Analysing a text file in Python

The other answers with regex and splitting the line will get the job done, but if you want a fully maintainable solution that will grow with you, you should build a grammar. I love pyparsing for this:

S ='''
7:06:32 (slbfd) IN: "lq_viz_server" aqeela@nabltas1  
7:08:21 (slbfd) UNSUPPORTED: "Slb_Internal_vlsodc" (PORT_AT_HOST_PLUS   ) Albahraj@nabwmps3  (License server system does not support this feature. (-18,327))
7:08:21 (slbfd) OUT: "OFM32" Albahraj@nabwmps3'''

from pyparsing import *
from collections import defaultdict

# Define the grammar
num = Word(nums)
marker = Literal(":").suppress()
timestamp = Group(num + marker + num + marker + num)
label = Literal("(slbfd)")
flag = Word(alphas)("flag") + marker
name = QuotedString(quoteChar='"')("name")

line    = timestamp + label + flag + name + restOfLine
grammar = OneOrMore(Group(line))

# Now parsing is a piece of cake!  
P = grammar.parseString(S)
counts = defaultdict(int)

for x in P:
    if x.flag=="IN": counts[x.name] += 1
    if x.flag=="OUT": counts[x.name] -= 1

for key in counts:
    print key, counts[key]

This gives as output:

lq_viz_server 1
OFM32 -1

Which would look more impressive if your sample log file was longer. The beauty of a pyparsing solution is the ability to adapt to a more complex query in the future (ex. grab and parse the timestamp, pull email address, parse error codes...). The idea is that you write the grammar independent of the query - you simply convert the raw text to a computer friendly format, abstracting away the parsing implementation away from it's usage.

If I consider that the file is divided into lines (I don't know if it's true) you have to apply split() function to each line. You will have this:

["7:06:32", "(slbfd)", "IN:", "lq_viz_server", "aqeela@nabltas1"]  

And then I think you have to be capable of apply any logic comparing the values that you need.

i made some wild assumptions about your specification and here is a sample code to help you start:

objects = {}
with open("data.txt") as data:
    for line in data:
        if "IN:" in line or "OUT:" in line:
            try:
                name = line.split("\"")[1]
            except IndexError:
                print("No double quoted name on line: {}".format(line))
                name = "PARSING_ERRORS"
            if "OUT:" in line:
                diff = 1
            else:
                diff = -1
            try:
                objects[name] += diff
            except KeyError:
                objects[name] = diff
print(objects) # for debug only, not advisable to print huge number of names

You have two options:

1. Use the .split() function of the string (as pointed out in the comments)
2. Use the re module for regular expressions.

I would suggest using the re module and create a pattern with named groups.

Recipe:

• first create a pattern with re.compile() containing named groups
• do a for loop over the file to get the lines use .match() od the
• created pattern object on each line use .groupdict() of the
• returned match object to access your values of interest

In the mode of just get 'er done with the standard distribution, this works:

import re
from collections import Counter
# open your file as inF...
count=Counter()
for line in inF:
    match=re.match(r'\d+:\d+:\d+ \(slbfd\) (\w+): "(\w+)"', line)
    if match:
        if match.group(1) == 'IN': count[match.group(2)]+=1
        elif match.group(1) == 'OUT': count[match.group(2)]-=1

print(count)

Prints:

Counter({'lq_viz_server': 1, 'OFM32': -1})