On Jan 18, 11:56 pm, Tim Chase <python.l...@tim.thechases.com> wrote:
> kak...@gmail.com wrote:
> > I want to parse a log file with the following format for
> > example:
> > TIMESTAMPE Operation FileName
> > Bytes
> > 12/Jan/2010:16:04:59 +0200 EXISTS sample3.3gp 37151
> > 12/Jan/2010:16:04:59 +0200 EXISTS sample3.3gp 37151
> > 12/Jan/2010:16:04:59 +0200 EXISTS sample3.3gp 37151
> > 12/Jan/2010:16:04:59 +0200 EXISTS sample3.3gp 37151
> > 12/Jan/2010:16:04:59 +0200 EXISTS sample3.3gp 37151
> > 12/Jan/2010:16:05:05 +0200 DELETE sample3.3gp 37151
>
> > How can i count the operations for a month(e.g total of 40 Operations,
> > 30 exists, 10 delete?)
>
> It can be done pretty easily with a regexp to parse the relevant
> bits:
>
> import re
> r = re.compile(r'\d+/([^/]+)/(\d+)\S+\s+\S+\s+(\w+)')
> stats = {}
> for line in file('log.txt'):
> m = r.match(line)
> if m:
> stats[m.groups()] = stats.get(m.groups(), 0) + 1
> print stats
>
> This prints out
>
> {('Jan', '2010', 'EXISTS'): 5, ('Jan', '2010', 'DELETE'): 1}
>
> With the resulting data structure, you can manipulate it to do
> coarser-grained aggregates such as the total operations, or remap
> month-name abbreviations into integers so they could be sorted
> for output.
>
> -tkc
Thank you both so much
Antonis
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