Help with script with performance problems

[Dennis Roberts]

I have a script to parse a dns querylog and generate some statistics.
For a 750MB file a perl script using the same methods (splits) can
parse the file in 3 minutes. My python script takes 25 minutes. It
is enough of a difference that unless I can figure out what I did
wrong or a better way of doing it I might not be able to use python
(since most of what I do is parsing various logs). The main reason to
try python is I had to look at some early scripts I wrote in perl and
had no idea what the hell I was thinking or what the script even did!
After some googling and reading Eric Raymonds essay on python I jumped
in:) Here is my script. I am looking for constructive comments -
please don't bash my newbie code.

#!/usr/bin/python -u

import string
import sys

clients = {}
queries = {}
count = 0

print "Each dot is 100000 lines..."

f = sys.stdin

while 1:

line = f.readline()

if count % 100000 == 0:
sys.stdout.writ e(".")

if line:
splitline = string.split(li ne)

try:
(month, day, time, stype, source, qtype, query, ctype,
record) = splitline
except:
print "problem spliting line", count
print line
break

try:
words = string.split(so urce,'#')
source = words[0]
except:
print "problem splitting source", count
print line
break

if clients.has_key (source):
clients[source] = clients[source] + 1
else:
clients[source] = 1

if queries.has_key (query):
queries[query] = queries[query] + 1
else:
queries[query] = 1

else:
print
break

count = count + 1

f.close()

print count, "lines processed"

for numclient, count in clients.items() :
if count > 100000:
print "%s,%s" % (numclient, count)

for numquery, count in queries.items() :
if count > 100000:
print "%s,%s" % (numquery, count)

[Ville Vainio]

go**********@sp acerodent.org (Dennis Roberts) writes:

is enough of a difference that unless I can figure out what I did
wrong or a better way of doing it I might not be able to use python
(since most of what I do is parsing various logs). The main reason to
Isn't parsing logs a batch-oriented thing, where 20 minutes more
wouldn't matter all that much? Log parsing is the home field of Perl,
so python probably can't match its performance there, but other
advantages of Python might make you still want to avoid going back to
Perl. As long as it's 'efficient enough', who cares?
f = sys.stdin
Have you tried using a normal file instead of stdin? BTW, you can
iterate over a file easily by "for line in open("mylog.log "):". ISTR
it's also more efficient than readline()'s, because it caches the
lines instead of reading them one by one. You can also get the line
numbers by doing "for linenum, line in enumerate(open( "mylog.log" )):"

splitline = string.split(li ne)
Do not use 'string' module (it's deprecated), use string methods
instead: line.split()
clients[source] = clients[source] + 1

clients[source] += 1

or another way to handle the common 'add 1, might not exist' idiom:
clients[source] = 1 + clients.get(sou rce,0)

See http://aspn.activestate.com/ASPN/Coo...n/Recipe/66516
--
Ville Vainio http://www.students.tut.fi/~vainio24

[Miki Tebeka]

Hello Dennis,

A general note: Use the "hotshot" module to find where you spend most of your time.

splitline = string.split(li ne)

My guess is that if you'll use the "re" module things will be much faster.

import re
ws_split = re.compile("\s+ ").split
....
splitline = split(line)
....

HTH.

Miki

[Paul Clinch]

mi***@zoran.co. il (Miki Tebeka) wrote in message news:<62******* *************** ***@posting.goo gle.com>...

Hello Dennis,

A general note: Use the "hotshot" module to find where you spend most of your time.

splitline = string.split(li ne)

My guess is that if you'll use the "re" module things will be much faster.

import re
ws_split = re.compile("\s+ ").split
...
splitline = split(line)
...

HTH.

Miki

An alternative in python 2.3 is the timeit module, the following
extracted from doc.s:-
import timeit

timer1 = timeit.Timer('u nicode("abc")')
timer2 = timeit.Timer('" abc" + u""')

# Run three trials
print timer1.repeat(r epeat=3, number=100000)
print timer2.repeat(r epeat=3, number=100000)

# On my laptop this outputs:
# [0.3683179616928 1006, 0.3744169473648 0713, 0.3530489206314 0869]
# [0.1757440567016 6016, 0.1819350719451 9043, 0.1756579875946 0449]

Regards Paul Clinch

[Dennis Roberts]

Ville Vainio <vi************ ********@spamtu t.fi> wrote in message news:<du******* ******@amadeus. cc.tut.fi>...

f = sys.stdin

Have you tried using a normal file instead of stdin? BTW, you can
iterate over a file easily by "for line in open("mylog.log "):". ISTR
it's also more efficient than readline()'s, because it caches the
lines instead of reading them one by one. You can also get the line
numbers by doing "for linenum, line in enumerate(open( "mylog.log" )):"

i have a 240207 line sample log file that I test with. The script I
submitted parsed it in 18 seconds. My perl script parsed it in 4
seconds.

The new python script, using a normal file as suggested above, does it
in 3 seconds!

Changed "f = sys.stdin" to "f = open('sample', 'r')".

Thanks Ville!

