I am trying to find words and print using below code. Everything is working perfect but only issue is i am unable to print the last word(which is number).
words = ['Town of','Block No.','Lot No.','Premium (if any) Paid ']
import re
for i in words:
y = re.findall('{} ([^ ]*)'.format(i), textfile)
print(y)
Text file i working with:
textfile = """1, REBECCA M. ROTH , COLLECTOR OF TAXES of the taxing district of the
township of MORRIS for Six Hundred Sixty Seven dollars andFifty Two cents, the land
in said taxing district described as Block No. 10303 Lot No. 10 :
and known as 239 E HANOVER AVE , on the tax Taxes For: 2012
Sewer
Assessments For Improvements
Total Cost of Sale 35.00
Total
Premium (if any) Paid 1,400.00 """
Would like to know where am i making mistake.
Any suggestion is appreciated.
A couple of issues:
As others have mentioned, you need to escape special characters like parentheses ( ) and dots .. Very simply, you can use re.escape
Another issue is the trailing space in Premium \(if any\) Paid (it's trying to match two spaces instead of one as you're also checking for a space in your regex {} ([^ ]*))
You should instead change your code to the following:
See working code here
words = ['Town of','Block No.','Lot No.','Premium (if any) Paid']
import re
for i in words:
y = re.findall('{} ([^ ]*)'.format(re.escape(i)), textfile)
print(y)
Two problems:
Your current 'Premium (if any) Paid ' string ends on a space, and '{} ([^ ]*)' also has a space after {}, which adds them together. Delete the trailing space in 'Premium (if any) Paid '.
You need to escape parenthesis, so if you want to keep your regular expression unchanged, the string in the list should be ['Premium \(if any\) Paid']. You can also use re.escape instead.
For your particular cases, this seems to be an optimal solution:
words = ['Town of','Block No.','Lot No.','Premium (if any) Paid']
import re
for i in words:
y = re.findall('{}\s+([\S]*)'.format(re.escape(i)), text, re.I)
print(y)
I have following requirements in date which can be any of the following format.
mm/dd/yyyy or dd Mon YYYY
Few examples are shown below
04/20/2009 and 24 Jan 2001
To handle this I have written regular expression as below
Few text scenarios are metnioned below
txt1 = 'Lithium 0.25 (7/11/77). LFTS wnl. Urine tox neg. Serum tox
+ fluoxetine 500; otherwise neg. TSH 3.28. BUN/Cr: 16/0.83. Lipids unremarkable. B12 363, Folate >20. CBC: 4.9/36/308 Pertinent Medical
Review of Systems Constitutional:'
txt2 = "s The patient is a 44 year old married Caucasian woman,
unemployed Decorator, living with husband and caring for two young
children, who is referred by Capitol Hill Hospital PCP, Dr. Heather
Zubia, for urgent evaluation/treatment till first visit with Dr. Toney
Winkler IN EIGHT WEEKS on 24 Jan 2001."
date = re.findall(r'(?:\b(?<!\.)[\d{0,2}]+)'
'(?:[/-]\d{0,}[/-]\d{2,4}) | (?:\b(?<!\.)[\d{1,2}]+)[th|st|nd]*'
' (?:[Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec][a-z]*) \d{2,4}', txtData)
I am not getting 24 Jan 2001 where as if I run individually (?:\b(?<!\.)[\d{1,2}]+)[th|st|nd]* (?:[Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec][a-z]*) \d{2,4}' I am able to get output.
Question 1: What is bug in above expression?
Question 2: I want to combine both to make more readable as I have to parse any other formats so I used join as shown below
RE1 = '(?:\b(?<!\.)[\d{0,2}]+) (?:[/-]\d{0,}[/-]\d{2,4})'
RE2 = '(?:\b(?<!\.)[\d{1,2}]+)[th|st|nd]* (?:[Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec][a-z]*) \d{2,4}'
regex_all = '|'.join([RE1, RE2])
regex_all = re.compile(regex_all)
date = regex_all.findall(txtData) // notice here txtData can be any one of the above string.
I am getting output as NaN in case of above for date.
Please suggest what is the mistake if I join.
Thanks for your help.
