Parsing log file and returning timestamp ordered output

log_list = {}
...
            if hh_mm in log_list:
                log_list[hh_mm] += 1
            else:
                log_list[hh_mm] = 1
...

This can be replaced with a Counter where unknown keys default to zero.

from collections import Counter

log_list = Counter()
...
            log_list[hh_mm] += 1
...

re_pattern does not need to be redefined each time through the loop. It should be moved outside of the loop, possibly to the top of the file as a constant (ie, named in all caps: RE_PATTERN), and maybe even compiled using re.compile(…)

There is no point capturing patterns you aren’t using. You just need (…) around the timestamp re pattern.

From srtd_list on, you can outdent one level. You’ve finished reading the loglines, so you should allow the file to be closed immediately.

The key=… in sorted(…) is unnecessary, since you are sorting on the guaranteed-unique first element of a tuple.

You don’t need regex at all to do this. You could write the first part of the code as:

import csv
from collections import Counter

with open('access.log','r') as loglines:
    log_list = Counter(line.split()[3][13:18]
                       for line in loglines
                       if line != '\n')
srtd_list = sorted(log_list.items())
…

This is simultaneously simpler and more cryptic. Comment it well if you use it!

Just an idea, but instead of regexes you could use built-in Python libraries for parsing datetimes, for example:

>>> from datetime import datetime
>>> d = "25/Sep/2002:14:04:19 +0200"
>>> datetime.strptime(d, '%d/%b/%Y:%H:%M:%S %z')
datetime.datetime(2002, 9, 25, 14, 4, 19, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200)))

This code will parse your timestamp into a timezone-aware datetime. This approach could be interesting in case you want to be able to parse different formats, or you have varying time zones in your logs. Without a timezone, timestamps are meaningless unless you are operating against a known, stable location, but daylight saving time could come into play.

Maybe you can ignore the timezone in your use case, depending on how the log was produced. Or not.

Also, this could offer better performance than regex but I haven't tested it.

It's obvious that this is a webserver log, and it's rather common to see bash scripts being used for that kind of purpose. A combination of grep, cut and uniq -c could get the job done in 10 lines or less I think.

Now if you are interested in computing live statistics by constantly monitoring the file, you need to implement some sort of bash tail feature. In Python this could be done using process.popen and then you read from the stream line by line, and increment your counters accordingly (I could post some sample code if you're interested).