Regex to find numbers that are not in a phrase - python-3.x

If I have e.g. this string:
Beschreibung Menge VK-Preis MwSt% Betrag
Schadenbewertunginkl.Restwertermittlung 1 25,00€ 19 25,00€
Rechnungsbetragexcl.MwSt.: 25,00€
MwSt.(19%): 4,75€
Rechnungsbetragincl.MwSt.: 123.029,75€
I want to extract all the numbers.
My regexes are:
regex_up_to_thousand = r'\b(?:\d{1,3}){1}(?:,{1}\d{2})\b'
and
regex_every_price = r'\b(?:\d{1,3}(\.|,))+(:?\d{3}(\.|,))(?:\d{2})\b'
My idea was to first get the "big" prices, remove them from the text and get the other numbers.
Which works in most cases, until I have a date that looks like this maybe
Gutachtennummer: 1009126 Leistungsdatum: 11.10.2021
I would get the 11.10 with my second regex, and I don't know how to prevent this.
I thought the \b would help, but sadly not.
Any ideas?
It's not the end of the world, since I do a lot of math in the background, but it's a possibility that a date would fit some values and I calculate something wrong in the end.


You could try the following pattern.
\b\d+(?:(?:\.|,)\d{3})*(?:(?:\.|,)\d{2})\b(?!\W\d)
The main thing is (?!\W\d) at the end which ensures that after your amount you will not have a construct of 1 non-word character followed by 1 digit.
Example: https://regex101.com/r/q1ic9S/1

Related

FuzzyWuzzy for very similar records in Python

I have a dataset with which I want to find the closest string match. For that purpose I'm using FuzzyWuzzy in this way
sol=process.extract(t,dev2,scorer=fuzz.token_sort_ratio)
Where t is the string and dev2 is the list to compare to. My problem is that sometimes it has very similar records and options provided by FuzzyWuzzy seems to be lacking. And I've tested with token_sort, token_set, partial_token sort and set, ratio, partial_ratio, and WRatio.
For example, the string Italy - Serie A gives me the following 2 closest matches.
Token_sort_ratio: (92, 'Italy - Serie D');(86, 'Italian - Serie A')
The one wanted is obviously the second one, but character by character is closer the first one, which is a different league.
This happens as well with teams. If, let's say I have a string Buchtholz I would obtains Buchtholz II before I get TSV Buchtholz.
My main guess now would be to try and weight the presence and absence of several characters more heavily, like single capital letters at the end of the string, so if there is a difference in the letter or an absence it is weighted as less close. Or for () and special characters.
I don't know if there is a way to take this into account or you guys have a better approach to get the string that really matches.

Similarity matches often require knowledge of the data being analysed. i.e. it is not just a blind single round of matching. I recommend that you pass your results through more steps of matching, starting with inclusive/optimistic approaches (like token_set_ratio) with low cut off scores and working toward more exclusive/pessimistic approaches with higher cut off scores until you have a clear winner. If you know more about the text you're analyzing, you can even modify the strings as you progress.
In a case I worked on, I did similarity matches of goods movement descriptions. In the descriptions the numbers sequences were more important than the text. e.g. when looking for a match for "SLURRY VALVE 250MM RAGMAX 2000" the 250 and 2000 part of the string are important, otherwise I get a "SLURRY VALVE 50MM RAGMAX 2000" as the best match instead of "VALVE B/F 250MM,RAGMAX 250RAG2000 RAGON" which is a better result.
I put the similarity match process through two steps: 1. Get a bunch of similar matches using an optimistic matching scorer (token_set_ratio) 2. get the number sequences of these results and pass them through another round of matching with a more strict scorer (token_sort_ratio). Doing this gave me the better result in the example I showed above.
Below is some blocks of code that could be of assistance:
here's a function to get numbers from the sequence. (In your case you might use this to exclude numbers from your string instead?)
def get_numbers_from_string(description):
numbers = ''.join((ch if ch in '0123456789.-' else ' ') for ch in description)
numbers = ' '.join([nr for nr in numbers.split()])
return numbers
and here is a portion of the code I used to put the description match through two rounds:
try:
# get close match from goods move that has material numbers
df_material = pd.DataFrame(process.extract(description,
corpus_material,
scorer=fuzz.token_set_ratio),
columns=['Similar Text','Score']
)
if df_material['Score'][df_material['Score']>=cut_off_accuracy_materials].count()>=1:
similar_text = df_material['Similar Text'].iloc[0]
score = df_material['Score'].iloc[0]
if nr_description_numbers>4:
# if there are multiple matches found, then get best number combination match
df_material = df_material[df_material['Score']>=cut_off_accuracy_materials]
new_corpus = list(df_material['Similar Text'])
new_corpus = np.vectorize(get_numbers_from_string)(new_corpus)
df_material['numbers'] = new_corpus
df_numbers = pd.DataFrame(process.extract(description_numbers,
new_corpus,
scorer=fuzz.token_sort_ratio),
columns=['numbers','Score']
)
similar_text = df_material['Similar Text'][df_material['numbers']==df_numbers['numbers'].iloc[0]].iloc[0]
nr_score = df_numbers['Score'].iloc[0]
hope it helps, and good luck

