过滤和排序进程

参考: 原文

这个代码样例合集将展示如果通过process_iter()函数去过滤和排序进程。开始:

>>> import psutil
>>> from pprint import pprint as pp

当前用户拥有的进程:

>>> import getpass
>>> pp([(p.pid, p.info['name']) for p in psutil.process_iter(['name', 'username']) if p.info['username'] == getpass.getuser()])
(16832, 'bash'),
(19772, 'ssh'),
(20492, 'python')]

正在运行的进程:

>>> pp([(p.pid, p.info) for p in psutil.process_iter(['name', 'status']) if p.info['status'] == psutil.STATUS_RUNNING])
[(1150, {'name': 'Xorg', 'status': 'running'}),
 (1776, {'name': 'unity-panel-service', 'status': 'running'}),
 (20492, {'name': 'python', 'status': 'running'})]

使用log日志文件的进程:

>>> for p in psutil.process_iter(['name', 'open_files']):
...      for file in p.info['open_files'] or []:
...          if file.path.endswith('.log'):
...               print("%-5s %-10s %s" % (p.pid, p.info['name'][:10], file.path))
...
1510  upstart    /home/giampaolo/.cache/upstart/unity-settings-daemon.log
2174  nautilus   /home/giampaolo/.local/share/gvfs-metadata/home-ce08efac.log
2650  chrome     /home/giampaolo/.config/google-chrome/Default/data_reduction_proxy_leveldb/000003.log

进程消耗超过500M的内存:

>>> pp([(p.pid, p.info['name'], p.info['memory_info'].rss) for p in psutil.process_iter(['name', 'memory_info']) if p.info['memory_info'].rss > 500 * 1024 * 1024])
[(2650, 'chrome', 532324352),
 (3038, 'chrome', 1120088064),
 (21915, 'sublime_text', 615407616)]

CPU耗时最多的前 3 个进程：

>>> pp([(p.pid, p.info['name'], sum(p.info['cpu_times'])) for p in sorted(psutil.process_iter(['name', 'cpu_times']), key=lambda p: sum(p.info['cpu_times'][:2]))][-3:])
[(2721, 'chrome', 10219.73),
 (1150, 'Xorg', 11116.989999999998),
 (2650, 'chrome', 18451.97)]