Note that it is a very bad idea to join such long patterns that also match at the same location within the string. That would cause the regex engine to backtrack too much, and possibly lead to crashes and slowdown. If there is a way to re-write the alternations so that they could only match at different locations, or even get rid of them completely, do it.
Besides, you should use grouping constructs (...) to groups sequences of patterns, and only use [...] character classes when you need to matches specific chars.
Also, your alternatives are overlapping, you may combine them easily. See the fixed regex:
\b(?<!\.)\d{1,2}(?:[/-]\d+[/-]|(?:th|st|[nr]d)?\s*(?:(?:Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)[a-z]*))\s*(?:\d{4}|\d{2})\b
See the regex demo.
Details
\b - a word boundary
(?<!\.) - no . immediately to the left of the current location
\d{1,2} - 1 or 2 digits
(?: - start of a non-capturing alternation group:
[/-]\d+[/-] - / or -, 1+ digits, - or /
| - or
(?:th|st|[nr]d)?\s*(?:
(?:Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)[a-z]*)) - th, st, nd or rd (optionally), followed with 0+ whitespaces, and then month names
\s* - 0+ whitespaces
(?:\d{4}|\d{2}) - 2 or 4 digits
\b - trailing word boundary.
Another note: if you want to match the date-like strings with two matching delimiters, you will need to capture the first one, and use a backreference to match the second one, see this regex demo. In Python, you would need a re.finditer to get those matches.
See this Python demo:
import re
rx = r"\b(?<!\.)\d{1,2}(?:([/-])\d+\1|(?:th|st|[nr]d)?\s*(?:(?:Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)[a-z]*))\s*(?:\d{4}|\d{4})\b"
s = "Lithium 0.25 (7/11/77). LFTS wnl. Urine tox neg. Serum tox\nfluoxetine 500; otherwise neg. TSH 3.28. BUN/Cr: 16/0.83. Lipids unremarkable. B12 363, Folate >20. CBC: 4.9/36/308 Pertinent Medical\nReview of Systems Constitutional:\n\nThe patient is a 44 year old married Caucasian woman, unemployed Decorator, living with husband and caring for two young children, who is referred by Capitol Hill Hospital PCP, Dr. Heather Zubia, for urgent evaluation/treatment till first visit with Dr. Toney Winkler IN EIGHT WEEKS on 24 Jan 2001"
print([x.group(0) for x in re.finditer(rx, s, re.I)])
# => ['7/11/77', '24 Jan 2001']
I think your approach is too complicated. I suggest using a combination of a simple regex and strptime().
import re
from datetime import datetime
date_formats = ['%m/%d/%Y', '%d %b %Y']
pattern = re.compile(r'\b(\d\d?/\d\d?/\d{4}|\d\d? \w{3} \d{4})\b')
data = "... your string ..."
for match in re.findall(pattern, data):
print("Trying to parse '%s'" % match)
for fmt in date_formats:
try:
date = datetime.strptime(match, fmt)
print(" OK:", date)
break
except:
pass
The advantage of this approach is, besides a much more manageable regex, that it won't pick dates that look plausible but do not exist, like 2/29/2000 (whereas 2/29/2004 works).
r'(?:\b(?<!\.)[\d{0,2}]+)'
'(?:[/-]\d{0,}[/-]\d{2,4}) | (?:\b(?<!\.)[\d{1,2}]+)[th|st|nd]*'
' (?:[Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec][a-z]*) \d{2,4}'
you should use raw strings (r'foo') for each string, not only the first one. This way backslashes (\) will be considered as normal character and usable by the re library.
[abc|def] matches any character between the [], while (one|two|three) matches any expression (one, two, or three)
I've searched and searched, but can't find an any relief for my regex woes.
I wrote the following dummy sentence:
Watch Joe Smith Jr. and Saul "Canelo" Alvarez fight Oscar de la Hoya and Genaddy Triple-G Golovkin for the WBO belt GGG. Canelo Alvarez and Floyd 'Money' Mayweather fight in Atlantic City, New Jersey. Conor MacGregor will be there along with Adonis Superman Stevenson and Mr. Sugar Ray Robinson. "Here Goes a String". 'Money Mayweather'. "this is not a-string", "this is not A string", "This IS a" "Three Word String".
