed'] = count - len(succeeded) 102 103 return result 104 105 106 def bench(test_func, test_envs, test_cases, *args, **vargs): 107 """Fill benchmark table 108 109 test_func -- benchmarking function, see bench_one for description 110 test_envs -- list of test environments, see bench_one 111 test_cases -- list of test cases, see bench_one 112 args, vargs -- additional arguments for bench_one 113 114 Returns dict with the following fields: 115 'envs': test_envs 116 'cases': test_cases 117 'tab': filled 2D array, where cell [i][j] is bench_one result for 118 test_cases[i] for test_envs[j] (i.e., rows are test cases and 119 columns are test environments) 120 """ 121 tab = {} 122 results = { 123 'envs': test_envs, 124 'cases': test_cases, 125 'tab': tab 126 } 127 n = 1 128 n_tests = len(test_envs) * len(test_cases) 129 for env in test_envs: 130 for case in test_cases: 131 print('Testing {}/{}: {} :: {}'.format(n, n_tests, 132 env['id'], case['id'])) 133 if case['id'] not in tab: 134 tab[case['id']] = {} 135 tab[case['id']][env['id']] = bench_one(test_func, env, case, 136 *args, **vargs) 137 n += 1 138 139 print('Done') 140 return results