Situation, that i faced many times, when you know exactly what time interval you looking for potential causes of some incident or random 5xx statuses spike. And all you have is raw logs of your balancer of choice (e.g nginx).
It's common to include timestamp in log rows in format like 2022-11-11T10:12:12. So with this tool you don't need to reinvent regular expression for particular interval each time to filter these logs.
% ./main.py --from 01:13:24 --to 21:18:03
(01:(13:(2[4-9]|[3-5][0-9])|(1[4-9]|2[0-9]|3[0-9]|4[0-9]|5[0-8]):[0-5][0-9]|59:[0-5][0-9])|0[2-9]:[0-5][0-9]:[0-5][0-9]|1[0-9]:[0-5][0-9]:[0-5][0-9]|20:[0-5][0-9]:[0-5][0-9]|21:(00:[0-5][0-9]|(0[1-9]|1[0-7]):[0-5][0-9]|18:(0[0-3])))
In example above you can notice a common pattern of seconds plus [0-9] seconds that can be reduced to simplier expression, so there is an option for the optimization.
File day_seconds.txt is an example of file with timestamps in it (strictly speaking only the time part).
% cat day_seconds.txt | grep -E "$(./main.py --from 01:13:24 --to 21:18:03)" | head -n 5
01:13:24
01:13:25
01:13:26
01:13:27
01:13:28
% cat day_seconds.txt | grep -E "$(./main.py --from 01:13:24 --to 21:18:03)" | tail -n 5
21:17:59
21:18:00
21:18:01
21:18:02
21:18:03