I'm looking for a regular expression that will return the following when used in Python 3.6:
Canelo, Money, Money Mayweather, Three Word String
The regex that has gotten me the closest is:
(["'])[A-Z](\\?.)*?\1
I want it to only match strings of 3 capitalized words or less immediately surrounded by single or double quotes. Unfortunately, so far it seem to match any string in quotes, no matter what the length, no matter what the content, as long is it begins with a capital letter.
I've put a lot of time into trying to hack through it myself, but I've hit a wall. Can anyone with stronger regex kung-fu give me an idea of where I'm going wrong here?
Try to use this one: (["'])((?:[A-Z][a-z]+ ?){1,3})\1
(["']) - opening quote
([A-Z][a-z]+ ?){1,3} - Capitalized word repeating 1 to 3 times separated by space
[A-Z] - capital char (word begining char)
[a-z]+ - non-capital chars (end of word)
_? - space separator of capitalized words (_ is a space), ? for single word w/o ending space
{1,3} - 1 to 3 times
\1 - closing quote, same as opening
Group 2 is what you want.
Match 1
Full match 29-37 `"Canelo"`
Group 1. 29-30 `"`
Group 2. 30-36 `Canelo`
Match 2
Full match 146-153 `'Money'`
Group 1. 146-147 `'`
Group 2. 147-152 `Money`
Match 3
Full match 318-336 `'Money Mayweather'`
Group 1. 318-319 `'`
Group 2. 319-335 `Money Mayweather`
Match 4
Full match 398-417 `"Three Word String"`
Group 1. 398-399 `"`
Group 2. 399-416 `Three Word String`
RegEx101 Demo: https://regex101.com/r/VMuVae/4
Working with the text you've provided, I would try to use regular expression lookaround to get the words surrounded by quotes and then apply some conditions on those matches to determine which ones meet your criterion. The following is what I would do:
[p for p in re.findall('(?<=[\'"])[\w ]{2,}(?=[\'"])', txt) if all(x.istitle() for x in p.split(' ')) and len(p.split(' ')) <= 3]
txt is the text you've provided here. The output is the following:
# ['Canelo', 'Money', 'Money Mayweather', 'Three Word String']
Cleaner:
matches = []
for m in re.findall('(?<=[\'"])[\w ]{2,}(?=[\'"])', txt):
if all(x.istitle() for x in m.split(' ')) and len(m.split(' ')) <= 3:
matches.append(m)
print(matches)
# ['Canelo', 'Money', 'Money Mayweather', 'Three Word String']
Here's my go at it: ([\"'])(([A-Z][^ ]*? ?){1,3})\1
This question already has answers here:
How can I split a text into sentences?
(20 answers)
Closed 3 years ago.
I want to make a list of sentences from a string and then print them out. I don't want to use NLTK to do this. So it needs to split on a period at the end of the sentence and not at decimals or abbreviations or title of a name or if the sentence has a .com This is attempt at regex that doesn't work.
import re
text = """\
Mr. Smith bought cheapsite.com for 1.5 million dollars, i.e. he paid a lot for it. Did he mind? Adam Jones Jr. thinks he didn't. In any case, this isn't true... Well, with a probability of .9 it isn't.
"""
sentences = re.split(r' *[\.\?!][\'"\)\]]* *', text)
for stuff in sentences:
print(stuff)
Example output of what it should look like
Mr. Smith bought cheapsite.com for 1.5 million dollars, i.e. he paid a lot for it.
Did he mind?
Adam Jones Jr. thinks he didn't.
In any case, this isn't true...
Well, with a probability of .9 it isn't.
(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s
Try this. split your string this.You can also check demo.
http://regex101.com/r/nG1gU7/27
Ok so sentence-tokenizers are something I looked at in a little detail, using regexes, nltk, CoreNLP, spaCy. You end up writing your own and it depends on the application. This stuff is tricky and valuable and people don't just give their tokenizer code away. (Ultimately, tokenization is not a deterministic procedure, it's probabilistic, and also depends very heavily on your corpus or domain, e.g. legal/financial documents vs social-media posts vs Yelp reviews vs biomedical papers...)
In general you can't rely on one single Great White infallible regex, you have to write a function which uses several regexes (both positive and negative); also a dictionary of abbreviations, and some basic language parsing which knows that e.g. 'I', 'USA', 'FCC', 'TARP' are capitalized in English.
