I am trying to match spaces just after punctuation marks so that I can split up a large corpus of text, but I am seeing some common edge cases with places, titles and common abbreviations:
I am from New York, N.Y. and I would like to say hello! How are you today? I am well. I owe you $6. 00 because you bought me a No. 3 burger. -Sgt. Smith
I am using this with the re.split function in Python 3 I want to get this:
["I am from New York, N.Y. and I would like to say hello!",
"How are you today?",
"I am well.",
"I owe you $6. 00 because you bought me a No. 3 burger."
"-Sgt. Smith"]
This is currently my regex:
(?<=[\.\?\!])(?<=[^A-Z].)(?<=[^0-9].)(?<=[^N]..)(?<=[^o].)
I decided to try to fix the No. first, with the last two conditions. But it relies on matching the N and the o independently which I think is going to case false positives elsewhere. I cannot figure out how to get it to make just the string No behind the period. I will then use a similar approach for Sgt. and any other "problem" strings I come across.
I am trying to use something like:
(?<=[\.\?\!])(?<=[^A-Z].)(?<=[^0-9].)^(?<=^No$)
But it doesn't capture anything after that. How can I get it to exclude certain strings which I expect to have a period in it, and not capture them?
Here is a regexr of my situation: https://regexr.com/4sgcb
This is the closest regex I could get (the trailing space is the one we match):
(?<=(?<!(No|\.\w))[\.\?\!])(?! *\d+ *)
which will split also after Sgt. for the simple reason that a lookbehind assertion has to be fixed width in Python (what a limitation!).
This is how I would do it in vim, which has no such limitation (the trailing space is the one we match):
\(\(No\|Sgt\|\.\w\)\#<![?.!]\)\( *\d\+ *\)\#!\zs
For the OP as well as the casual reader, this question and the answers to it are about lookarounds and are very interesting.
You may consider a matching approach, it will offer you better control over the entities you want to count as single words, not as sentence break signals.
Use a pattern like
\s*((?:\d+\.\s*\d+|(?:No|M[rs]|[JD]r|S(?:r|gt))\.|\.(?!\s+-?[A-Z0-9])|[^.!?])+(?:[.?!]|$))
See the regex demo
It is very similar to what I posted here, but it contains a pattern to match poorly formatted float numbers, added No. and Sgt. abbreviation support and a better handling of strings not ending with final sentence punctuation.
Python demo:
import re
p = re.compile(r'\s*((?:\d+\.\s*\d+|(?:No|M[rs]|[JD]r|S(?:r|gt))\.|\.(?!\s+-?[A-Z0-9])|[^.!?])+(?:[.?!]|$))')
s = "I am from New York, N.Y. and I would like to say hello! How are you today? I am well. I owe you $6. 00 because you bought me a No. 3 burger. -Sgt. Smith"
for m in p.findall(s):
print(m)
Output:
I am from New York, N.Y. and I would like to say hello!
How are you today?
I am well.
I owe you $6. 00 because you bought me a No. 3 burger.
-Sgt. Smith
Pattern details
\s* - matches 0 or more whitespace (used to trim the results)
(?:\d+\.\s*\d+|(?:No|M[rs]|[JD]r|S(?:r|gt))\.|\.(?!\s+-?[A-Z0-9])|[^.!?])+ - one or more occurrences of several aternatives:
\d+\.\s*\d+ - 1+ digits, ., 0+ whitespaces, 1+ digits
(?:No|M[rs]|[JD]r|S(?:r|gt))\. - abbreviated strings like No., Mr., Ms., Jr., Dr., Sr., Sgt.
\.(?!\s+-?[A-Z0-9]) - matches a dot not followed by 1 or more whitespace and then an optional - and uppercase letters or digits
| - or
[^.!?] - any character but a ., !, and ?
(?:[.?!]|$) - a ., !, and ? or end of string.
