Add City Union Bank Bank of Baroda and RBL statement parsers
This commit is contained in:
A R R R Associates
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from __future__ import annotations
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import re
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from pathlib import Path
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import pandas as pd
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from .base import BaseParser, StatementMeta, amount, extract_text, finalize, norm
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from .common import date_iso, find, infer_mode
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class BankOfBarodaParser(BaseParser):
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bank_name = "Bank of Baroda"
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parser_name = "BankOfBarodaParser"
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_DATE = re.compile(r"^(\d{2}-\d{2}-\d{2})\s+(.*)$")
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_BALANCE = re.compile(r"(-?[0-9,]+\.\d{2})(Cr|Dr)\s*$", re.I)
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_MONEY = re.compile(r"(?<![A-Za-z0-9])([0-9,]+\.\d{2})(?![A-Za-z0-9])")
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@classmethod
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def detect(cls, text: str) -> float:
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upper = (text or "").upper()
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score = 0.0
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if "BANK OF BARODA" in upper:
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score += 0.62
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if "BARB0" in upper or "IFSC CODE: BARB" in upper:
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score += 0.20
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if all(token in upper for token in ("DATE", "PARTICULARS", "CHQ.NO.", "WITHDRAWALS", "DEPOSITS", "BALANCE")):
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score += 0.16
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if "BOB ADVANTAGE" in upper:
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score += 0.02
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return min(score, 0.99)
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@staticmethod
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def _signed_balance(value: str, marker: str) -> float | None:
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parsed = amount(value)
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if parsed is None:
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return None
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return -abs(parsed) if marker.upper() == "DR" else abs(parsed)
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@staticmethod
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def _reference_number(narration: str, cheque_no: str) -> str:
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if norm(cheque_no):
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return norm(cheque_no)
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for pattern in (
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r"\bNEFT[-/]([A-Z0-9]{10,30})\b",
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r"\bRTGS[-/]([A-Z0-9]{10,30})\b",
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r"\b([0-9]{12,18})\b",
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):
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match = re.search(pattern, narration, re.I)
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if match:
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return match.group(1)
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return ""
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def parse(self, path, text=None):
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pdf_path = Path(path)
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text = text or extract_text(pdf_path)
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meta = StatementMeta(
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bank_name=self.bank_name,
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source_file=pdf_path.name,
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parser_name=self.parser_name,
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confidence="High",
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)
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meta.customer_name = norm(find(r"A/C Name\s*:\s*([^\n]+)", text, flags=re.I))
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meta.account_number = find(r"A/C Number\s*:\s*([0-9]+)", text, flags=re.I)
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meta.ifsc = find(r"IFSC CODE:\s*([A-Z0-9]+)", text, flags=re.I)
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period = re.search(r"Statement of account for the period of\s+(\d{2}-\d{2}-\d{4})\s+to\s+(\d{2}-\d{2}-\d{4})", text, re.I)
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if period:
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meta.period_from = date_iso(period.group(1))
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meta.period_to = date_iso(period.group(2))
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rows: list[dict] = []
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current: dict | None = None
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previous_balance: float | None = None
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opening_balance: float | None = None
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pages = re.split(r"\f", text)
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for page_no, page_text in enumerate(pages, start=1):
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for raw_line in page_text.splitlines():
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line = raw_line.rstrip()
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match = self._DATE.match(line.strip())
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if match:
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if current is not None:
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rows.append(current)
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previous_balance = current["balance"]
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current = None
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txn_date, remainder = match.groups()
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balance_match = self._BALANCE.search(remainder)
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if not balance_match:
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continue
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balance_value = self._signed_balance(balance_match.group(1), balance_match.group(2))
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before_balance = remainder[:balance_match.start()].rstrip()
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if norm(before_balance).upper() == "B/F":
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opening_balance = balance_value
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previous_balance = balance_value
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continue
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money_matches = list(self._MONEY.finditer(before_balance))
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narration_part = before_balance
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cheque_no = ""
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if money_matches:
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narration_part = before_balance[:money_matches[0].start()].rstrip()
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cheque_match = re.search(r"\s([0-9]{1,8})\s*$", narration_part)
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if cheque_match:
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cheque_no = cheque_match.group(1)
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narration_part = narration_part[:cheque_match.start()].rstrip()
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debit_value = credit_value = None
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if previous_balance is not None and balance_value is not None:
