A R R R Associates
38 lines
2.3 KiB
Python
38 lines
2.3 KiB
Python
from __future__ import annotations
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import re, pandas as pd
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from pathlib import Path
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from .base import *
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from .common import find
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class AxisParser(BaseParser):
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bank_name='Axis Bank'; parser_name='AxisParser'
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@classmethod
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def detect(cls,text): return 0.98 if 'SMART STATEMENT REPORT' in text.upper() and 'UTIB' in text.upper() else 0
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def parse(self,path,text=None):
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text=text or extract_text(path); meta=StatementMeta(bank_name=self.bank_name,source_file=Path(path).name,parser_name=self.parser_name,confidence='High')
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# name is first meaningful line after report title
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m=re.search(r'Smart Statement Report\s*\n\s*([^\n]+)',text,re.I); meta.customer_name=norm(m.group(1)) if m else ''
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meta.account_number=find(r'Statement of Account No\s*-\s*([^\s]*)',text)
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meta.ifsc=find(r'IFSC:\s*([A-Z0-9]+)',text)
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m=re.search(r'for period\s*\((\d{2}/\d{2}/\d{4})\s+to\s+(\d{2}/\d{2}/\d{4})\)',text,re.I)
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if m: meta.period_from=pd.to_datetime(m.group(1),dayfirst=True).strftime('%Y-%m-%d'); meta.period_to=pd.to_datetime(m.group(2),dayfirst=True).strftime('%Y-%m-%d')
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meta.opening_balance=amount(find(r'Opening Balance:\s*INR\s*([\d,]+\.\d{2})',text))
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pat=re.compile(r'^\s*(\d+)\s+(\d{2}/\d{2}/\d{4})\s+(\d{2}/\d{2}/\d{4})\s+(.*)$')
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rows=[]; cur=None; page=1
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for line in text.splitlines():
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if '\f' in line: page+=line.count('\f')
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m=pat.match(line)
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if m:
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if cur: rows.append(cur)
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cur={'transaction_date':m.group(2),'value_date':m.group(3),'body':m.group(4),'source_page':page}
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elif cur and line.strip() and not re.match(r'^(S\. No\.|Smart Statement|Page )',line.strip(),re.I): cur['body']+=' '+line.strip()
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if cur: rows.append(cur)
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out=[]
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for r in rows:
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b=norm(r['body']); ma=re.search(r'INR\s*([\d,]+\.\d{2})\s+(CR|DR)\s+INR\s*([\d,]+\.\d{2})',b,re.I)
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if not ma: continue
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txn=amount(ma.group(1)); typ=ma.group(2).upper(); bal=amount(ma.group(3)); narr=b[:ma.start()].strip(); ref=''
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z=re.search(r'([A-Z0-9/-]{8,})',narr); ref=z.group(1) if z else ''
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out.append({**r,'narration':narr,'reference_no':ref,'debit':txn if typ=='DR' else None,'credit':txn if typ=='CR' else None,'balance':bal})
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return meta,finalize(pd.DataFrame(out),meta)
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