To illustrate how easily this can get seriously complicated, let's try to write you that functional spec for a deterministic tokenizer just to decide whether single or multiple period ('.'/'...') indicates end-of-sentence, or something else:
function isEndOfSentence(leftContext, rightContext)
Return False for decimals inside numbers or currency e.g. 1.23 , $1.23, "That's just my $.02" Consider also section references like 1.2.A.3.a, European date formats like 09.07.2014, IP addresses like 192.168.1.1, MAC addresses...
Return False (and don't tokenize into individual letters) for known abbreviations e.g. "U.S. stocks are falling" ; this requires a dictionary of known abbreviations. Anything outside that dictionary you will get wrong, unless you add code to detect unknown abbreviations like A.B.C. and add them to a list.
Ellipses '...' at ends of sentences are terminal, but in the middle of sentences are not. This is not as easy as you might think: you need to look at the left context and the right context, specifically is the RHS capitalized and again consider capitalized words like 'I' and abbreviations. Here's an example proving ambiguity which : She asked me to stay... I left an hour later. (Was that one sentence or two? Impossible to determine)
You may also want to write a few patterns to detect and reject miscellaneous non-sentence-ending uses of punctuation: emoticons :-), ASCII art, spaced ellipses . . . and other stuff esp. Twitter. (Making that adaptive is even harder). How do we tell if #midnight is a Twitter user, the show on Comedy Central, text shorthand, or simply unwanted/junk/typo punctuation? Seriously non-trivial.
After you handle all those negative cases, you could arbitrarily say that any isolated period followed by whitespace is likely to be an end of sentence. (Ultimately, if you really want to buy extra accuracy, you end up writing your own probabilistic sentence-tokenizer which uses weights, and training it on a specific corpus(e.g. legal texts, broadcast media, StackOverflow, Twitter, forums comments etc.)) Then you have to manually review exemplars and training errors. See Manning and Jurafsky book or Coursera course [a].
Ultimately you get as much correctness as you are prepared to pay for.
All of the above is clearly specific to the English-language/ abbreviations, US number/time/date formats. If you want to make it country- and language-independent, that's a bigger proposition, you'll need corpora, native-speaking people to label and QA it all, etc.
All of the above is still only ASCII, which is practically speaking only 96 characters. Allow the input to be Unicode, and things get harder still (and the training-set necessarily must be either much bigger or much sparser)
In the simple (deterministic) case, function isEndOfSentence(leftContext, rightContext) would return boolean, but in the more general sense, it's probabilistic: it returns a float 0.0-1.0 (confidence level that that particular '.' is a sentence end).
References: [a] Coursera video: "Basic Text Processing 2-5 - Sentence Segmentation - Stanford NLP - Professor Dan Jurafsky & Chris Manning" [UPDATE: an unofficial version used to be on YouTube, was taken down]
Try to split the input according to the spaces rather than a dot or ?, if you do like this then the dot or ? won't be printed in the final result.
>>> import re
>>> s = """Mr. Smith bought cheapsite.com for 1.5 million dollars, i.e. he paid a lot for it. Did he mind? Adam Jones Jr. thinks he didn't. In any case, this isn't true... Well, with a probability of .9 it isn't."""
>>> m = re.split(r'(?<=[^A-Z].[.?]) +(?=[A-Z])', s)
>>> for i in m:
... print i
...
Mr. Smith bought cheapsite.com for 1.5 million dollars, i.e. he paid a lot for it.
Did he mind?
Adam Jones Jr. thinks he didn't.
In any case, this isn't true...
Well, with a probability of .9 it isn't.
sent = re.split('(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)(\s|[A-Z].*)',text)
for s in sent:
print s
Here the regex used is : (?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)(\s|[A-Z].*)
First block: (?<!\w\.\w.) : this pattern searches in a negative feedback loop (?<!) for all words (\w) followed by fullstop (\.) , followed by other words (\.)
Second block: (?<![A-Z][a-z]\.): this pattern searches in a negative feedback loop for anything starting with uppercase alphabets ([A-Z]), followed by lower case alphabets ([a-z]) till a dot (\.) is found.
