I wrote a Perl script today to analyze Folding@home logs. Then I wrote the exact same script in Python. The scripts are attached. Here are my observations.
Perl Pluses
Parsing the input was easier in Perl. I used the
exact same regular expressions in both, but the Perl
seemed a lot easier.
Autovivification made things easier.
Automatic string<->int conversions saved time and thought.
Worked everywhere. Some machines still have Perl 5.003,
but I didn't use any new language features. The Python
version required Python 2.2, which was only installed on
a couple of machines.
Python Positives
The StatSample class just happened. It seemed easier, so I
wrote a class. I didn't want to go back and do the same in
Perl because class declarations are so messy there.
The Python is a lot easier to read. Perl's punctuation
clutters the text and makes it hard to read.
First time I've ever used the print statement in a nontrivial
way. Worked pretty well in this case. Wouldn't be as clean
if I didn't have whitespace around each calculated value.
I'm still new to Python. If you can see ways to write it better,
I'd appreciate the criticism. If you can see ways to write the
Perl better, that's cool too.
--
Bob Miller K<bob>
kbobsoft software consulting
http://kbobsoft.com [EMAIL PROTECTED]
folding-stats.pl
Description: Perl program
#!/usr/local/bin/python
import fileinput
import math
import re
def time_format(interval):
hr, min, sec = int(interval / 3600), interval / 60 % 60, interval % 60
if hr:
return "%d:%02d:%02d" % (hr, min, sec)
else:
return "%d:%02d" % (min, sec)
class StatSample:
"List of numbers that can calculate simple statistics."
def __init__(self):
self.__data = []
def __len__(self):
return len(self.__data)
def __getitem__(self, index):
return self.__data[index]
def __setitem__(self, index):
return self.__data[index]
def append(self, datum):
return self.__data.append(datum)
def minimum(self):
min = None
for d in self:
if min is None or min > d:
min = d
return min
def maximum(self):
max = None
for d in self:
if max is None or max < d:
max = d
return max
def mean(self):
if len(self) == 0: raise
sum = 0
for d in self:
sum += d
return sum / len(self)
def variance(self):
if len(self) == 0:
return 0
sum, sum2 = 0, 0
for d in self:
sum += d
sum2 += d * d
return (sum2 - (sum * sum) / len(self)) / (len(self) - 1)
def std_deviation(self):
return math.sqrt(self.variance())
# Read the file.
ftimes = StatSample()
o, t = None, None
for line in fileinput.input():
timestamp = re.match(r'\[(\d+)\:(\d+)\:(\d+)\]', line)
if timestamp:
hr, min, sec = [int(n) for n in timestamp.groups()]
o, t = t, (hr * 60 + min) * 60 + sec
if re.search('Finished a frame', line) and o is not None:
ftimes.append((t - o + 86400) % 86400)
# Calculate and print statistics.
print len(ftimes), "frames"
print "fastest:", time_format(ftimes.minimum()),
print " slowest:", time_format(ftimes.maximum())
print "mean:", time_format(ftimes.mean())
print "standard deviation:", time_format(ftimes.std_deviation())
