A R R R Associates
518 lines
18 KiB
Python
518 lines
18 KiB
Python
from __future__ import annotations
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import json
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import re
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from datetime import datetime, timezone
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from difflib import SequenceMatcher
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from sqlalchemy import delete, func, select
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from app.modules.accounting.opening_balance_models import (
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AccountingOpeningBalanceRun,
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AccountingOpeningLedgerItem,
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AccountingOpeningMasterMapping,
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AccountingOpeningStockItem,
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)
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def _utcnow():
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return datetime.now(timezone.utc)
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def _s(value):
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return str(value or "").strip()
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def _n(value):
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try:
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return float(value or 0)
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except Exception:
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return 0.0
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def _norm(value):
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return re.sub(r"[^a-z0-9]+", " ", _s(value).casefold()).strip()
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def _near(a, b, tolerance=0.01):
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return abs(float(a or 0) - float(b or 0)) <= tolerance
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def _mapping_index(db, *, tenant_id, client_id, master_type, previous_company_guid, current_company_guid):
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rows = list(
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db.execute(
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select(AccountingOpeningMasterMapping).where(
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AccountingOpeningMasterMapping.tenant_id == int(tenant_id),
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AccountingOpeningMasterMapping.client_id == int(client_id),
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AccountingOpeningMasterMapping.master_type == master_type,
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AccountingOpeningMasterMapping.previous_company_guid == _s(previous_company_guid),
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AccountingOpeningMasterMapping.current_company_guid == _s(current_company_guid),
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)
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).scalars().all()
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)
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return {row.previous_name_norm: row.current_name for row in rows}
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def save_master_mapping(
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db,
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*,
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tenant_id,
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client_id,
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master_type,
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previous_company_guid,
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previous_name,
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current_company_guid,
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current_name,
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user_id,
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note="",
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):
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master_type = _s(master_type).lower()
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if master_type not in {"ledger", "stock_item"}:
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raise ValueError("Master mapping type must be ledger or stock_item.")
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previous_norm = _norm(previous_name)
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if not previous_norm or not _s(current_name):
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raise ValueError("Both previous-year and current-year master names are required.")
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row = db.execute(
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select(AccountingOpeningMasterMapping).where(
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AccountingOpeningMasterMapping.tenant_id == int(tenant_id),
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AccountingOpeningMasterMapping.client_id == int(client_id),
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AccountingOpeningMasterMapping.master_type == master_type,
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AccountingOpeningMasterMapping.previous_company_guid == _s(previous_company_guid),
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AccountingOpeningMasterMapping.previous_name_norm == previous_norm,
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AccountingOpeningMasterMapping.current_company_guid == _s(current_company_guid),
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)
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).scalar_one_or_none()
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if row is None:
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row = AccountingOpeningMasterMapping(
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tenant_id=int(tenant_id),
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client_id=int(client_id),
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master_type=master_type,
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previous_company_guid=_s(previous_company_guid),
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previous_name=_s(previous_name),
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previous_name_norm=previous_norm,
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current_company_guid=_s(current_company_guid),
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current_name=_s(current_name),
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created_by_user_id=int(user_id),
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)
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else:
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row.previous_name = _s(previous_name)
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row.current_name = _s(current_name)
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row.note = _s(note)
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db.add(row)
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db.commit()
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return row
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def _match_ledgers(previous, current, learned):
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current_by_norm = {}
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for row in current:
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current_by_norm.setdefault(_norm(row.get("name")), []).append(row)
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used = set()
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result = []
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for py in previous:
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py_name = _s(py.get("name"))
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py_norm = _norm(py_name)
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target_name = learned.get(py_norm)
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match = None
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method = ""
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confidence = 0
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if target_name:
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candidates = [row for row in current if _s(row.get("name")).casefold() == target_name.casefold()]
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if len(candidates) == 1:
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match = candidates[0]
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method = "learned_mapping"
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confidence = 100
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if match is None:
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exact = current_by_norm.get(py_norm, [])
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if len(exact) == 1:
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match = exact[0]