Third block: (?<=\.|\?): this pattern searches in a feedback loop of dot (\.) OR question mark (\?)
Fourth block: (\s|[A-Z].*): this pattern searches after the dot OR question mark from the third block. It searches for blank space (\s) OR any sequence of characters starting with a upper case alphabet ([A-Z].*).
This block is important to split if the input is as
Hello world.Hi I am here today.
i.e. if there is space or no space after the dot.
Naive approach for proper english sentences not starting with non-alphas and not containing quoted parts of speech:
import re
text = """\
Mr. Smith bought cheapsite.com for 1.5 million dollars, i.e. he paid a lot for it. Did he mind? Adam Jones Jr. thinks he didn't. In any case, this isn't true... Well, with a probability of .9 it isn't.
"""
EndPunctuation = re.compile(r'([\.\?\!]\s+)')
NonEndings = re.compile(r'(?:Mrs?|Jr|i\.e)\.\s*$')
parts = EndPunctuation.split(text)
sentence = []
for part in parts:
if len(part) and len(sentence) and EndPunctuation.match(sentence[-1]) and not NonEndings.search(''.join(sentence)):
print(''.join(sentence))
sentence = []
if len(part):
sentence.append(part)
if len(sentence):
print(''.join(sentence))
False positive splitting may be reduced by extending NonEndings a bit. Other cases will require additional code. Handling typos in a sensible way will prove difficult with this approach.
You will never reach perfection with this approach. But depending on the task it might just work "enough"...
I'm not great at regular expressions, but a simpler version, "brute force" actually, of above is
sentence = re.compile("([\'\"][A-Z]|([A-Z][a-z]*\. )|[A-Z])(([a-z]*\.[a-z]*\.)|([A-Za-z0-9]*\.[A-Za-z0-9])|([A-Z][a-z]*\. [A-Za-z]*)|[^\.?]|[A-Za-z])*[\.?]")
which means
start acceptable units are '[A-Z] or "[A-Z]
please note, most regular expressions are greedy so the order is very important when we do |(or). That's, why I have written i.e. regular expression first, then is come forms like Inc.
Try this:
(?<!\b(?:[A-Z][a-z]|\d|[i.e]))\.(?!\b(?:com|\d+)\b)
I wrote this taking into consideration smci's comments above. It is a middle-of-the-road approach that doesn't require external libraries and doesn't use regex. It allows you to provide a list of abbreviations and accounts for sentences ended by terminators in wrappers, such as a period and quote: [.", ?', .)].
abbreviations = {'dr.': 'doctor', 'mr.': 'mister', 'bro.': 'brother', 'bro': 'brother', 'mrs.': 'mistress', 'ms.': 'miss', 'jr.': 'junior', 'sr.': 'senior', 'i.e.': 'for example', 'e.g.': 'for example', 'vs.': 'versus'}
terminators = ['.', '!', '?']
wrappers = ['"', "'", ')', ']', '}']
def find_sentences(paragraph):
end = True
sentences = []
while end > -1:
end = find_sentence_end(paragraph)
if end > -1:
sentences.append(paragraph[end:].strip())
paragraph = paragraph[:end]
sentences.append(paragraph)
sentences.reverse()
return sentences
def find_sentence_end(paragraph):
[possible_endings, contraction_locations] = [[], []]
contractions = abbreviations.keys()
sentence_terminators = terminators + [terminator + wrapper for wrapper in wrappers for terminator in terminators]
for sentence_terminator in sentence_terminators:
t_indices = list(find_all(paragraph, sentence_terminator))
possible_endings.extend(([] if not len(t_indices) else [[i, len(sentence_terminator)] for i in t_indices]))
for contraction in contractions:
c_indices = list(find_all(paragraph, contraction))
contraction_locations.extend(([] if not len(c_indices) else [i + len(contraction) for i in c_indices]))
possible_endings = [pe for pe in possible_endings if pe[0] + pe[1] not in contraction_locations]
if len(paragraph) in [pe[0] + pe[1] for pe in possible_endings]:
max_end_start = max([pe[0] for pe in possible_endings])
possible_endings = [pe for pe in possible_endings if pe[0] != max_end_start]
possible_endings = [pe[0] + pe[1] for pe in possible_endings if sum(pe) > len(paragraph) or (sum(pe) < len(paragraph) and paragraph[sum(pe)] == ' ')]
end = (-1 if not len(possible_endings) else max(possible_endings))
return end
def find_all(a_str, sub):
start = 0
while True:
start = a_str.find(sub, start)
if start == -1:
return
yield start
start += len(sub)
I used Karl's find_all function from this entry: Find all occurrences of a substring in Python
My example is based on the example of Ali, adapted to Brazilian Portuguese. Thanks Ali.
