llvm-project/lldb/test/pexpect-2.4/examples/uptime.py

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2.4 KiB
Python
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#!/usr/bin/env python
"""This displays uptime information using uptime. This is redundant,
but it demonstrates expecting for a regular expression that uses subgroups.
$Id: uptime.py 489 2007-11-28 23:40:34Z noah $
"""
import pexpect
import re
# There are many different styles of uptime results. I try to parse them all. Yeee!
# Examples from different machines:
# [x86] Linux 2.4 (Redhat 7.3)
# 2:06pm up 63 days, 18 min, 3 users, load average: 0.32, 0.08, 0.02
# [x86] Linux 2.4.18-14 (Redhat 8.0)
# 3:07pm up 29 min, 1 user, load average: 2.44, 2.51, 1.57
# [PPC - G4] MacOS X 10.1 SERVER Edition
# 2:11PM up 3 days, 13:50, 3 users, load averages: 0.01, 0.00, 0.00
# [powerpc] Darwin v1-58.corefa.com 8.2.0 Darwin Kernel Version 8.2.0
# 10:35 up 18:06, 4 users, load averages: 0.52 0.47 0.36
# [Sparc - R220] Sun Solaris (8)
# 2:13pm up 22 min(s), 1 user, load average: 0.02, 0.01, 0.01
# [x86] Linux 2.4.18-14 (Redhat 8)
# 11:36pm up 4 days, 17:58, 1 user, load average: 0.03, 0.01, 0.00
# AIX jwdir 2 5 0001DBFA4C00
# 09:43AM up 23:27, 1 user, load average: 0.49, 0.32, 0.23
# OpenBSD box3 2.9 GENERIC#653 i386
# 6:08PM up 4 days, 22:26, 1 user, load averages: 0.13, 0.09, 0.08
# This parses uptime output into the major groups using regex group matching.
p = pexpect.spawn ('uptime')
p.expect('up\s+(.*?),\s+([0-9]+) users?,\s+load averages?: ([0-9]+\.[0-9][0-9]),?\s+([0-9]+\.[0-9][0-9]),?\s+([0-9]+\.[0-9][0-9])')
duration, users, av1, av5, av15 = p.match.groups()
# The duration is a little harder to parse because of all the different
# styles of uptime. I'm sure there is a way to do this all at once with
# one single regex, but I bet it would be hard to read and maintain.
# If anyone wants to send me a version using a single regex I'd be happy to see it.
days = '0'
hours = '0'
mins = '0'
if 'day' in duration:
p.match = re.search('([0-9]+)\s+day',duration)
days = str(int(p.match.group(1)))
if ':' in duration:
p.match = re.search('([0-9]+):([0-9]+)',duration)
hours = str(int(p.match.group(1)))
mins = str(int(p.match.group(2)))
if 'min' in duration:
p.match = re.search('([0-9]+)\s+min',duration)
mins = str(int(p.match.group(1)))
# Print the parsed fields in CSV format.
print 'days, hours, minutes, users, cpu avg 1 min, cpu avg 5 min, cpu avg 15 min'
print '%s, %s, %s, %s, %s, %s, %s' % (days, hours, mins, users, av1, av5, av15)