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delta = round(balance_value - previous_balance, 2)
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if delta < -0.009:
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debit_value = abs(delta)
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elif delta > 0.009:
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credit_value = delta
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elif money_matches:
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debit_value = amount(money_matches[-1].group(1))
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current = {
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"transaction_date": txn_date,
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"value_date": txn_date,
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"narration": norm(narration_part),
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"reference_no": self._reference_number(norm(narration_part), cheque_no),
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"debit": debit_value,
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"credit": credit_value,
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"balance": balance_value,
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"source_page": page_no,
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"mode": infer_mode(norm(narration_part)),
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}
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continue
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if current is not None:
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continuation = norm(line)
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upper = continuation.upper()
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if not continuation or upper.startswith(("PAGE TOTAL", "GRAND TOTAL", "BANK OF BARODA", "A/C NUMBER", "STATEMENT OF ACCOUNT", "DATE PARTICULARS", "NOTE:", "UNLESS ")):
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continue
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if set(continuation) <= {"-"}:
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continue
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current["narration"] = norm(f"{current['narration']} {continuation}")
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current["reference_no"] = self._reference_number(current["narration"], current["reference_no"])
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current["mode"] = infer_mode(current["narration"])
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if current is not None:
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rows.append(current)
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data = pd.DataFrame(rows)
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if not data.empty:
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first = data.iloc[0]
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first_balance = float(first["balance"])
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first_debit = float(first["debit"]) if pd.notna(first["debit"]) else 0.0
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first_credit = float(first["credit"]) if pd.notna(first["credit"]) else 0.0
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meta.opening_balance = round(opening_balance if opening_balance is not None else first_balance + first_debit - first_credit, 2)
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meta.total_debit = round(float(pd.to_numeric(data["debit"], errors="coerce").fillna(0).sum()), 2)
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meta.total_credit = round(float(pd.to_numeric(data["credit"], errors="coerce").fillna(0).sum()), 2)
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meta.closing_balance = round(float(data.iloc[-1]["balance"]), 2)
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return meta, finalize(data, meta)
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@@ -0,0 +1,107 @@
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from __future__ import annotations
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import re
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from pathlib import Path
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import pandas as pd
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import pdfplumber
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from .base import BaseParser, StatementMeta, amount, extract_text, finalize, norm
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from .common import date_iso, find, infer_mode
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class CityUnionBankParser(BaseParser):
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bank_name = "City Union Bank"
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parser_name = "CityUnionBankParser"
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@classmethod
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def detect(cls, text: str) -> float:
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upper = (text or "").upper()
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score = 0.0
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if "CITY UNION BANK" in upper:
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score += 0.62
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if "CIUB0" in upper or "IFSC :CIUB" in upper or "IFSC:CIUB" in upper:
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score += 0.20
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if all(token in upper for token in ("DATE", "DESCRIPTION", "CHEQUE NO", "DEBIT", "CREDIT", "BALANCE")):
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score += 0.16
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if "END OF STATEMENT - FROM INTERNET BANKING" in upper:
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score += 0.02
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return min(score, 0.99)
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@staticmethod
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def _reference_number(narration: str, cheque_no: str) -> str:
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if norm(cheque_no):
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return norm(cheque_no)
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for pattern in (
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r"\bUTR[:/\s-]*([A-Z0-9]{10,30})\b",
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r"\bCHQ\s*NO\s*([0-9]{1,12})\b",
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r"\b([A-Z]{4}H\d{10,})\b",
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):
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match = re.search(pattern, narration, re.I)
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if match:
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return match.group(1)
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return ""
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def parse(self, path, text=None):
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pdf_path = Path(path)
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text = text or extract_text(pdf_path)
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meta = StatementMeta(
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bank_name=self.bank_name,
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source_file=pdf_path.name,
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parser_name=self.parser_name,
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confidence="High",
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)
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meta.customer_name = norm(find(r"CUSTOMER DETAILS\s*:\s*([^\n]+)", text, flags=re.I))
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meta.account_number = find(r"ACCOUNT NO\s*\(15 DIGIT\)\s*:\s*([0-9]+)", text, flags=re.I)
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if not meta.account_number:
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meta.account_number = find(r"ACCOUNT NO\s*:\s*([A-Z0-9-]+)", text, flags=re.I)
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meta.ifsc = find(r"IFSC\s*:\s*([A-Z0-9]+)", text, flags=re.I)
