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How to extract all comma delimited numbers inside () bracked and ignore any text

I am trying to extract the comma delimited numbers inside () brackets from a string. I can get the numbers if that are alone in a line. But i cant seem to find a solution to get the numbers when other surrounding text is involved. Any help will be appreciated. Below is the code that I current use in python.
line = """
Abuta has a history of use in the preparation of curares, an arrow poison to cause asphyxiation in hunting
It has also been used in traditional South American and Indian Ayurvedic medicines (101065,101066,101067)
The genus name Cissampelos is derived from the Greek words for ivy and vine (101065)
"""
line = each.strip()
regex_criteria = r'"^([1-9][0-9]*|\([1-9][0-9]*\}|\(([1-9][0-9]*,?)+[1-9][0-9]*\))$"gm'
if (line.__contains__('(') and line.__contains__(')') and not re.search('[a-zA-Z]', refline)):
refline = line[line.find('(')+1:line.find(')')]
if not re.search('[a-zA-Z]', refline):

Remove the ^, $ is whats preventing you from getting all the numbers. And gm flags wont work in python re.
You can change your regex to :([1-9][0-9]*|\([1-9][0-9]*\}|\(?:([1-9][0-9]*,?)+[1-9][0-9]*\)) if you want to get each number separately.
Or you can simplify your pattern to (?<=[(,])[1-9][0-9]+(?=[,)])
Test regex here: https://regex101.com/r/RlGwve/1
Python code:
import re
line = """
Abuta has a history of use in the preparation of curares, an arrow poison to cause asphyxiation in hunting
It has also been used in traditional South American and Indian Ayurvedic medicines (101065,101066,101067)
The genus name Cissampelos is derived from the Greek words for ivy and vine (101065)
"""
print(re.findall(r'(?<=[(,])[1-9][0-9]+(?=[,)])', line))
# ['101065', '101066', '101067', '101065']
(?<=[(,])[1-9][0-9]+(?=[,)])
The above pattern tells to match numbers which begin with 1-9 followed by one or more digits, only if the numbers begin with or end with either comma or brackets.

Here's another option:
pattern = re.compile(r"(?<=\()[1-9]+\d*(?:,[1-9]\d*)*(?=\))")
results = [match[0].split(",") for match in pattern.finditer(line)]
(?<=\(): Lookbehind for (
[1-9]+\d*: At least one number (would \d+ work too?)
(?:,[1-9]\d*)*: Zero or multiple numbers after a ,
(?=\)): Lookahead for )
Result for your line:
[['101065', '101066', '101067'], ['101065']]
If you only want the comma separated numbers:
pattern = re.compile(r"(?<=\()[1-9]+\d*(?:,[1-9]\d*)+(?=\))")
results = [match[0].split(",") for match in pattern.finditer(line)]
(?:,[1-9]\d*)+: One or more numbers after a ,
Result:
[['101065', '101066', '101067']]
Now, if your line could also look like
line = """
Abuta has a history of use in the preparation of curares, an arrow poison to cause asphyxiation in hunting
It has also been used in traditional South American and Indian Ayurvedic medicines ( 101065,101066, 101067 )
The genus name Cissampelos is derived from the Greek words for ivy and vine (101065)
"""
then you have to sprinkle the pattern with \s* and remove the whitespace afterwards (here with str.translate and str.maketrans):
pattern = re.compile(r"(?<=\()\s*[1-9]+\d*(?:\s*,\s*[1-9]\d*\s*)*(?=\))")
table = str.maketrans("", "", " ")
results = [match[0].translate(table).split(",") for match in pattern.finditer(line)]
Result:
[['101065', '101066', '101067'], ['101065']]

Using the pypi regex module you could also use capture groups:
\((?P<num>\d+)(?:,(?P<num>\d+))*\)
The pattern matches:
\( Match (
(?P<num>\d+) Capture group, match 1+ digits
(?:,(?P<num>\d+))* Optionally repeat matching , and 1+ digits in a capture group
\) Match )
Regex demo | Python demo
Example code
import regex
pattern = r"\((?P<num>\d+)(?:,(?P<num>\d+))*\)"
line = """
Abuta has a history of use in the preparation of curares, an arrow poison to cause asphyxiation in hunting
It has also been used in traditional South American and Indian Ayurvedic medicines (101065,101066,101067)
The genus name Cissampelos is derived from the Greek words for ivy and vine (101065)
"""
matches = regex.finditer(pattern, line)
for _, m in enumerate(matches, start=1):
print(m.capturesdict())
Output
{'num': ['101065', '101066', '101067']}
{'num': ['101065']}