As mentioned in my comment above, if you are not able to define a fixed set of edge cases, this might not be possible without false positives or false negatives. Again, without context you are not able to destinguish between abbreviations like "-Sgt. Smith" and ends of sentences like "Sergeant is often times abbreviated as Sgt. This makes it shorter.".
However, if you can define a fixed set of edge cases, its probably easier and much more readable to do this in multiple steps.
1. Identify your edge cases
For example, you can destinguish "Ill have a No. 3" and "No. I am your father" by checking for a subsequent number. So you would identify that edge case with a regex like this: No. \d. (Again, context matters. Sentences like "Is 200 enough? No. 200 is not enough." will still give you a false positive)
2. Mask your edge cases
For each edge case, mask the string with a respective string that will 100% not be part of the original text. E.g. "No." => "======NUMBER======"
3. Run your algorithm
Now that you got rid of your unwanted punctuations, you can run a simpler regex like this to identify the true positives: [\.\!\?]\s
4. Unmask your edge cases
Turn "======NUMBER======" back into "No."
Doing it with only one regex will be tricky - as stated in comments, there are lots of edge cases.
Myself I would do it with three steps:
Replace spaces that should stay with some special character (re.sub)
Split the text (re.split)
Replace the special character with space
For example:
import re
zero_width_space = '\u200B'
s = 'I am from New York, N.Y. and I would like to say hello! How are you today? I am well. I owe you $6. 00 because you bought me a No. 3 burger. -Sgt. Smith'
s = re.sub(r'(?<=\.)\s+(?=[\da-z])|(?<=,)\s+|(?<=Sgt\.)\s+', zero_width_space, s)
s = re.split(r'(?<=[.?!])\s+', s)
from pprint import pprint
pprint([line.replace(zero_width_space, ' ') for line in s])
Prints:
['I am from New York, N.Y. and I would like to say hello!',
'How are you today?',
'I am well.',
'I owe you $6. 00 because you bought me a No. 3 burger.',
'-Sgt. Smith']
For the past few hours I've been trying to match address(es) from the following sample data and I can't get it to work:
medicalHistory None
address 24 Lewin Street, KUBURA,
NSW, Australia
email MaryBeor#spambob.com
address 16 Yarra Street,
LAWRENCE, VIC, Australia
name Mary Beor
medicalHistory None
phone 00000000000000000000353336907
birthday 26-11-1972
My plan was to find anything that starts with "address", is followed by any space followed by characters, numbers commas and newlines and ends with newline followed by a character. I came up with the following (and many variations of it):
address\s+([0-9a-zA-Z, \n\t]+)(?!\n\w)
Unfortunately that matches the following:
address 24 Lewin Street, KUBURA,
NSW, Australia
email MaryBeor
and
address 16 Yarra Street,
LAWRENCE, VIC, Australia
name Mary Beor
medicalHistory None
phone 00000000000000000000353336907
birthday 26
instead of
address 24 Lewin Street, KUBURA,
NSW, Australia
and
address 16 Yarra Street,
LAWRENCE, VIC, Australia
Can you please tell me what I'm doing wrong?
I would do it this way:
address\s+((?![\r\n]+\w)[0-9a-zA-Z, \r\n\t])+
See it here on Regexr.
This ((?![\r\n]+\w)[0-9a-zA-Z, \r\n\t])+ is the important part, where I say, match the next character from [0-9a-zA-Z, \r\n\t], if (?![\r\n]+\w) is not following. This is matching what you expect.
In both your cases the regex stopped matching because of a character that is not included in your character class. If you want to go that way than you would need to combine a lazy quantifier and a positive lookahead:
address\s+([0-9a-zA-Z, \n\r\t]+?)(?=\r\w)
[0-9a-zA-Z, \n\r\t]+? is matching as less as possible till the condition (?=\r\w) is true.
See it here at Regexr
The problem with your regex is that + is greedy and goes until it finds a character out of that group, the # in the first case and - in the second.
