nopenpilot/selfdrive/debug/cpu_usage_stat.py

122 lines
5.0 KiB
Python
Executable File

#!/usr/bin/env python3
# type: ignore
import psutil
import time
import os
import sys
import numpy as np
import argparse
import re
from collections import defaultdict
'''
System tools like top/htop can only show current cpu usage values, so I write this script to do statistics jobs.
Features:
Use psutil library to sample cpu usage(avergage for all cores) of OpenPilot processes, at a rate of 5 samples/sec.
Do cpu usage statistics periodically, 5 seconds as a cycle.
Caculate the average cpu usage within this cycle.
Caculate minumium/maximium/accumulated_average cpu usage as long term inspections.
Monitor multiple processes simuteneously.
Sample usage:
root@localhost:/data/openpilot$ python selfdrive/debug/cpu_usage_stat.py boardd,ubloxd
('Add monitored proc:', './boardd')
('Add monitored proc:', 'python locationd/ubloxd.py')
boardd: 1.96%, min: 1.96%, max: 1.96%, acc: 1.96%
ubloxd.py: 0.39%, min: 0.39%, max: 0.39%, acc: 0.39%
'''
# Do statistics every 5 seconds
PRINT_INTERVAL = 5
SLEEP_INTERVAL = 0.2
monitored_proc_names = [
'ubloxd', 'thermald', 'uploader', 'deleter', 'controlsd', 'plannerd', 'radard', 'mapd', 'loggerd' , 'logmessaged', 'tombstoned',
'logcatd', 'proclogd', 'boardd', 'pandad', './ui', 'ui', 'calibrationd', 'params_learner', 'modeld', 'dmonitoringmodeld', 'camerad', 'sensord', 'updated', 'gpsd', 'athena']
cpu_time_names = ['user', 'system', 'children_user', 'children_system']
timer = getattr(time, 'monotonic', time.time)
def get_arg_parser():
parser = argparse.ArgumentParser(
description="Unlogger and UI",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("proc_names", nargs="?", default='',
help="Process names to be monitored, comma seperated")
parser.add_argument("--list_all", action='store_true',
help="Show all running processes' cmdline")
parser.add_argument("--detailed_times", action='store_true',
help="show cpu time details (split by user, system, child user, child system)")
return parser
if __name__ == "__main__":
args = get_arg_parser().parse_args(sys.argv[1:])
if args.list_all:
for p in psutil.process_iter():
print('cmdline', p.cmdline(), 'name', p.name())
sys.exit(0)
if len(args.proc_names) > 0:
monitored_proc_names = args.proc_names.split(',')
monitored_procs = []
stats = {}
for p in psutil.process_iter():
if p == psutil.Process():
continue
matched = any([l for l in p.cmdline() if any([pn for pn in monitored_proc_names if re.match(r'.*{}.*'.format(pn), l, re.M | re.I)])])
if matched:
k = ' '.join(p.cmdline())
print('Add monitored proc:', k)
stats[k] = {'cpu_samples': defaultdict(list), 'min': defaultdict(lambda: None), 'max': defaultdict(lambda: None),
'avg': defaultdict(lambda: 0.0), 'last_cpu_times': None, 'last_sys_time':None}
stats[k]['last_sys_time'] = timer()
stats[k]['last_cpu_times'] = p.cpu_times()
monitored_procs.append(p)
i = 0
interval_int = int(PRINT_INTERVAL / SLEEP_INTERVAL)
while True:
for p in monitored_procs:
k = ' '.join(p.cmdline())
cur_sys_time = timer()
cur_cpu_times = p.cpu_times()
cpu_times = np.subtract(cur_cpu_times, stats[k]['last_cpu_times']) / (cur_sys_time - stats[k]['last_sys_time'])
stats[k]['last_sys_time'] = cur_sys_time
stats[k]['last_cpu_times'] = cur_cpu_times
cpu_percent = 0
for num, name in enumerate(cpu_time_names):
stats[k]['cpu_samples'][name].append(cpu_times[num])
cpu_percent += cpu_times[num]
stats[k]['cpu_samples']['total'].append(cpu_percent)
time.sleep(SLEEP_INTERVAL)
i += 1
if i % interval_int == 0:
l = []
for k, stat in stats.items():
if len(stat['cpu_samples']) <= 0:
continue
for name, samples in stat['cpu_samples'].items():
samples = np.array(samples)
avg = samples.mean()
c = samples.size
min_cpu = np.amin(samples)
max_cpu = np.amax(samples)
if stat['min'][name] is None or min_cpu < stat['min'][name]:
stat['min'][name] = min_cpu
if stat['max'][name] is None or max_cpu > stat['max'][name]:
stat['max'][name] = max_cpu
stat['avg'][name] = (stat['avg'][name] * (i - c) + avg * c) / (i)
stat['cpu_samples'][name] = []
msg = 'avg: {1:.2%}, min: {2:.2%}, max: {3:.2%} {0}'.format(os.path.basename(k), stat['avg']['total'], stat['min']['total'], stat['max']['total'])
if args.detailed_times:
for stat_type in ['avg', 'min', 'max']:
msg += '\n {}: {}'.format(stat_type, [name + ':' + str(round(stat[stat_type][name]*100, 2)) for name in cpu_time_names])
l.append((os.path.basename(k), stat['avg']['total'], msg))
l.sort(key= lambda x: -x[1])
for x in l:
print(x[2])
print('avg sum: {0:.2%} over {1} samples {2} seconds\n'.format(
sum([stat['avg']['total'] for k, stat in stats.items()]), i, i * SLEEP_INTERVAL
))