Add support for multiple SBI statement layouts

This commit is contained in:
A R R R Associates
2026-08-03 10:24:31 +05:30
parent a7da29badb
commit 64368247df
2 changed files with 408 additions and 118 deletions
@@ -7,7 +7,7 @@ from .hsbc import HSBCParser
from .indian_bank import IndianBankModernParser, IndianBankLegacyParser
from .indusind import IndusIndParser
from .kotak import KotakParser
from .sbi import SBIModernParser, SBIOtherParser
from .sbi import SBIYONORelationshipParser, SBIStandardParser, SBICompactParser, SBIModernParser, SBIOtherParser
from .base import extract_text
PARSERS = [
@@ -19,8 +19,9 @@ PARSERS = [
IndianBankLegacyParser,
IndusIndParser,
KotakParser,
SBIOtherParser,
SBIModernParser,
SBIYONORelationshipParser,
SBIStandardParser,
SBICompactParser,
]
BANK_OPTIONS = [
@@ -43,7 +44,7 @@ BANK_PARSERS = {
"indian_bank": [IndianBankModernParser, IndianBankLegacyParser],
"indusind": [IndusIndParser],
"kotak": [KotakParser],
"sbi": [SBIOtherParser, SBIModernParser],
"sbi": [SBIYONORelationshipParser, SBIStandardParser, SBICompactParser],
}
+402 -113
View File
@@ -1,120 +1,409 @@
from __future__ import annotations
import re, pandas as pd
import os
import re
import subprocess
import tempfile
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
from .base import *
from .common import DATE_TOKEN_PATTERN, date_iso, find
class SBIModernParser(BaseParser):
bank_name='State Bank of India'; parser_name='SBIModernParser'
@classmethod
def detect(cls,text):
u=norm(text).upper()
bank_marker='STATE BANK OF INDIA' in u
digital_layout='REF NO./CHEQUE' in u and 'DETAILS' in u
yono_print_layout=(
'STATEMENT OF ACCOUNT' in u
and 'VALUE DATE' in u
and 'POST DATE' in u
and 'DEBIT' in u
and 'CREDIT' in u
and 'BALANCE' in u
import pandas as pd
import pdfplumber
from .base import BaseParser, StatementMeta, amount, extract_text, finalize, norm
from .common import DATE_TOKEN_PATTERN, date_iso, find, parse_flexible_date
_MONEY_RE = re.compile(r"(?<![\d.])([\d,]+\.\d{2})(?!\d)")
_REFERENCE_RE = re.compile(
r"(?:UPI|NEFT|IMPS|RTGS|UTR|CHEQUE|CHQ)[/ :A-Z0-9._-]{5,}", re.I
)
_HEADER_RE = re.compile(
r"^(?:REF\s*NO|VALUE\s*DATE|POST\s*DATE|TXN\s*DATE|DATE\s+DETAILS|"
r"ACCOUNT\s+STATEMENT|STATEMENT\s+OF\s+ACCOUNT|STATE\s+BANK\s+OF\s+INDIA|"
r"PAGE\s+NO|STATEMENT\s+SUMMARY|BROUGHT\s+FORWARD|DR\s+COUNT|CR\s+COUNT)",
re.I,
)
return 0.98 if bank_marker and (digital_layout or yono_print_layout) else 0
def parse(self,path,text=None):
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')
meta.customer_name=find(r'Account Name\s*:?\s*([^\n]+)',text)
if not meta.customer_name:
meta.customer_name=find(r'\bMs\.?\s+([A-Z][A-Z .]{3,})',text)
meta.account_number=find(r'Account Number\s*:?\s*([0-9X*]+)',text)
meta.ifsc=find(r'(?:IFS|IFSC) Code\s*:?\s*([A-Z0-9]+)',text)
m=re.search(rf'(?:Account Statement from|Statement From\s*:?)\s*({DATE_TOKEN_PATTERN})\s+to\s+({DATE_TOKEN_PATTERN})', text, re.I)
if m:
meta.period_from=date_iso(m.group(1)); meta.period_to=date_iso(m.group(2))
meta.opening_balance=amount(find(r'Balance as on[^\n]*\n\s*([\d,]+\.\d{2})',text))
# Format A: date details ref debit credit balance
date_re=re.compile(rf'^\s*({DATE_TOKEN_PATTERN})\s+(.*)$', re.I)