Note (I made the other changes one at a time as well - the file open
change was the only one that made it faster)

[Aahz]

In article <a9************ **************@ posting.google. com>,
Dennis Roberts <go**********@s pacerodent.org> wrote:

I have a script to parse a dns querylog and generate some statistics.
For a 750MB file a perl script using the same methods (splits) can
parse the file in 3 minutes. My python script takes 25 minutes. It
is enough of a difference that unless I can figure out what I did
wrong or a better way of doing it I might not be able to use python
(since most of what I do is parsing various logs). The main reason to
try python is I had to look at some early scripts I wrote in perl and
had no idea what the hell I was thinking or what the script even did!
After some googling and reading Eric Raymonds essay on python I jumped
in:) Here is my script. I am looking for constructive comments -
please don't bash my newbie code.

If you haven't yet, make sure you upgrade to Python 2.3; there are a lot
of speed enhancements. Also, it allows you to switch to idioms that work
more like Perl's:

for line in f:
fields = line.split()
...

Generally speaking, contrary to what another poster suggested, string
methods will almost always be faster than regexes (assuming that a
string method does what you want directly, of course; using multiple
string methods may or may not be faster than regexes).
--
Aahz (aa**@pythoncra ft.com) <*> http://www.pythoncraft.com/

Weinberg's Second Law: If builders built buildings the way programmers wrote
programs, then the first woodpecker that came along would destroy civilization.

[Peter Otten]

Dennis Roberts wrote:

I have a script to parse a dns querylog and generate some statistics.
For a 750MB file a perl script using the same methods (splits) can
parse the file in 3 minutes. My python script takes 25 minutes. It
is enough of a difference that unless I can figure out what I did
wrong or a better way of doing it I might not be able to use python
(since most of what I do is parsing various logs). The main reason to
try python is I had to look at some early scripts I wrote in perl and
had no idea what the hell I was thinking or what the script even did!
After some googling and reading Eric Raymonds essay on python I jumped
in:) Here is my script. I am looking for constructive comments -
please don't bash my newbie code.

Below is my version of your script. It tries to use more idiomatic Python
and is about 20%t faster on some bogus data - but nowhere near to close the
performance gap you claim to the perl script.
However, it took 143 seconds to process 10**7 lines generated by

<makesample.p y>
import itertools, sys
sample = "%dmonth day time stype source%d#sowhat qtype %dquery ctype record"
thousand = itertools.cycle (range(1000))
hundred = itertools.cycle (range(100))

out = file(sys.argv[1], "w")
try:
try:
count = int(sys.argv[2])
except IndexError:
count = 10**7
for i in range(count):
print >> out, sample % (i, thousand.next() , hundred.next())
finally:
out.close()
</makesample.py>

with Python 2.3.2 on my 2.6GHz P4. Would that mean Perl would do it in 17
seconds? Anyway, the performance problem would rather be your computer :-),
Python should be fast enough for the purpose.

Peter

<parselog.py>
#!/usr/bin/python -u
#Warning, not seriously tested
import sys

#import time
#starttime = time.time()

clients = {}
queries = {}
lineNo = -1

threshold = 100
pointmod = 100000

f = file(sys.argv[1])
try:
print "Each dot is %d lines..." % pointmod
for lineNo, line in enumerate(f):
if lineNo % pointmod == 0:
sys.stdout.writ e(".")

try:
month, day, timestr, stype, source, qtype, query, ctype, record
= line.split()
except ValueError:
raise Exception("prob lem splitting line %d\n%s" % (lineNo,
line))

source = source.split('# ', 1)[0]

clients[source] = clients.get(sou rce, 0) + 1
queries[query] = queries.get(que ry, 0) + 1
finally:
f.close()

print
print lineNo+1, "lines processed"

for numclient, count in clients.iterite ms():
if count > threshold:
print "%s,%s" % (numclient, count)

for numquery, count in queries.iterite ms():
if count > threshold:
print "%s,%s" % (numquery, count)

#print "time:", time.time() - starttime
</parselog.py>

[Peter Otten]

Peter Otten wrote:

However, it took 143 seconds to process 10**7 lines generated by

I just downloaded psycho, oops, keep misspelling the name :-) and it brings
down the time to 92 seconds - almost for free. I must say I'm impressed,
the psycologist(s) did an excellent job.

Peter

#!/usr/bin/python -u
import psyco, sys
psyco.full()

def main():
clients = {}
queries = {}
lineNo = -1

threshold = 100
pointmod = 100000

f = file(sys.argv[1])
try:
print "Each dot is %d lines..." % pointmod
for lineNo, line in enumerate(f):
if lineNo % pointmod == 0:
sys.stdout.writ e(".")

try:
month, day, timestr, stype, source, qtype, query, ctype,
record = line.split()
except ValueError:
raise Exception("prob lem splitting line %d\n%s" % (lineNo,
line))

source = source.split('# ', 1)[0]

clients[source] = clients.get(sou rce, 0) + 1
queries[query] = queries.get(que ry, 0) + 1
finally:
f.close()

print
print lineNo+1, "lines processed"

for numclient, count in clients.iterite ms():
if count > threshold:
print "%s,%s" % (numclient, count)

for numquery, count in queries.iterite ms():
if count > threshold:
print "%s,%s" % (numquery, count)

import time
starttime = time.time()
main()
print "time:", time.time() - starttime