Here is the approach I have taken to finding addresses using regular expressions:
A set of patterns is useful to find many forms that we might expect from an address starting with simply a number followed by set of strings (ex. 1 Basic Road) and then getting more specific such as looking for "P.O. Box", "c/o", "attn:", etc.
Below is a simple test in python. The test will find all the addresses but not the last 4 items which are company names. This example is not comprehensive, but can be altered to suit your needs and catch examples you find in your data.
import re
strings = [
'701 FIFTH AVE',
'2157 Henderson Highway',
'Attn: Patent Docketing',
'HOLLYWOOD, FL 33022-2480',
'1940 DUKE STREET',
'111 MONUMENT CIRCLE, SUITE 3700',
'c/o Armstrong Teasdale LLP',
'1 Almaden Boulevard',
'999 Peachtree Street NE',
'P.O. BOX 2903',
'2040 MAIN STREET',
'300 North Meridian Street',
'465 Columbus Avenue',
'1441 SEAMIST DR.',
'2000 PENNSYLVANIA AVENUE, N.W.',
'465 Columbus Avenue',
'28 STATE STREET',
'P.O, Drawer 800889.',
'2200 CLARENDON BLVD.',
'840 NORTH PLANKINTON AVENUE',
'1025 Connecticut Avenue, NW',
'340 Commercial Street',
'799 Ninth Street, NW',
'11318 Lazarro Ln',
'P.O, Box 65745',
'c/o Ballard Spahr LLP',
'8210 SOUTHPARK TERRACE',
'1130 Connecticut Ave., NW, Suite 420',
'465 Columbus Avenue',
"BANNER & WITCOFF , LTD",
"CHIP LAW GROUP",
"HAMMER & ASSOCIATES, P.C.",
"MH2 TECHNOLOGY LAW GROUP, LLP",
]
patterns = [
"c\/o [\w ]{2,}",
"C\/O [\w ]{2,}",
"P.O\. [\w ]{2,}",
"P.O\, [\w ]{2,}",
"[\w\.]{2,5} BOX [\d]{2,8}",
"^[#\d]{1,7} [\w ]{2,}",
"[A-Z]{2,2} [\d]{5,5}",
"Attn: [\w]{2,}",
"ATTN: [\w]{2,}",
"Attention: [\w]{2,}",
"ATTENTION: [\w]{2,}"
]
contact_list = []
total_count = len(strings)
found_count = 0
for string in strings:
pat_no = 1
for pattern in patterns:
match = re.search(pattern, string.strip())
if match:
print("Item found: " + match.group(0) + " | Pattern no: " + str(pat_no))
found_count += 1
pat_no += 1
print("-- Total: " + str(total_count) + " Found: " + str(found_count))