Another approach is to use a non-greedy quantifier and a positive look-ahead for a newline followed by a word-character, like (python version):
re.findall(r'address\s+.*?(?=\n\w)', s, re.DOTALL)
It yields:
['address 24 Lewin Street, KUBURA, \n NSW, Australia',
'address 16 Yarra Street, \n LAWRENCE, VIC, Australia']
I am trying to write a regular expression that facilitates an address, example 21-big walk way or 21 St.Elizabeth's drive I came up with the following regular expression but I am not too keen to how to incorporate all the characters (alphanumeric, space dash, full stop, apostrophe)
"regexp=^[A-Za-z-0-99999999'
See the answer to this question on address validating with regex:
regex street address match
The problem is, street addresses vary so much in formatting that it's hard to code against them. If you are trying to validate addresses, finding if one isn't valid based on its format is mighty hard to do.
This would return the following address (253 N. Cherry St. ), anything with its same format:
\d{1,5}\s\w.\s(\b\w*\b\s){1,2}\w*\.
This allows 1-5 digits for the house number, a space, a character followed by a period (for N. or S.), 1-2 words for the street name, finished with an abbreviation (like st. or rd.).
Because regex is used to see if things meet a standard or protocol (which you define), you probably wouldn't want to allow for the addresses provided above, especially the first one with the dash, since they aren't very standard. you can modify my above code to allow for them if you wish--you could add
(-?)
to allow for a dash but not require one.
In addition, http://rubular.com/ is a quick and interactive way to learn regex. Try it out with the addresses above.
In case if you don't have a fixed format for the address as mentioned above, I would use regex expression just to eliminate the symbols which are not used in the address (like specialized sybmols - &(%#$^). Result would be:
[A-Za-z0-9'\.\-\s\,]
Just to add to Serzas' answer(since don't have enough reps. to comment).
alphabets and numbers can effectively be replaced by \w for words.
Additionally apostrophe,comma,period and hyphen doesn't necessarily need a backslash.
My requirement also involved front and back slashes so \/ and finally whitespaces with \s. The working regex for me ,as such was :
pattern: "[\w',-\\/.\s]"
Regular expression for simple address validation
^[#.0-9a-zA-Z\s,-]+$
E.g. for Address match case
#1, North Street, Chennai - 11
E.g. for Address not match case
$1, North Street, Chennai # 11
I have succesfully used ;
Dim regexString = New stringbuilder
With regexString
.Append("(?<h>^[\d]+[ ])(?<s>.+$)|") 'find the 2013 1st ambonstreet
.Append("(?<s>^.*?)(?<h>[ ][\d]+[ ])(?<e>[\D]+$)|") 'find the 1-7-4 Dual Ampstreet 130 A
.Append("(?<s>^[\D]+[ ])(?<h>[\d]+)(?<e>.*?$)|") 'find the Terheydenlaan 320 B3
.Append("(?<s>^.*?)(?<h>\d*?$)") 'find the 245e oosterkade 9
End With
Dim Address As Match = Regex.Match(DataRow("customerAddressLine1"), regexString.ToString(), RegexOptions.Multiline)
If Not String.IsNullOrEmpty(Address.Groups("s").Value) Then StreetName = Address.Groups("s").Value
If Not String.IsNullOrEmpty(Address.Groups("h").Value) Then HouseNumber = Address.Groups("h").Value
If Not String.IsNullOrEmpty(Address.Groups("e").Value) Then Extension = Address.Groups("e").Value
The regex will attempt to find a result, if there is none, it move to the next alternative. If no result is found, none of the 4 formats where present.
This one worked for me:
\d+[ ](?:[A-Za-z0-9.-]+[ ]?)+(?:Avenue|Lane|Road|Boulevard|Drive|Street|Ave|Dr|Rd|Blvd|Ln|St)\.?
The source: https://www.codeproject.com/Tips/989012/Validate-and-Find-Addresses-with-RegEx
Regex is a very bad choice for this kind of task. Try to find a web service or an address database or a product which can clean address data instead.