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period = re.search(r"STATEMENT OF ACCOUNT\s+from\s+(\d{2}/\d{2}/\d{4})\s+to\s+(\d{2}/\d{2}/\d{4})", text, re.I)
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if period:
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meta.period_from = date_iso(period.group(1))
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meta.period_to = date_iso(period.group(2))
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rows: list[dict] = []
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with pdfplumber.open(str(pdf_path)) as pdf:
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for page_no, page in enumerate(pdf.pages, start=1):
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for table in page.extract_tables() or []:
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if not table:
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continue
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header = [norm(cell).upper() for cell in table[0]]
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if not all(token in header for token in ("DATE", "DESCRIPTION", "DEBIT", "CREDIT", "BALANCE")):
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continue
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for raw in table[1:]:
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cells = list(raw) + [None] * (6 - len(raw))
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txn_date, description, cheque_no, debit, credit, balance = cells[:6]
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txn_date = norm(txn_date)
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if not re.fullmatch(r"\d{2}/\d{2}/\d{4}", txn_date):
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continue
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debit_value = amount(debit)
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credit_value = amount(credit)
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balance_value = amount(balance)
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if debit_value is None and credit_value is None:
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continue
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narration = norm(description)
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rows.append({
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"transaction_date": txn_date,
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"value_date": txn_date,
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"narration": narration,
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"reference_no": self._reference_number(narration, norm(cheque_no)),
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"debit": debit_value,
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"credit": credit_value,
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"balance": balance_value,
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"source_page": page_no,
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"mode": infer_mode(narration),
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})
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data = pd.DataFrame(rows)
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if not data.empty:
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first = data.iloc[0]
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first_balance = float(first["balance"])
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first_debit = float(first["debit"]) if pd.notna(first["debit"]) else 0.0
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first_credit = float(first["credit"]) if pd.notna(first["credit"]) else 0.0
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meta.opening_balance = round(first_balance + first_debit - first_credit, 2)
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meta.total_debit = round(float(pd.to_numeric(data["debit"], errors="coerce").fillna(0).sum()), 2)
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meta.total_credit = round(float(pd.to_numeric(data["credit"], errors="coerce").fillna(0).sum()), 2)
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meta.closing_balance = round(float(data.iloc[-1]["balance"]), 2)
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return meta, finalize(data, meta)
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@@ -0,0 +1,119 @@
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from __future__ import annotations
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import re
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from pathlib import Path
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import pandas as pd
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import pdfplumber
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from .base import BaseParser, StatementMeta, amount, extract_text, finalize, norm
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from .common import date_iso, find, infer_mode
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class RBLBankParser(BaseParser):
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bank_name = "RBL Bank"
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parser_name = "RBLBankParser"
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@classmethod
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def detect(cls, text: str) -> float:
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upper = (text or "").upper()
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score = 0.0
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if "RBL BANK" in upper or "RBLBANK" in upper:
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score += 0.58
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if "RATN000" in upper or "IFSC/RTGS/NEFT" in upper and "RATN" in upper:
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score += 0.20
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if "STATEMENT OF TRANSACTIONS IN SAVINGS ACCOUNT" in upper:
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score += 0.12
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if all(token in upper for token in ("TRANSACTION DETAILS", "VALUE DATE", "WITHDRAWAL AMT", "DEPOSIT AMT", "BALANCE AMT")):
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score += 0.10
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return min(score, 0.99)
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@staticmethod
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def _signed_balance(value) -> float | None:
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text = norm(value).upper()
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parsed = amount(text)
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if parsed is None:
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return None
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return -abs(parsed) if text.endswith("DR") else abs(parsed)
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@staticmethod
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def _reference_number(narration: str, cheque_no: str) -> str:
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if norm(cheque_no):
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return norm(cheque_no)
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for pattern in (
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r"\bUPI/([0-9]{10,18})\b",
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r"\bIMPS\s+([0-9]{10,18})\b",
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r"\b(?:NEFT|RTGS)/([A-Z0-9]{10,30})\b",
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r"\b([0-9]{12,18})-IMPS\b",
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):
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match = re.search(pattern, narration, re.I)
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if match:
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return match.group(1)
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return ""
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def parse(self, path, text=None):
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pdf_path = Path(path)
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text = text or extract_text(pdf_path)
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meta = StatementMeta(