Dealing with comma and fullstops as per convention

I have various instance of strings such as:
- hello world,i am 2000to -> hello world, i am 2000 to
- the state was 56,869,12th -> the state was 66,869, 12th
- covering.2% -> covering. 2%
- fiji,295,000 -> fiji, 295,000
For dealing with first case, I came up with two step regex:
re.sub(r"(?<=[,])(?=[^\s])(?=[^0-9])", r" ", text) # hello world, i am 20,000to
re.sub(r"(?<=[0-9])(?=[.^[a-z])", r" ", text) # hello world, i am 20,000 to
But this breaks the text in some different ways and other cases are not covered as well. Can anyone suggest a more general regex that solves all cases properly. I've tried using replace, but it does some unintended replacements which in turn raise some other problems. I'm not an expert in regex, would appreciate pointers.

This approach covers your cases above by breaking the text into tokens:
in_list = [
'hello world,i am 2000to',
'the state was 56,869,12th',
'covering.2%',
'fiji,295,000',
'and another example with a decimal 12.3not4,5 is right out',
'parrot,, is100.00% dead'
'Holy grail runs for this portion of 100 minutes,!, 91%. Fascinating'
]
tokenizer = re.compile(r'[a-zA-Z]+[\.,]?|(?:\d{1,3}(?:,\d{3})+|\d+)(?:\.\d+)?(?:%|st|nd|rd|th)?[\.,]?')
for s in in_list:
print(' '.join(re.findall(pattern=tokenizer, string=s)))
# hello world, i am 2000 to
# the state was 56,869, 12th
# covering. 2%
# fiji, 295,000
# and another example with a decimal 12.3 not 4, 5 is right out
# parrot, is 100.00% dead
# Holy grail runs for this portion of 100 minutes, 91%. Fascinating
Breaking up the regex, each token is the longest available substring with:
Only letters with or without a period or comma,[a-zA-Z]+[\.,]?
OR |
A number-ish expression which could be
1 to 3 digits \d{1,3} followed by any number of groups of comma + 3 digits (?:,\d{3})+
OR | any number of comma-free digits \d+
optionally a decimal place followed by at least one digit (?:\.\d+),
optionally a suffix (percent, 'st', 'nd', 'rd', 'th') (?:[\.,%]|st|nd|rd|th)?
optionally period or comma [\.]?
Note the (?:blah) is used to suppress re.findall's natural desire to tell you how every parenthesized group matches up on an individual basis. In this case we just want it to walk forward through the string, and the ?: accomplishes this.

Python Regular expression of group to match text before amount

I am trying to write a python regular expression which captures multiple values from a few columns in dataframe. Below regular expression attempts to do the same. There are 4 parts of the string.
group 1: Date - month and day
group 2: Date - month and day
group 3: description text before amount i.e. group 4
group 4: amount - this group is optional
Some peculiar conditions for group 3 - text that
(1)the text itself might contain characters like "-" , "$". So we cannot use - & $ as the boundary of text.
(2) The text (group 3) sometimes may not be followed by amount.
(3) Empty space between group 3 and 4 is optional
Below is python function code which takes in a dataframe having 4 columns c1,c2,c3,c4 adds the columns dt, txt and amt after processing to dataframe.
def parse_values(args):
re_1='(([JAN|FEB|MAR|APR|MAY|JUN|JUL|AUG|SEP|OCT|NOV|DEC]{3}\s{0,}[\d]{1,2})\s{0,}){2}(.*[\s]|.*[^\$]|.*[^-]){1}([-+]?\$[\d|,]+(?:\.\d+)?)?'
srch=re.search(re_1, args[0])
if srch is None:
return args
m = re.match(re_1, args[0])
args['dt']=m.group(1)
args['txt']=m.group(3)
args['amt']=m.group(4)
if m.group(4) is None:
if pd.isnull(args['c3']):
args['amt']=args.c2
else:
args['amt']=args.c3
return args
And in order to test the results I have below 6 rows which needs to return a properly formatted amt column in return.
tt=[{'c1':'OCT 7 OCT 8 HURRY CURRY THORNHILL ','c2':'$16.84'},
{'c1':'OCT 7 OCT 8 HURRY CURRY THORNHILL','c2':'$16.84'},
{'c1':'MAR 15 MAR 16 LOBLAWS FOODS INC - EAST YORK -$80,00,7770.70'},
{'c1':'MAR 15 MAR 16 LOBLAWS FOODS INC - EAST YORK-$2070.70'},
{'c1':'MAR 15 MAR 16 LOBLAWS FOODS INC - EAST YORK$2070.70'},
{'c1':'MAR 15 MAR 16 LOBLAWS FOODS INC - EAST YORK $80,00,7770.70'}
]
t=pd.DataFrame(tt,columns=['c1','c2','c3','c4'])
t=t.apply(parse_values,1)
t
However due to the error in my regular expression in re_1 I am not getting the amt column and txt column parsed properly as they return NaN or miss some words (as dipicted in some rows of the output image below).