Related:
Address validation using Google Maps API
As a simple one line expression recommend this,
^([a-zA-z0-9/\\''(),-\s]{2,255})$
I needed
STREET # | STREET | CITY | STATE | ZIP
So I wrote the following regex
[0-9]{1,5}( [a-zA-Z.]*){1,4},?( [a-zA-Z]*){1,3},? [a-zA-Z]{2},? [0-9]{5}
This allows
1-5 Street #s
1-4 Street description words
1-3 City words
2 Char State
5 Char Zip code
I also added option , for separating street, city, state, zip
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))
UiPath Academy training video lists this RegEx for US addresses (and it works fine for me):
\b\d{1,8}(-)?[a-z]?\W[a-z|\W|\.]{1,}\W(road|drive|avenue|boulevard|circle|street|lane|waylrd\.|st\.|dr\.|ave\.|blvd\.|cir\.|In\.|rd|dr|ave|blvd|cir|ln)
I had a different use case - find any addresses in logs and scold application developers (favourite part of a devops job). I had the advantage of having the word "address" in the pattern but should work without that if you have specific field to scan
\baddress.[0-9\\\/# ,a-zA-Z]+[ ,]+[0-9\\\/#, a-zA-Z]{1,}
Look for the word "address" - skip this if not applicable
Look for first part numbers, letters, #, space - Unit Number / street number/suite number/door number
Separated by a space or comma
Look for one or more of rest of address numbers, letters, #, space
Tested against :
1 Sleepy Boulevard PO, Box 65745
Suite #100 /98,North St,Snoozepura
Ave., New Jersey,
Suite 420 1130 Connect Ave., NW,
Suite 420 19 / 21 Old Avenue,
Suite 12, Springfield, VIC 3001
Suite#100/98 North St Snoozepura
This worked for me when there were street addresses with unit/suite numbers, zip codes, only street. It also didn't match IP addresses or mac addresses. Worked with extra spaces.
This assumes users are normal people separate elements of a street address with a comma, hash sign, or space and not psychopaths who use characters like "|" or ":"!
For French address and some international address too, I use it.
[\\D+ || \\d]+\\d+[ ||,||[A-Za-z0-9.-]]+(?:[Rue|Avenue|Lane|... etcd|Ln|St]+[ ]?)+(?:[A-Za-z0-9.-](.*)]?)
I was inspired from the responses given here and came with those 2 solutions
support optional uppercase
support french also
regex structure
numbers (required)
letters, chars and spaces
at least one common address keyword (required)
as many chars you want before the line break
definitions:
accuracy
capacity of detecting addresses and not something that looks like an address which is not.
range
capacity to detect uncommon addresses.
Regex 1:
high accuracy
low range
/[0-9]+[ |[a-zà-ú.,-]* ((highway)|(autoroute)|(north)|(nord)|(south)|(sud)|(east)|(est)|(west)|(ouest)|(avenue)|(lane)|(voie)|(ruelle)|(road)|(rue)|(route)|(drive)|(boulevard)|(circle)|(cercle)|(street)|(cer\.)|(cir\.)|(blvd\.)|(hway\.)|(st\.)|(aut\.)|(ave\.)|(ln\.)|(rd\.)|(hw\.)|(dr\.)|(a\.))([ .,-]*[a-zà-ú0-9]*)*/i
regex 2:
low accuracy
high range
/[0-9]*[ |[a-zà-ú.,-]* ((highway)|(autoroute)|(north)|(nord)|(south)|(sud)|(east)|(est)|(west)|(ouest)|(avenue)|(lane)|(voie)|(ruelle)|(road)|(rue)|(route)|(drive)|(boulevard)|(circle)|(cercle)|(street)|(cer\.?)|(cir\.?)|(blvd\.?)|(hway\.?)|(st\.?)|(aut\.?)|(ave\.?)|(ln\.?)|(rd\.?)|(hw\.?)|(dr\.?)|(a\.))([ .,-]*[a-zà-ú0-9]*)*/i
This one works well for me
^(\d+) ?([A-Za-z](?= ))? (.*?) ([^ ]+?) ?((?<= )APT)? ?((?<= )\d*)?$
Source : https://community.alteryx.com/t5/Alteryx-Designer-Discussions/RegEx-Addresses-different-formats-and-headaches/td-p/360147
Here is my RegEx for address, city & postal validation rules
validation rules:
address -
1 - 40 characters length.
