Convert an asctime datetime format to a dfdatetime string format

asctime2dfdatetime.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import re

examples = [
	'Wed, 07 Feb 2018 09:26:19 +0000 (UTC)',
	'Sat, 08 Sep 2018 18:56:22',
	'Tue, 06 Mar 2018 11:20:03 +0000',
	'11 Sep 2017 20:51:44 +0100',
	'13 Dec 2016 13:46:28 -0800 (PST)',
	'Wed, 07 Feb 2018 09:26:19 +0000 (added by pippo)',
	'Wed, 7 Feb 2018 09:26:19 +0000 (UTC)',
	'1 Sep 2017 20:51:44 +0100'
]

asctime_pattern = re.compile(
	r'(?P<day>\d{1,2})\s+'
	r'(?P<month>Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)\s+'
	r'(?P<year>\d{4})\s+'
	r'(?P<hour>\d{1,2}):(?P<minute>\d{1,2}):(?P<second>\d{1,2})'
	r'(?:\s+(?P<timezone>[+-]\d{4}))?')

timezone_pattern = re.compile(r'([+-]\d{2})(\d{2})')

month_lookup_table = {
	'Jan': 1, 'Feb': 2, 'Mar': 3,
	'Apr': 4, 'May': 5, 'Jun': 6,
	'Jul': 7, 'Aug': 8, 'Sep': 9,
	'Oct': 10, 'Nov': 11, 'Dec': 12
}

for example in examples:
	match = re.search(asctime_pattern, example)
	print('{0} --> {1:4s}-{2:02d}-{3:0>2s} {4:0>2s}:{5:0>2s}:{6:0>2s}.000{7}'.format(
		example,
		match.group('year'), month_lookup_table[match.group('month')], match.group('day'),
		match.group('hour'), match.group('minute'), match.group('second'),
		re.sub(timezone_pattern, r'\1:\2', match.group('timezone') or '+0000')
	))