How about this:
(((?:JAN|FEB|MAR|APR|MAY|JUN|JUL|AUG|SEP|OCT|NOV|DEC)\s*[\d]{1,2})\s*){2}(.*?)\s*(?=[\-$])([-+]?\$[\d|,]+(?:\.\d+)?)
As seen at regex101.com
Explanation:
First off, I've shortened the regex by changing a few minor details like using \s* instead of \s{0,}, which mean the exact same thing.
The whole [Jan|...|DEC] code was using a character class i.e. [], whcih only takes a single character from the entire set. Using non capturing groups is the correct way of selecting from different groups of multiple letters, which in your case are 'months'.
The meat of the regex: LOOKAHEADS
(?=[\-$]) tells the regex that the text before it in (.*) should match as much as it can until it finds a position followed by a dash or a dollar sign. Lookaheads don't actually match whatever they're looking for, they just tell the regex that the lookahead's arguments should be following that position.

Insert space after the second or third capital letter python

I have a pandas dataframe containing addresses. Some are formatted correctly like 481 Rogers Rd York ON. Others have a space missing between the city quandrant and the city name, for example: 101 9 Ave SWCalgary AB or even possibly: 101 9 Ave SCalgary AB, where SW refers to south west and S to south.
I'm trying to find a regex that will add a space between second and third capital letters if they are followed by lowercase letters, or if there are only 2 capitals followed by lower case, add a space between the first and second.
So far, I've found that ([A-Z]{2,3}[a-z]) will match the situation correctly, but I can't figure out how to look back into it and sub at position 2 or 3. Ideally, I'd like to use an index to split the match at [-2:] but I can't figure out how to do this.
I found that re.findall('(?<=[A-Z][A-Z])[A-Z][a-z].+', '101 9 Ave SWCalgary AB')
will return the last part of the string and I could use a look forward regex to find the start and then join them but this seems very inefficient.
Thanks

You may use
df['Test'] = df['Test'].str.replace(r'\b([A-Z]{1,2})([A-Z][a-z])', r'\1 \2')
See this regex demo
Details
\b - a word boundary
([A-Z]{1,2}) - Capturing group 1 (later referred with \1 from the replacement pattern): one or two uppercase letters
([A-Z][a-z]) - Capturing group 2 (later referred with \2 from the replacement pattern): an uppercase letter + a lowercase one.
If you want to specifically match city quadrants, you may use a bit more specific regex:
df['Test'] = df['Test'].str.replace(r'\b([NS][EW]|[NESW])([A-Z][a-z])', r'\1 \2')
See this regex demo. Here, [NS][EW]|[NESW] matches N or S that are followed with E or W, or a single N, E, S or W.
Pandas demo:
import pandas as pd
df = pd.DataFrame({'Test':['481 Rogers Rd York ON',
'101 9 Ave SWCalgary AB',
'101 9 Ave SCalgary AB']})
>>> df['Test'].str.replace(r'\b([A-Z]{1,2})([A-Z][a-z])', r'\1 \2')
0 481 Rogers Rd York ON
1 101 9 Ave SW Calgary AB
2 101 9 Ave S Calgary AB
Name: Test, dtype: object

You can use
([A-Z]{1,2})(?=[A-Z][a-z])
to capture the first (or first and second) capital letters, and then use lookahead for a capital letter followed by a lowercase letter. Then, replace with the first group and a space:
re.sub(r'([A-Z]{1,2})(?=[A-Z][a-z])', r'\1 ', str)
https://regex101.com/r/TcB4Ph/1

Regex to match strings in quotes that contain only 3 or less capitalized words

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