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method = "exact_normalized_name"
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confidence = 98
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if match is not None:
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used.add(id(match))
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py_close = _n(py.get("closing_balance"))
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cy_open = _n(match.get("opening_balance"))
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diff = round(py_close - cy_open, 2)
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status = "matched" if _near(py_close, cy_open) else "difference"
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result.append({
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"previous": py, "current": match, "difference": diff,
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"status": status, "method": method, "confidence": confidence,
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})
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else:
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result.append({
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"previous": py, "current": None, "difference": _n(py.get("closing_balance")),
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"status": "missing_in_current_year", "method": "", "confidence": 0,
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})
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for cy in current:
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if id(cy) in used:
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continue
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result.append({
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"previous": None, "current": cy, "difference": -_n(cy.get("opening_balance")),
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"status": "new_in_current_year", "method": "", "confidence": 0,
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})
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return result
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def _stock_score(py, cy):
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py_name = _norm(py.get("name"))
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cy_name = _norm(cy.get("name"))
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score = int(round(SequenceMatcher(None, py_name, cy_name).ratio() * 60))
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py_hsn = _s(py.get("hsn_code"))
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cy_hsn = _s(cy.get("hsn_code"))
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if py_hsn and cy_hsn:
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if py_hsn == cy_hsn:
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score += 25
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elif py_hsn[:4] and py_hsn[:4] == cy_hsn[:4]:
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score += 12
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else:
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score -= 20
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if _norm(py.get("parent")) == _norm(cy.get("parent")) and _norm(py.get("parent")):
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score += 10
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if _norm(py.get("base_units")) == _norm(cy.get("base_units")) and _norm(py.get("base_units")):
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score += 10
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return max(0, min(100, score))
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def _match_stock(previous, current, learned):
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current_by_norm = {}
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for row in current:
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current_by_norm.setdefault(_norm(row.get("name")), []).append(row)
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used = set()
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result = []
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for py in previous:
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py_name = _s(py.get("name"))
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py_norm = _norm(py_name)
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match = None
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method = ""
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confidence = 0
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target_name = learned.get(py_norm)
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if target_name:
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candidates = [row for row in current if _s(row.get("name")).casefold() == target_name.casefold()]
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if len(candidates) == 1:
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match = candidates[0]
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method = "learned_mapping"
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confidence = 100
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if match is None:
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exact = current_by_norm.get(py_norm, [])
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if len(exact) == 1:
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match = exact[0]
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method = "exact_normalized_name"
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confidence = 98
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if match is None:
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scored = sorted(
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[(_stock_score(py, cy), cy) for cy in current if id(cy) not in used],
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key=lambda row: (-row[0], _s(row[1].get("name"))),
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)
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if scored:
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top = scored[0][0]
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second = scored[1][0] if len(scored) > 1 else 0
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if top >= 90 and top - second >= 10:
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match = scored[0][1]
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method = "unique_hsn_name_match"
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confidence = top
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if match is None:
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result.append({
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"previous": py, "current": None,
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"qty_difference": _n(py.get("closing_balance")),
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"value_difference": _n(py.get("closing_value")),
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"status": "missing_in_current_year", "method": "", "confidence": 0,
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})
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continue
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used.add(id(match))
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py_qty = _n(py.get("closing_balance"))
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py_val = _n(py.get("closing_value"))
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cy_qty = _n(match.get("opening_balance"))
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cy_val = _n(match.get("opening_value"))
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qty_diff = round(py_qty - cy_qty, 6)
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val_diff = round(py_val - cy_val, 2)
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py_unit = _norm(py.get("base_units"))
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cy_unit = _norm(match.get("base_units"))
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if py_unit and cy_unit and py_unit != cy_unit:
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status = "unit_difference"
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elif _near(py_qty, cy_qty, 0.000001) and _near(py_val, cy_val):
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status = "matched"
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elif not _near(py_qty, cy_qty, 0.000001) and not _near(py_val, cy_val):
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status = "quantity_and_value_difference"
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elif not _near(py_qty, cy_qty, 0.000001):
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status = "quantity_difference"
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else:
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status = "value_difference"
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result.append({
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"previous": py, "current": match,