Add hyphen in between letters and hyphen

I have a list of sample names:
TW1
UD1
SS1
S17
SS23
UD12
I wish to add a hyphen in between the letters and the numbers as such:
TW-1
UD-1
SS-1
S-17
SS-23
UD-12
UD786
I tried this:
=MID(A1,1,COUNT(1*MID(A1,{1,2,3,4,5,6,7,8,9,0},1)))&"-"&SUBSTITUTE(A1,MID(A1,1,COUNT(1*MID(A1,{1,2,3,4,5,6,7,8,9,0},1))),"")
The results were not consistent. It gives the following results:
T-W1
U-D1
S-1
S1-7
SS-23
UD-12
How may I achieve the desired output?

=LEFT(A1,2-ISNUMBER(--MID(A1,2,1)))&"-"&RIGHT(A1,LEN(A1)-(2-ISNUMBER(--MID(A1,2,1))))
Is another option. Trick in this is to convert your number as a string to a number before testing if its a number. Instead of -- you could have done 1* or 0+.
This solution only works as your sample data was 1 or 2 characters before the first digit.

Slightly shorter than #Forward Ed's A:
=REPLACE(A1,2+(CODE(MID(A1,2,1))>64),,"-")

Lua: Search a specific string

Hi all tried all the string pattrens and library arguments but still stuck.
i want to get the name of the director from the following string i have tried the string.matcH but it matches the from the first character it finD from the string
the string is...
fixstrdirector = {id:39254,cast:[{id:15250,name:Hope Davis,character:Aunt Debra,order:5,cast_id:10,profile_path:/aIHF11Ss8P0A8JUfiWf8OHPVhOs.jpg},{id:53650,name:Anthony Mackie,character:Finn,order:3,cast_id:11,profile_path:/5VGGJ0Co8SC94iiedWb2o3C36T.jpg},{id:19034,name:Evangeline Lilly,character:Bailey Tallet,order:2,cast_id:12,profile_path:/oAOpJKgKEdW49jXrjvUcPcEQJb3.jpg},{id:6968,name:Hugh Jackman,character:Charlie Kenton,order:0,cast_id:13,profile_path:/wnl7esRbP3paALKn4bCr0k8qaFu.jpg},{id:79072,name:Kevin Durand,character:Ricky,order:4,cast_id:14,profile_path:/c95tTUjx5T0D0ROqTcINojpH6nB.jpg},{id:234479,name:Dakota Goyo,character:Max Kenton,order:1,cast_id:15,profile_path:/7PU6n4fhDuFwuwcYVyRNVEZE7ct.jpg},{id:8986,name:James Rebhorn,character:Marvin,order:6,cast_id:16,profile_path:/ezETMv0YM0Rg6YhKpu4vHuIY37D.jpg},{id:930729,name:Marco Ruggeri,character:Cliff,order:7,cast_id:17,profile_path:/1Ox63ukTd2yfOf1LVJOMXwmeQjO.jpg},{id:19860,name:Karl Yune,character:Tak Mashido,order:8,cast_id:18,profile_path:/qK315vPObCNdywdRN66971FtFez.jpg},{id:111206,name:Olga Fonda,character:Farra Lemkova,order:9,cast_id:19,profile_path:/j1qabOHf3Pf82f1lFpUmdF5XvSp.jpg},{id:53176,name:John Gatins,character:Kingpin,order:10,cast_id:41,profile_path:/A2MqnSKVzOuBf8MVfNyve2h2LxJ.jpg},{id:1126350,name:Sophie Levy,character:Big Sister,order:11,cast_id:42,profile_path:null},{id:1126351,name:Tess Levy,character:Little Sister,order:12,cast_id:43,profile_path:null},{id:1126352,name:Charlie Levy,character:Littlest Sister,order:13,cast_id:44,profile_path:null},{id:187983,name:Gregory Sims,character:Bill Panner,order:14,cast_id:45,profile_path:null}],crew:[{id:58726,name:Leslie Bohem,department:Writing,job:Screenplay,profile_path:null},{id:53176,name:John Gatins,department:Writing,job:Screenplay,profile_path:/A2MqnSKVzOuBf8MVfNyve2h2LxJ.jpg},{id:17825,name:Shawn Levy,department:Directing,job:Director,profile_path:/7f2f8EXdlWsPYN0HPGcIlG21xU.jpg},{id:12415,name:Richard Matheson,department:Writing,job:Story,profile_path:null},{id:57113,name:Dan Gilroy,department:Writing,job:Story,profile_path:null},{id:25210,name:Jeremy Leven,department:Writing,job:Story,profile_path:null},{id:17825,name:Shawn Levy,department:Production,job:Producer,profile_path:/7f2f8EXdlWsPYN0HPGcIlG21xU.jpg},{id:34970,name:Susan