rows=[]; cur=None; page=1
for line in text.splitlines():
if '\f' in line: page += line.count('\f')
m=date_re.match(line)
if m:
if cur: rows.append(cur)
cur={'transaction_date':m.group(1),'value_date':m.group(1),'lines':[m.group(2)],'source_page':page}
elif cur and line.strip() and not re.match(r'^(Date\s+Details|Txn Date|Account Statement|State Bank)',line.strip(),re.I):
cur['lines'].append(line)
if cur: rows.append(cur)
out=[]; prev=meta.opening_balance
for r in rows:
first=r['lines'][0]; alltxt=norm(' '.join(r['lines']))
nums=list(re.finditer(r'(?<!\d)([\d,]+\.\d{2})(?!\d)',first))
if not nums: continue
bal=amount(nums[-1].group(1)); debit=credit=None
# use dashes and positions from SBI layout: debit then credit then balance
if len(nums)>=2:
txn=amount(nums[-2].group(1)); p=nums[-2].start()
if prev is not None and bal is not None:
if abs((prev-txn)-bal)<0.05: debit=txn
elif abs((prev+txn)-bal)<0.05: credit=txn
if debit is None and credit is None:
upper=alltxt.upper()
if '/CR/' in upper or upper.startswith('DEP TFR') or 'INTEREST CREDIT' in upper:
credit=txn
elif '/DR/' in upper or upper.startswith('WDL TFR') or upper.startswith('DEBIT '):
debit=txn
elif p >= 78:
credit=txn
else:
debit=txn
narr=first[:nums[-2].start() if len(nums)>=2 else nums[-1].start()].strip()+' '+' '.join(x.strip() for x in r['lines'][1:])
ref=''; z=re.search(r'(?:UPI|NEFT|IMPS|RTGS)[/A-Z0-9-]{6,}',alltxt,re.I); ref=z.group(0) if z else ''
if debit is None and credit is None: continue
out.append({**r,'narration':norm(narr),'reference_no':ref,'debit':debit,'credit':credit,'balance':bal})
if bal is not None: prev=bal
if out:
if meta.opening_balance is None:
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']
return meta,finalize(pd.DataFrame(out),meta)
class SBIOtherParser(BaseParser):
bank_name='State Bank of India'; parser_name='SBIOtherParser'
def _expected_summary_transactions(text: str) -> int | None:
counts = re.findall(
r"(?:Brought\s+Forward.*?)(\d{1,3})\s+(\d{1,3})\s+[\d,]+\.\d{2}\s+[\d,]+\.\d{2}",
text,
re.I | re.S,
)
if not counts:
return None
return sum(int(debit_count) + int(credit_count) for debit_count, credit_count in counts)
def _ocr_yono_page(pdf_path: Path, page_number: int, work_dir: Path, dpi: int) -> tuple[int, str]:
prefix = work_dir / f"sbi_yono_{page_number:05d}"
image_path = prefix.with_suffix(".png")
render = subprocess.run(
[
"pdftoppm", "-f", str(page_number), "-l", str(page_number),
"-r", str(dpi), "-png", "-singlefile", str(pdf_path), str(prefix),
],
capture_output=True,
text=True,
timeout=180,
check=False,
)
if render.returncode != 0 or not image_path.exists():
raise RuntimeError(render.stderr.strip() or f"Unable to render SBI page {page_number}.")
try:
environment = os.environ.copy()
environment.setdefault("OMP_THREAD_LIMIT", "1")
ocr = subprocess.run(
[
"tesseract", str(image_path), "stdout", "-l", "eng",
"--psm", "6", "-c", "preserve_interword_spaces=1",
],
capture_output=True,
text=True,
timeout=180,
check=False,
env=environment,
)
if ocr.returncode != 0:
raise RuntimeError(ocr.stderr.strip() or f"SBI OCR failed for page {page_number}.")