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"qty_difference": qty_diff, "value_difference": val_diff,
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"status": status, "method": method, "confidence": confidence,
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})
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for cy in current:
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if id(cy) in used:
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continue
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result.append({
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"previous": None, "current": cy,
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"qty_difference": -_n(cy.get("opening_balance")),
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"value_difference": -_n(cy.get("opening_value")),
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"status": "new_in_current_year", "method": "", "confidence": 0,
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})
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return result
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def create_comparison_run(
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db,
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*,
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tenant_id,
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client_id,
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previous_company,
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current_company,
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previous_masters,
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current_masters,
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user_id,
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):
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py_guid = _s(previous_company.get("guid"))
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cy_guid = _s(current_company.get("guid"))
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ledger_map = _mapping_index(
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db,
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tenant_id=tenant_id,
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client_id=client_id,
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master_type="ledger",
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previous_company_guid=py_guid,
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current_company_guid=cy_guid,
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)
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stock_map = _mapping_index(
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db,
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tenant_id=tenant_id,
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client_id=client_id,
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master_type="stock_item",
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previous_company_guid=py_guid,
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current_company_guid=cy_guid,
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)
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ledger_matches = _match_ledgers(
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list(previous_masters.get("ledgers") or []),
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list(current_masters.get("ledgers") or []),
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ledger_map,
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)
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stock_matches = _match_stock(
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list(previous_masters.get("stock_items") or []),
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list(current_masters.get("stock_items") or []),
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stock_map,
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)
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run = AccountingOpeningBalanceRun(
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tenant_id=int(tenant_id),
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client_id=int(client_id),
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previous_company_name=_s(previous_company.get("name")),
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previous_company_guid=py_guid,
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current_company_name=_s(current_company.get("name")),
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current_company_guid=cy_guid,
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status="completed",
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ledger_count=len(ledger_matches),
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stock_item_count=len(stock_matches),
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created_by_user_id=int(user_id),
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)
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db.add(run)
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db.flush()
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for row in ledger_matches:
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py = row["previous"] or {}
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cy = row["current"] or {}
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db.add(
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AccountingOpeningLedgerItem(
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run_id=run.id,
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previous_name=_s(py.get("name")),
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previous_guid=_s(py.get("guid")),
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previous_group=_s(py.get("parent")),
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previous_closing_balance=_n(py.get("closing_balance")),
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current_name=_s(cy.get("name")),
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current_guid=_s(cy.get("guid")),
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current_group=_s(cy.get("parent")),
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current_opening_balance=_n(cy.get("opening_balance")),
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difference=float(row["difference"]),
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match_status=row["status"],
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match_method=row["method"],
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confidence=int(row["confidence"]),
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)
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)
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for row in stock_matches:
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py = row["previous"] or {}
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cy = row["current"] or {}
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db.add(
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AccountingOpeningStockItem(
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run_id=run.id,
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previous_name=_s(py.get("name")),
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previous_guid=_s(py.get("guid")),
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previous_group=_s(py.get("parent")),
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previous_hsn=_s(py.get("hsn_code")),
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previous_unit=_s(py.get("base_units")),
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previous_closing_qty=_n(py.get("closing_balance")),
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previous_closing_value=_n(py.get("closing_value")),
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previous_closing_rate=_s(py.get("closing_rate")),
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current_name=_s(cy.get("name")),
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current_guid=_s(cy.get("guid")),
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current_group=_s(cy.get("parent")),
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current_hsn=_s(cy.get("hsn_code")),
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current_unit=_s(cy.get("base_units")),
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current_opening_qty=_n(cy.get("opening_balance")),
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current_opening_value=_n(cy.get("opening_value")),
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quantity_difference=float(row["qty_difference"]),
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value_difference=float(row["value_difference"]),
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match_status=row["status"],
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match_method=row["method"],
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confidence=int(row["confidence"]),
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)
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)
