Add bank statement analyzer with automatic work storage
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A R R R Associates
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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 SBIModernParser(BaseParser):
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bank_name='State Bank of India'; parser_name='SBIModernParser'
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@classmethod
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def detect(cls,text):
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u=text.upper(); return 0.98 if 'STATE BANK OF INDIA' in u and 'REF NO./CHEQUE' in u and 'DETAILS' in u 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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meta.customer_name=find(r'Account Name\s*:?\s*([^\n]+)',text)
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meta.account_number=find(r'Account Number\s*:?\s*([0-9X*]+)',text)
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meta.ifsc=find(r'IFS Code\s*:?\s*([A-Z0-9]+)',text)
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m=re.search(r'Account Statement from\s*(\d{1,2}\s+[A-Za-z]{3}\s+\d{4})\s+to\s+(\d{1,2}\s+[A-Za-z]{3}\s+\d{4})',text,re.I)
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if m:
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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'Balance as on[^\n]*\n\s*([\d,]+\.\d{2})',text))
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# Format A: date details ref debit credit balance
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date_re=re.compile(r'^\s*(\d{1,2}\s+[A-Za-z]{3}\s+\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=date_re.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(1),'value_date':m.group(1),'lines':[m.group(2)],'source_page':page}
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elif cur and line.strip() and not re.match(r'^(Date\s+Details|Txn Date|Account Statement|State Bank)',line.strip(),re.I):
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cur['lines'].append(line)
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if cur: rows.append(cur)
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out=[]; prev=meta.opening_balance
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for r in rows:
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first=r['lines'][0]; alltxt=norm(' '.join(r['lines']))
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nums=list(re.finditer(r'(?<!\d)([\d,]+\.\d{2})(?!\d)',first))
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if not nums: continue
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bal=amount(nums[-1].group(1)); debit=credit=None
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# use dashes and positions from SBI layout: debit then credit then balance
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if len(nums)>=2:
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txn=amount(nums[-2].group(1)); p=nums[-2].start()
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if prev is not None and bal is not None:
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if abs((prev-txn)-bal)<0.05: debit=txn
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elif abs((prev+txn)-bal)<0.05: credit=txn
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if debit is None and credit is None:
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if p >= 78: credit=txn
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else: debit=txn
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narr=first[:nums[-2].start() if len(nums)>=2 else nums[-1].start()].strip()+' '+' '.join(x.strip() for x in r['lines'][1:])
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ref=''; z=re.search(r'(?:UPI|NEFT|IMPS|RTGS)[/A-Z0-9-]{6,}',alltxt,re.I); ref=z.group(0) if z else ''
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if debit is None and credit is None: continue
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out.append({**r,'narration':norm(narr),'reference_no':ref,'debit':debit,'credit':credit,'balance':bal})
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if bal is not None: prev=bal
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if out:
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if meta.opening_balance is None:
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f=out[0]; meta.opening_balance=round((f['balance'] or 0)+(f.get('debit') or 0)-(f.get('credit') or 0),2)
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meta.closing_balance=out[-1]['balance']
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return meta,finalize(pd.DataFrame(out),meta)
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class SBIOtherParser(BaseParser):
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bank_name='State Bank of India'; parser_name='SBIOtherParser'
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@classmethod
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def detect(cls,text):
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u=text.upper(); return 0.97 if 'TXN DATE' in u and 'VALUE' in u and 'REF NO./CHEQUE' in u and 'BY TRANSFER' in u 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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meta.customer_name=find(r'Account Name\s*:\s*([^\n]+)',text)
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meta.account_number=find(r'Account Number\s*:?\s*([0-9X*]+)',text)
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meta.ifsc=find(r'IFS Code\s*:?\s*([A-Z0-9]+)',text)
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m=re.search(r'Account Statement from\s*(\d{1,2}\s+[A-Za-z]{3}\s+\d{4})\s+to\s+(\d{1,2}\s+[A-Za-z]{3}\s+\d{4})',text,re.I)
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if m:
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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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m=re.search(r'Balance as on\s+[^\n]+\n',text,re.I)
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date_re=re.compile(r'^\s*(\d{1,2}\s+[A-Za-z]{3}\s+\d{4})\s+(\d{1,2}\s+[A-Za-z]{3}\s+\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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mm=date_re.match(line)
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if mm:
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if cur: rows.append(cur)
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cur={'transaction_date':mm.group(1),'value_date':mm.group(2),'lines':[mm.group(3)],'source_page':page}
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elif cur and line.strip() and not re.match(r'^(Txn Date|Account Statement|Account Name)',line.strip(),re.I): cur['lines'].append(line)
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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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first=r['lines'][0]; alltxt=norm(' '.join(r['lines']))
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nums=list(re.finditer(r'(?<!\d)([\d,]+\.\d{2})(?!\d)',first))
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if not nums: continue
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bal=amount(nums[-1].group(1)); debit=credit=None
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if len(nums)>=2:
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txn=amount(nums[-2].group(1)); p=nums[-2].start()
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# Based on header layout: Debit starts before Credit
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if p < 55: debit=txn
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else: credit=txn
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narr=first[:nums[-2].start() if len(nums)>=2 else nums[-1].start()].strip()+' '+' '.join(x.strip() for x in r['lines'][1:])
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ref=''; z=re.search(r'(?:UPI|NEFT|IMPS|RTGS)[/A-Z0-9-]{6,}',alltxt,re.I); ref=z.group(0) if z else ''
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if debit is None and credit is None: continue
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out.append({**r,'narration':norm(narr),'reference_no':ref,'debit':debit,'credit':credit,'balance':bal})
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if out:
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f=out[0]; meta.opening_balance=round((f['balance'] or 0)+(f.get('debit') or 0)-(f.get('credit') or 0),2); meta.closing_balance=out[-1]['balance']
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return meta,finalize(pd.DataFrame(out),meta)
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