return page_number, ocr.stdout or ""
finally:
image_path.unlink(missing_ok=True)
def _extract_yono_table_text(path: str | Path) -> str:
pdf_path = Path(path)
dpi = max(120, min(int(os.getenv("BANK_ANALYZER_SBI_OCR_DPI", "150")), 220))
workers = max(1, min(int(os.getenv("BANK_ANALYZER_SBI_OCR_WORKERS", "2")), 3))
with pdfplumber.open(str(pdf_path)) as pdf:
page_count = len(pdf.pages)
pages: dict[int, str] = {}
with tempfile.TemporaryDirectory(prefix="sbi_yono_ocr_") as temporary:
work_dir = Path(temporary)
with ThreadPoolExecutor(max_workers=min(workers, page_count)) as executor:
futures = {
executor.submit(_ocr_yono_page, pdf_path, page, work_dir, dpi): page
for page in range(1, page_count + 1)
}
for future in as_completed(futures):
page_number, page_text = future.result()
pages[page_number] = page_text
return "\n\f\n".join(pages.get(page, "") for page in range(1, page_count + 1))
def _page_increment(line: str) -> int:
return line.count("\f")
def _extract_common_meta(text: str, path: str | Path, parser_name: str) -> StatementMeta:
meta = StatementMeta(
bank_name="State Bank of India",
source_file=Path(path).name,
parser_name=parser_name,
confidence="High",
)
meta.customer_name = find(r"Account Name\s*:?\s*([^\n]+)", text)
if not meta.customer_name:
meta.customer_name = find(r"\b(?:Ms|Mr|Mrs)\.?\s+([A-Z][A-Z .]{3,})", text)
meta.account_number = find(r"Account Number\s*:?\s*([0-9Xx*]+)", text)
meta.ifsc = find(r"(?:IFS|IFSC) Code\s*:?\s*([A-Z0-9]+)", text)
periods = re.findall(
rf"(?:Account Statement from|Statement From\s*:?)\s*({DATE_TOKEN_PATTERN})\s+to\s+({DATE_TOKEN_PATTERN})",
text,
re.I,
)
if periods:
parsed = [
(parse_flexible_date(start), parse_flexible_date(end))
for start, end in periods
]
parsed = [(start, end) for start, end in parsed if not pd.isna(start) and not pd.isna(end)]
if parsed:
meta.period_from = min(start for start, _ in parsed).strftime("%Y-%m-%d")
meta.period_to = max(end for _, end in parsed).strftime("%Y-%m-%d")
return meta
def _opening_from_summary(text: str) -> float | None:
patterns = (
r"Brought\s+Forward\s*(?:\([^)]*\))?\s*[:\-]?\s*([\d,]+\.\d{2})\s*(CR|DR)?",
r"Balance\s+as\s+on[^\n]*?([\d,]+\.\d{2})\s*(CR|DR)?",
)
for pattern in patterns:
match = re.search(pattern, text, re.I | re.S)
if not match:
continue
value = amount(match.group(1))
suffix = (match.group(2) or "").upper() if match.lastindex and match.lastindex >= 2 else ""
if value is not None and suffix == "DR":
value = -value
if value is not None:
return value
return None
def _reference(narration: str) -> str:
match = _REFERENCE_RE.search(narration or "")
return norm(match.group(0)) if match else ""
def _semantic_side(narration: str) -> str:
upper = norm(narration).upper()
credit_markers = (
"/CR/", "BY TRANSFER", "TRANSFER FROM", "DEP TFR", "DEPOSIT",
"INTEREST CREDIT", "CREDIT INTEREST", "CASH DEP", "REVERSAL", "REFUND",
)
debit_markers = (
"/DR/", "TO TRANSFER", "TRANSFER TO", "WDL TFR", "WITHDRAWAL",
"ATM WDL", "DEBIT-", "DEBIT ", "CAS PRES", "CHQ", "CHEQUE",
)
if any(marker in upper for marker in credit_markers):
return "credit"
if any(marker in upper for marker in debit_markers):
return "debit"
return ""
def _row_values(first_line: str, narration: str, previous_balance: float | None):
tokens = list(_MONEY_RE.finditer(first_line))
if not tokens:
return None, None, None, first_line
balance = amount(tokens[-1].group(1))
movement_candidates = [amount(match.group(1)) for match in tokens[:-1]]
movement_candidates = [value for value in movement_candidates if value is not None]
debit = credit = None
if previous_balance is not None and balance is not None:
delta = round(balance - previous_balance, 2)
if abs(delta) >= 0.01:
matching = next(
(value for value in reversed(movement_candidates) if abs(abs(delta) - value) <= 0.05),
None,
)
movement = matching if matching is not None else abs(delta)
if delta < 0:
debit = movement
else:
credit = movement
elif movement_candidates:
movement = movement_candidates[-1]
side = _semantic_side(narration)
if side == "credit":
credit = movement
else:
debit = movement
narration_end = tokens[-2].start() if len(tokens) >= 2 else tokens[-1].start()
return debit, credit, balance, first_line[:narration_end].strip()
def _parse_rows(
text: str,
meta: StatementMeta,
start_re: re.Pattern[str],
date_groups: int,
) -> pd.DataFrame:
# OCR engines occasionally place two adjacent SBI transactions on one
# physical line. Split before every detected date pair so each transaction
# reaches the normal row collector independently.
text = re.sub(
r"(?<!\n)(?=(?:\d{1,2}[/-]\d{1,2}[/-]\d{2,4})\s+"
r"(?:\d{1,2}[/-]\d{1,2}[/-]\d{2,4})\s+)",
"\n",
text,
)
# Typical OCR noise turns 12/05/2025 into 12105/2025 by reading the first
# slash as the digit 1. Correct only at a transaction-line boundary.
text = re.sub(
r"(?m)^(\s*)(\d{1,2})[1|](\d{2})/(\d{4})(?=\s)",
r"\1\2/\3/\4",
text,
)
rows: list[dict] = []
current: dict | None = None
page = 1
for raw_line in text.splitlines():
page += _page_increment(raw_line)
line = raw_line.replace("\f", "").rstrip()
match = start_re.match(line)
if match:
if current:
rows.append(current)
transaction_date = match.group(1)
value_date = match.group(2) if date_groups == 2 else transaction_date
remainder = match.group(date_groups + 1)
current = {
"transaction_date": transaction_date,
"value_date": value_date,
"lines": [remainder],
"source_page": page,
}
continue
stripped = line.strip()
if current and stripped and not _HEADER_RE.match(stripped):
current["lines"].append(stripped)
if current:
rows.append(current)
output: list[dict] = []
previous_balance = meta.opening_balance
for row in rows:
first_line = row["lines"][0]
full_text = norm(" ".join(row["lines"]))
debit, credit, balance, first_narration = _row_values(
first_line,
full_text,
previous_balance,
)
if balance is None:
continue
narration = norm(" ".join([first_narration, *row["lines"][1:]]))
if debit is None and credit is None and previous_balance is not None:
delta = round(balance - previous_balance, 2)
if delta < -0.01:
debit = abs(delta)
elif delta > 0.01:
credit = delta
if debit is None and credit is None:
continue
output.append(
{
"transaction_date": row["transaction_date"],
"value_date": row["value_date"],
"narration": narration,
"reference_no": _reference(full_text),
"debit": debit,
"credit": credit,
"balance": balance,
"source_page": row["source_page"],
}
)
previous_balance = balance
frame = pd.DataFrame(output)
if not frame.empty:
if meta.opening_balance is None:
first = output[0]
meta.opening_balance = round(
float(first["balance"]) + float(first.get("debit") or 0) - float(first.get("credit") or 0),
2,
)
meta.closing_balance = float(output[-1]["balance"])
meta.total_debit = round(float(frame["debit"].fillna(0).sum()), 2)
meta.total_credit = round(float(frame["credit"].fillna(0).sum()), 2)
return finalize(frame, meta)
class SBIYONORelationshipParser(BaseParser):
bank_name = "State Bank of India"
parser_name = "SBIYONORelationshipParser"
@classmethod
def detect(cls,text):
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
def detect(cls, text: str) -> float:
upper = norm(text).upper()
markers = (
"RELATIONSHIP SUMMARY",
"STATEMENT OF ACCOUNT",
"VALUE DATE",
"POST DATE",
"STATEMENT SUMMARY",
)
score = sum(marker in upper for marker in markers)
return 0.995 if "STATE BANK OF INDIA" in upper and score >= 3 else 0.0
def parse(self, path, text=None):
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')
meta.customer_name=find(r'Account Name\s*:\s*([^\n]+)',text)
meta.account_number=find(r'Account Number\s*:?\s*([0-9X*]+)',text)
meta.ifsc=find(r'IFS Code\s*:?\s*([A-Z0-9]+)',text)
m=re.search(rf'Account Statement from\s*({DATE_TOKEN_PATTERN})\s+to\s+({DATE_TOKEN_PATTERN})', text, re.I)
if m:
meta.period_from=date_iso(m.group(1)); meta.period_to=date_iso(m.group(2))
m=re.search(r'Balance as on\s+[^\n]+\n',text,re.I)
date_re=re.compile(rf'^\s*({DATE_TOKEN_PATTERN})\s+({DATE_TOKEN_PATTERN})\s+(.*)$', re.I)
rows=[]; cur=None; page=1
for line in text.splitlines():
if '\f' in line: page += line.count('\f')
mm=date_re.match(line)
if mm:
if cur: rows.append(cur)
cur={'transaction_date':mm.group(1),'value_date':mm.group(2),'lines':[mm.group(3)],'source_page':page}
elif cur and line.strip() and not re.match(r'^(Txn Date|Account Statement|Account Name)',line.strip(),re.I): cur['lines'].append(line)