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bank_name=self.bank_name,
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source_file=pdf_path.name,
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parser_name=self.parser_name,
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confidence="High",
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)
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meta.customer_name = norm(find(r"Accountholder Name\s*:?\s*([^\n]+)", text, flags=re.I))
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meta.customer_id = find(r"CIF ID\s*:?\s*([0-9]+)", text, flags=re.I)
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meta.account_number = find(r"Statement Of Transactions In Savings Account No\.\s*([0-9]+)", text, flags=re.I)
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meta.ifsc = find(r"(?:IFSC/RTGS/NEFT|IFSC)\s*:?\s*([A-Z0-9]+)", text, flags=re.I)
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period = re.search(r"Period\s*:\s*(\d{2}-\d{2}-\d{4})\s+to\s+(\d{2}-\d{2}-\d{4})", text, re.I)
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if period:
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meta.period_from = date_iso(period.group(1))
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meta.period_to = date_iso(period.group(2))
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rows: list[dict] = []
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printed_opening: float | None = None
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with pdfplumber.open(str(pdf_path)) as pdf:
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for page_no, page in enumerate(pdf.pages, start=1):
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for table in page.extract_tables() or []:
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if not table:
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continue
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header = [norm(cell).upper() for cell in table[0]]
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if not all(token in header for token in ("DATE", "TRANSACTION DETAILS", "VALUE DATE", "WITHDRAWAL AMT", "DEPOSIT AMT", "BALANCE AMT")):
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continue
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for raw in table[1:]:
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cells = list(raw) + [None] * (7 - len(raw))
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txn_date, description, cheque_no, value_date, withdrawal, deposit, balance = cells[:7]
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txn_date = norm(txn_date)
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balance_value = self._signed_balance(balance)
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if not txn_date and balance_value is not None and printed_opening is None:
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printed_opening = balance_value
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continue
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if not re.fullmatch(r"\d{2}-[A-Za-z]{3}-\d{4}", txn_date):
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continue
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debit_value = amount(withdrawal)
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credit_value = amount(deposit)
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if debit_value is None and credit_value is None:
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continue
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narration = norm(description)
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rows.append({
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"transaction_date": txn_date,
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"value_date": norm(value_date) or txn_date,
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"narration": narration,
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"reference_no": self._reference_number(narration, norm(cheque_no)),
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"debit": debit_value,
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"credit": credit_value,
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"balance": balance_value,
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"source_page": page_no,
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"mode": infer_mode(narration),
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})
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data = pd.DataFrame(rows)
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if not data.empty:
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first = data.iloc[0]
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first_balance = float(first["balance"])
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first_debit = float(first["debit"]) if pd.notna(first["debit"]) else 0.0
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first_credit = float(first["credit"]) if pd.notna(first["credit"]) else 0.0
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meta.opening_balance = round(printed_opening if printed_opening is not None else first_balance + first_debit - first_credit, 2)
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meta.total_debit = round(float(pd.to_numeric(data["debit"], errors="coerce").fillna(0).sum()), 2)
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meta.total_credit = round(float(pd.to_numeric(data["credit"], errors="coerce").fillna(0).sum()), 2)
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meta.closing_balance = round(float(data.iloc[-1]["balance"]), 2)
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return meta, finalize(data, meta)
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@@ -11,6 +11,9 @@ from .kotak import KotakParser
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from .sbi import SBIModernParser, SBIOtherParser
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from .central_bank_of_india import CentralBankOfIndiaParser
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from .yes_bank import YesBankParser
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from .city_union_bank import CityUnionBankParser
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from .bank_of_baroda import BankOfBarodaParser
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from .rbl_bank import RBLBankParser
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from .base import extract_text
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PARSERS = [
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@@ -18,6 +21,9 @@ PARSERS = [
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AxisParser,
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CentralBankOfIndiaParser,
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YesBankParser,
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CityUnionBankParser,
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BankOfBarodaParser,
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RBLBankParser,
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HDFCParser,
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ICICIParser,
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HSBCParser,
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@@ -34,6 +40,9 @@ BANK_OPTIONS = [
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("axis", "Axis Bank"),
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||||
("central_bank_of_india", "Central Bank of India"),
|
||||
("yes_bank", "YES Bank"),
|
||||
("city_union_bank", "City Union Bank"),
|
||||
("bank_of_baroda", "Bank of Baroda"),
|
||||
("rbl_bank", "RBL Bank"),
|
||||
("hdfc", "HDFC Bank"),
|
||||
("icici", "ICICI Bank"),
|
||||
("hsbc", "HSBC Bank"),
|
||||
@@ -48,6 +57,9 @@ BANK_PARSERS = {
|
||||
"axis": [AxisParser],
|
||||
"central_bank_of_india": [CentralBankOfIndiaParser],
|
||||
"yes_bank": [YesBankParser],
|
||||
"city_union_bank": [CityUnionBankParser],
|
||||
"bank_of_baroda": [BankOfBarodaParser],
|
||||
"rbl_bank": [RBLBankParser],
|
||||
"hdfc": [HDFCParser],
|
||||
"icici": [ICICIParser],
|
||||
"hsbc": [HSBCParser],
|
||||
@@ -104,3 +116,4 @@ def parse_pdf(path, bank_hint: str | None = None):
|
||||
)
|
||||
return parser.parse(path, text)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user