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