if cur: rows.append(cur)
out=[]
for r in rows:
first=r['lines'][0]; alltxt=norm(' '.join(r['lines']))
nums=list(re.finditer(r'(?<!\d)([\d,]+\.\d{2})(?!\d)',first))
if not nums: continue
bal=amount(nums[-1].group(1)); debit=credit=None
if len(nums)>=2:
txn=amount(nums[-2].group(1)); p=nums[-2].start()
# Based on header layout: Debit starts before Credit
if p < 55: debit=txn
else: credit=txn
narr=first[:nums[-2].start() if len(nums)>=2 else nums[-1].start()].strip()+' '+' '.join(x.strip() for x in r['lines'][1:])
ref=''; z=re.search(r'(?:UPI|NEFT|IMPS|RTGS)[/A-Z0-9-]{6,}',alltxt,re.I); ref=z.group(0) if z else ''
if debit is None and credit is None: continue
out.append({**r,'narration':norm(narr),'reference_no':ref,'debit':debit,'credit':credit,'balance':bal})
if out:
f=out[0]; meta.opening_balance=round((f['balance'] or 0)+(f.get('debit') or 0)-(f.get('credit') or 0),2); meta.closing_balance=out[-1]['balance']
return meta,finalize(pd.DataFrame(out),meta)
extracted_text = text or extract_text(path)
start_re = re.compile(
r"^\s*(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})\s+"
r"(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})\s+(.*)$",
re.I,
)
meta = _extract_common_meta(extracted_text, path, self.parser_name)
meta.opening_balance = _opening_from_summary(extracted_text)
frame = _parse_rows(extracted_text, meta, start_re, 2)
expected = _expected_summary_transactions(extracted_text)
# The shared OCR path is sufficient for detection, but dense YONO tables
# occasionally need a table-oriented OCR pass. Retry only when the bank's
# printed debit/credit counts prove that rows were missed.
if expected and len(frame) < max(1, int(expected * 0.95)):
try:
table_text = _extract_yono_table_text(path)
retry_meta = _extract_common_meta(table_text, path, self.parser_name)
retry_meta.opening_balance = _opening_from_summary(table_text)
retry_frame = _parse_rows(table_text, retry_meta, start_re, 2)
if len(retry_frame) > len(frame):
meta, frame = retry_meta, retry_frame
except (OSError, RuntimeError, subprocess.SubprocessError):
# Preserve the already extracted result when the optional targeted
# retry is unavailable; the common OCR failure handling remains
# unchanged.
pass
return meta, frame
class SBIStandardParser(BaseParser):
bank_name = "State Bank of India"
parser_name = "SBIStandardParser"
@classmethod
def detect(cls, text: str) -> float:
upper = norm(text).upper()
if "STATE BANK OF INDIA" not in upper and "ACCOUNT STATEMENT FROM" not in upper:
return 0.0
has_table = (
"TXN DATE" in upper
and "DESCRIPTION" in upper
and "REF NO./CHEQUE" in upper
and "DEBIT" in upper
and "CREDIT" in upper
and "BALANCE" in upper
and ("VALUE DATE" in upper or "TXN DATE VALUE DESCRIPTION" in upper)
)
return 0.99 if has_table else 0.0
def parse(self, path, text=None):
text = text or extract_text(path)
meta = _extract_common_meta(text, path, self.parser_name)
meta.opening_balance = _opening_from_summary(text)
start_re = re.compile(
rf"^\s*({DATE_TOKEN_PATTERN})\s+({DATE_TOKEN_PATTERN})\s+(.*)$",
re.I,
)
return meta, _parse_rows(text, meta, start_re, 2)
class SBICompactParser(BaseParser):
bank_name = "State Bank of India"
parser_name = "SBICompactParser"
@classmethod
def detect(cls, text: str) -> float:
upper = norm(text).upper()
markers = ("STATE BANK OF INDIA", "DATE DETAILS", "REF NO./CHEQUE", "SEARCH FOR")
return 0.985 if all(marker in upper for marker in markers) else 0.0
def parse(self, path, text=None):
text = text or extract_text(path)
meta = _extract_common_meta(text, path, self.parser_name)
meta.opening_balance = _opening_from_summary(text)
start_re = re.compile(rf"^\s*({DATE_TOKEN_PATTERN})\s+(.*)$", re.I)
return meta, _parse_rows(text, meta, start_re, 1)
# Backward-compatible names retained because the production registry and any
# external imports may still refer to these classes.
SBIModernParser = SBICompactParser
SBIOtherParser = SBIStandardParser