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summary = {
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"ledgers": {},
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"stock_items": {},
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}
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for key in {
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"matched", "difference", "missing_in_current_year", "new_in_current_year"
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}:
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summary["ledgers"][key] = sum(1 for row in ledger_matches if row["status"] == key)
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for key in {
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"matched", "quantity_difference", "value_difference",
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"quantity_and_value_difference", "unit_difference",
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"missing_in_current_year", "new_in_current_year",
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}:
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summary["stock_items"][key] = sum(1 for row in stock_matches if row["status"] == key)
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run.summary_json = json.dumps(summary, ensure_ascii=False)
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db.add(run)
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db.commit()
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db.refresh(run)
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return run
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def list_runs(db, *, tenant_id, client_id, limit=30):
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return list(
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db.execute(
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select(AccountingOpeningBalanceRun)
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.where(
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AccountingOpeningBalanceRun.tenant_id == int(tenant_id),
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AccountingOpeningBalanceRun.client_id == int(client_id),
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)
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.order_by(AccountingOpeningBalanceRun.id.desc())
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.limit(limit)
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).scalars().all()
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)
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def ledger_items(db, *, run_id, status=""):
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stmt = select(AccountingOpeningLedgerItem).where(
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AccountingOpeningLedgerItem.run_id == int(run_id)
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)
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if _s(status):
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stmt = stmt.where(AccountingOpeningLedgerItem.match_status == _s(status))
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return list(db.execute(stmt.order_by(AccountingOpeningLedgerItem.previous_name, AccountingOpeningLedgerItem.current_name)).scalars().all())
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def stock_items(db, *, run_id, status=""):
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stmt = select(AccountingOpeningStockItem).where(
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AccountingOpeningStockItem.run_id == int(run_id)
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)
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if _s(status):
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stmt = stmt.where(AccountingOpeningStockItem.match_status == _s(status))
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return list(db.execute(stmt.order_by(AccountingOpeningStockItem.previous_name, AccountingOpeningStockItem.current_name)).scalars().all())
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def correction_payload(db, *, run, ledger_ids, stock_ids):
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ledger_rows = []
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stock_rows = []
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for row in db.execute(
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select(AccountingOpeningLedgerItem).where(
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AccountingOpeningLedgerItem.run_id == run.id,
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AccountingOpeningLedgerItem.id.in_([int(x) for x in ledger_ids] or [-1]),
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)
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).scalars().all():
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if row.match_status != "difference" or not row.current_name:
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continue
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ledger_rows.append({
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"item_id": row.id,
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"name": row.current_name,
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"guid": row.current_guid,
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"expected_opening": row.current_opening_balance,
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"target_opening": row.previous_closing_balance,
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})
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for row in db.execute(
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select(AccountingOpeningStockItem).where(
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AccountingOpeningStockItem.run_id == run.id,
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AccountingOpeningStockItem.id.in_([int(x) for x in stock_ids] or [-1]),
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)
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).scalars().all():
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if row.match_status not in {
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"quantity_difference", "value_difference", "quantity_and_value_difference"
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}:
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continue
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if not row.current_name or _norm(row.previous_unit) != _norm(row.current_unit):
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continue
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qty = row.previous_closing_qty
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value = row.previous_closing_value
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rate = abs(value / qty) if abs(qty) > 0.0000001 else 0
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stock_rows.append({
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"item_id": row.id,
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"name": row.current_name,
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"guid": row.current_guid,
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"unit": row.current_unit or row.previous_unit,
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"expected_opening_qty": row.current_opening_qty,
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"expected_opening_value": row.current_opening_value,
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"target_opening_qty": qty,
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"target_opening_value": value,
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"target_opening_rate": rate,
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})
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return ledger_rows, stock_rows
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def apply_correction_results(db, *, run_id, result, user_id):
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now = _utcnow()
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for row in result.get("ledgers") or []:
|
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item = db.get(AccountingOpeningLedgerItem, int(row.get("item_id") or 0))
|
|
if not item or item.run_id != int(run_id):
|
|
continue
|
|
item.correction_status = "verified" if row.get("verified") else "failed"
|
|
item.correction_note = _s(row.get("message"))
|
|
item.verified_opening_balance = _n(row.get("verified_opening"))
|
|
item.corrected_by_user_id = int(user_id)
|
|
item.corrected_at_utc = now
|
|
db.add(item)
|
|
|
|
for row in result.get("stock_items") or []:
|
|
item = db.get(AccountingOpeningStockItem, int(row.get("item_id") or 0))
|
|
if not item or item.run_id != int(run_id):
|
|
continue
|
|
item.correction_status = "verified" if row.get("verified") else "failed"
|
|
item.correction_note = _s(row.get("message"))
|
|
item.verified_opening_qty = _n(row.get("verified_opening_qty"))
|
|
item.verified_opening_value = _n(row.get("verified_opening_value"))
|
|
item.corrected_by_user_id = int(user_id)
|
|
item.corrected_at_utc = now
|
|
db.add(item)
|
|
|
|
db.commit()
|