Montford,department:Production,job:Producer,profile_path:/1XJt51Y9ciPhkHrAYE0j6Jsmgji.jpg},{id:3183,name:Don Murphy,department:Production,job:Producer,profile_path:null},{id:34967,name:Rick Benattar,department:Production,job:Producer,profile_path:null},{id:1126348,name:Eric Hedayat,department:Production,job:Producer,profile_path:null},{id:186721,name:Ron Ames,department:Production,job:Producer,profile_path:null},{id:10956,name:Josh McLaglen,department:Production,job:Executive Producer,profile_path:null},{id:57634,name:Mary McLaglen,department:Production,job:Executive Producer,profile_path:null},{id:23779,name:Jack Rapke,department:Production,job:Executive Producer,profile_path:null},{id:488,name:Steven Spielberg,department:Production,job:Executive Producer,profile_path:/cuIYdFbEe89PHpoiOS9tmo84ED2.jpg},{id:30,name:Steve Starkey,department:Production,job:Executive Producer,profile_path:null},{id:24,name:Robert Zemeckis,department:Production,job:Executive Producer,profile_path:/isCuZ9PWIOyXzdf3ihodXzjIumL.jpg},{id:531,name:Danny Elfman,department:Sound,job:Original Music Composer,profile_path:/pWacZpYPos8io22nEiim7d3wp2j.jpg},{id:18265,name:Mauro Fiore,department:Crew,job:Cinematography,profile_path:null},{id:54271,name:Dean Zimmerman,department:Editing,job:Editor,profile_path:null},{id:25365,name:Richard Hicks,department:Production,job:Casting,profile_path:null},{id:5490,name:David Rubin,department:Production,job:Casting,profile_path:null},{id:52088,name:Tom Meyer,department:Art,job:Production Design,profile_path:null}]}
i have tried string.match(fixstrdirector,"name:(.+),department:Directing")
but it gives me the from the first occurace it find the name to the end of thr string
output:
Hope Davis,character:Aunt Debra,order:5,cast_id:10,profile_path:/aIHF11Ss8P0A8JUfiWf8OHPVhOs.jpg},{id:53650,name:Anthony Mackie,character:Finn,order:3,cast_id:11,profile_path:/5VGGJ0Co8SC94iiedWb2o3C36T.jpg},{id:19034,name:Evangeline Lilly,character:Bailey Tallet,order:2,cast_id:12,profile_path:/oAOpJKgKEdW49jXrjvUcPcEQJb3.jpg},{id:6968,name:Hugh Jackman,character:Charlie Kenton,order:0,cast_id:13,profile_path:/wnl7esRbP3paALKn4bCr0k8qaFu.jpg},{id:79072,name:Kevin Durand,character:Ricky,order:4,cast_id:14,profile_path:/c95tTUjx5T0D0ROqTcINojpH6nB.jpg},{id:234479,name:Dakota Goyo,character:Max Kenton,order:1,cast_id:15,profile_path:/7PU6n4fhDuFwuwcYVyRNVEZE7ct.jpg},{id:8986,name:James Rebhorn,character:Marvin,order:6,cast_id:16,profile_path:/ezETMv0YM0Rg6YhKpu4vHuIY37D.jpg},{id:930729,name:Marco Ruggeri,character:Cliff,order:7,cast_id:17,profile_path:/1Ox63ukTd2yfOf1LVJOMXwmeQjO.jpg},{id:19860,name:Karl Yune,character:Tak Mashido,order:8,cast_id:18,profile_path:/qK315vPObCNdywdRN66971FtFez.jpg},{id:111206,name:Olga Fonda,character:Farra Lemkova,order:9,cast_id:19,profile_path:/j1qabOHf3Pf82f1lFpUmdF5XvSp.jpg},{id:53176,name:John Gatins,character:Kingpin,order:10,cast_id:41,profile_path:/A2MqnSKVzOuBf8MVfNyve2h2LxJ.jpg},{id:1126350,name:Sophie Levy,character:Big Sister,order:11,cast_id:42,profile_path:null},{id:1126351,name:Tess Levy,character:Little Sister,order:12,cast_id:43,profile_path:null},{id:1126352,name:Charlie Levy,character:Littlest Sister,order:13,cast_id:44,profile_path:null},{id:187983,name:Gregory Sims,character:Bill Panner,order:14,cast_id:45,profile_path:null}],crew:[{id:58726,name:Leslie Bohem,department:Writing,job:Screenplay,profile_path:null},{id:53176,name:John Gatins,department:Writing,job:Screenplay,profile_path:/A2MqnSKVzOuBf8MVfNyve2h2LxJ.jpg},{id:17825,name:Shawn Levy