ABREVIACOES = ['sra?s?', 'exm[ao]s?', 'ns?', 'nos?', 'doc', 'ac', 'publ', 'ex', 'lv', 'vlr?', 'vls?',
'exmo(a)', 'ilmo(a)', 'av', 'of', 'min', 'livr?', 'co?ls?', 'univ', 'resp', 'cli', 'lb',
'dra?s?', '[a-z]+r\(as?\)', 'ed', 'pa?g', 'cod', 'prof', 'op', 'plan', 'edf?', 'func', 'ch',
'arts?', 'artigs?', 'artg', 'pars?', 'rel', 'tel', 'res', '[a-z]', 'vls?', 'gab', 'bel',
'ilm[oa]', 'parc', 'proc', 'adv', 'vols?', 'cels?', 'pp', 'ex[ao]', 'eg', 'pl', 'ref',
'[0-9]+', 'reg', 'f[ilí]s?', 'inc', 'par', 'alin', 'fts', 'publ?', 'ex', 'v. em', 'v.rev']
ABREVIACOES_RGX = re.compile(r'(?:{})\.\s*$'.format('|\s'.join(ABREVIACOES)), re.IGNORECASE)
def sentencas(texto, min_len=5):
# baseado em https://stackoverflow.com/questions/25735644/python-regex-for-splitting-text-into-sentences-sentence-tokenizing
texto = re.sub(r'\s\s+', ' ', texto)
EndPunctuation = re.compile(r'([\.\?\!]\s+)')
# print(NonEndings)
parts = EndPunctuation.split(texto)
sentencas = []
sentence = []
for part in parts:
txt_sent = ''.join(sentence)
q_len = len(txt_sent)
if len(part) and len(sentence) and q_len >= min_len and \
EndPunctuation.match(sentence[-1]) and \
not ABREVIACOES_RGX.search(txt_sent):
sentencas.append(txt_sent)
sentence = []
if len(part):
sentence.append(part)
if sentence:
sentencas.append(''.join(sentence))
return sentencas
Full code in: https://github.com/luizanisio/comparador_elastic
If you want to break up sentences at 3 periods (not sure if this is what you want) you can use this regular expresion:
import re
text = """\
Mr. Smith bought cheapsite.com for 1.5 million dollars, i.e. he paid a lot for it. Did he mind? Adam Jones Jr. thinks he didn't. In any case, this isn't true... Well, with a probability of .9 it isn't.
"""
sentences = re.split(r'\.{3}', text)
for stuff in sentences:
print(stuff)
I have this string.
string = """Horseradish CULTURE: Well-drained, friable soil with a pH
range of 6.2-6.8 will yield the best results. When roots are received,
work the soil about a foot deep and incorporate compost, manure, or
fertilizer. Make a 5-6" deep furrow and plant root cuttings 12" apart,
slanted 2-3" deep with the flat-cut end up..."""
and this code
seed_spacing = re.search(r'(?:sow|transplant|plant)(?:(?!rows).)+(\d+)(\'|") apart', string, re.I)
seed_spacing.group()
>>>Make a 5-6" deep furrow and plant root cuttings 12" apart
seed_spacing.group(1)
>>>2
I want to see 12, but I am getting 2. I need this to be flexible for cases in which it is a one digit number. I thought + was greedy. What am I missing?
+ is greedy - but it's not just greedy in \d+, it's also greedy in (?:(?!rows).)+. The latter is eating the 1. Perhaps you'd like (?:(?!rows)\D)+ better (that is, eat characters that aren't digits).
This part
(?:(?!rows).)+
of your regular expression is greedy and it matches till 1, so make it non-greedy like this
(?:(?!rows).)+?
You will get
seed_spacing.group(1)
as
12