Letters, numbers, space and . , : ' #
city -
1 - 19 characters length
Only Alpha characters are allowed
Spaces are allowed
postalCode -
The USA zip must meet the following criteria and is required:
Minimum of 5 digits (9 digits if zip + 4 is provided)
Numeric only
A Canadian postal code is a six-character string.
in the format A1A 1A1, where A is a letter and 1 is a digit.
a space separates the third and fourth characters.
do not include the letters D, F, I, O, Q or U.
the first position does not make use of the letters W or Z.
address: ^[a-zA-Z0-9 .,#;:'-]{1,40}$
city: ^[a-zA-Z ]{1,19}$
usaPostal: ^([0-9]{5})(?:[-]?([0-9]{4}))?$
canadaPostal : ^(?!.*[DFIOQU])[A-VXY][0-9][A-Z] ?[0-9][A-Z][0-9]$
\b(\d{1,8}[a-z]?[0-9\/#- ,a-zA-Z]+[ ,]+[.0-9\/#, a-zA-Z]{1,})\n
A more dynamic approach to #micah would be the following:
(?'Address'(?'Street'[0-9][a-zA-Z\s]),?\s*(?'City'[A-Za-z\s]),?\s(?'Country'[A-Za-z])\s(?'Zipcode'[0-9]-?[0-9]))
It won't care about individual lengths of segments of code.
https://regex101.com/r/nuy7hB/1
I would like to extract portion of a text using a regular expression. So for example, I have an address and want to return just the number and streets and exclude the rest:
2222 Main at King Edward Vancouver BC CA
But the addresses varies in format most of the time. I tried using Lookbehind Regex and came out with this expression:
.*?(?=\w* \w* \w{2}$)
The above expressions handles the above example nicely but then it gets way too messy as soon as commas come into the text, postal codes which can be a 6 character string or two 3 character strings with a space in the middle, etc...
Is there any more elegant way of extracting a portion of text other than a lookbehind regex?
Any suggestion or a point in another direction is greatly appreciated.
Thanks!
Regular expressions are for data that is REGULAR, that follows a pattern. So if your data is completely random, no, there's no elegant way to do this with regex.
On the other hand, if you know what values you want, you can probably write a few simple regexes, and then just test them all on each string.
Ex.
regex1= address # grabber, regex2 = street type grabber, regex3 = name grabber.
Attempt a match on string1 with regex1, regex2, and finally regex3. Move on to the next string.
well i thot i'd throw my hat into the ring:
.*(?=,? ([a-zA-Z]+,?\s){3}([\d-]*\s)?)
and you might want ^ or \d+ at the front for good measure
and i didn't bother specifying lengths for the postal codes... just any amount of characters hyphens in this one.
it works for these inputs so far and variations on comas within the City/state/country area:
2222 Main at King Edward Vancouver, BC, CA, 333-333
555 road and street place CA US 95000
2222 Main at King Edward Vancouver BC CA 333
555 road and street place CA US
it is counting at there being three words at the end for the city, state and country but other than that it's like ryansstack said, if it's random it won't work. if the city is two words like New York it won't work. yeah... regex isn't the tool for this one.
btw: tested on regexhero.net
i can think of 2 ways you can do this
1) if you know that "the rest" of your data after the address is exactly 2 fields, ie BC and CA, you can do split on your string using space as delimiter, remove the last 2 items.
2) do a split on delimiter /[A-Z][A-Z]/ and store the result in array. then print out the array ( this is provided that the address doesn't contain 2 or more capital letters)