You're searching from the first occurrence of "name:" until the "department:Directing" with everything in between.
Instead, you need to restrict what can be between the two strings. Here for example I'm saying that the characters that make up the name can only be alphanumeric or a space:
string.match(fixstrdirector,"name:([%w ]+),department:Directing")
Alternatively, given that there's a comma separating the parameters, a better approach would be to search for "name:" followed by any characters other than a comma, followed by "department:Directing":
string.match(fixstrdirector,"name:([^,]+),department:Directing")
Of course that wouldn't work if the name had a comma it in!

Lua patterns provides - modifier for tasks as you have above. As stated on PiL - Section 20.2:
The + modifier matches one or more characters of the original class.
It will always get the longest sequence that matches the pattern.
Like *, the modifier - also matches zero or more occurrences of
characters of the original class. However, instead of matching the
longest sequence, it matches the shortest one.
Next, when you are using . to match, it'll find any and all characters satisfying the pattern. Therefore, you'll get the result from first occurence of name until the ,department:Directing is found. Since you know that it is a JSON data, you can try to match for [^,]; that is, non-comma characters.
So, for your case try:
local tAllNames = {}
for sName in fixstrdirector:gmatch( "name:([^,]-),department:Directing" ) do
tAllNames[ #tAllNames + 1 ] = sName
end
and all your required names will be stored in the table tAllNames. An example of the above can be seen at codepad.

find matching string in two strings

I would like to get hints for a perl script that finds the longest common substring present in two strings. Each string is maximal 500 characters long.
For example
abcsffwqfwqsdfasdfTHISISANAPPLEfasdfasdfsdfsadfasdfsdaf4353.54.4fdfsdgg
detertqteqtTHISISANAPPLEafsedfgwetwqrgtwrgtwetpqw4t5osdavm\wert4384..53
The output should be THISISANAPPLE
Sounds easy, but may not be trivial.
Anyone has an idea?

Check String::LCSS_XS
use String::LCSS_XS 'lcss';
my ($s1,$s2) = (
"abcsffwqfwqsdfasdfTHISISANAPPLEfasdfasdfsdfsadfasdfsdaf4353.54.4fdfsdgg",
"detertqteqtTHISISANAPPLEafsedfgwetwqrgtwrgtwetpqw4t5osdavm\wert4384..53"
);
my $longest = lcss ($s1, $s2);
print "$longest\n";
output
THISISANAPPLE

Oracle/SQL - Removing undefined chars from string

I currently have an assignemnt where i have to handle data from a lot of countries. My customer have given me a list of acceptable characters, lets call it:
'aber =*'
All other characters should just be changed to '_'.
I know the conversion for my country's specific chars (æøå), easily done with something like
select replace ('Ål', 'Å', 'AA') from dual;
But how would i go about removing all unwanted "noise" without splitting it up in char-by-char comparison?
For example "bear*2 = fear" should become "bear*_ = _ear" as 2 and f are not in the accepted list.

Oracle 10g and up. As one of the approaches, you can use regular expression function regexp_replace():
select regexp_replace('bear*2 = fear', '[^aber =*]', '_') as res
from dual
res
------------------------------
bear*_ = _ear
Find out more about regexp_replace() function.

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