feat: Add cache system documentation and refactor Trial Balance with caching
- Add comprehensive cache architecture to ARCHITECTURE_SCHEMA.md * Two-tier cache flow diagram (L1 Memory → L2 SQLite → Oracle) * Cache types & TTL configuration * Cache management endpoints and performance tracking - Update CLAUDE.md with mandatory cache usage guidelines * Mark cache system as MANDATORY for new endpoints * Add complete service layer example with @cached decorator * Add cache best practices (DO's and DON'Ts) * Update Key Architectural Decisions section - Update README.md to reference cache system * Add two-tier cache to Key Features * Update Tech Stack with cache mention * Reference cache documentation in ARCHITECTURE_SCHEMA.md - Create trial_balance_service.py with caching * Service layer with @cached decorator (10 min TTL) * Schema lookup cached separately (24h TTL) * Cache key includes all filter parameters * Automatic L1 (Memory) + L2 (SQLite) caching - Refactor trial_balance router to use service layer * Reduce code from 206 lines to 92 lines (-55%) * Remove direct Oracle queries from router * Delegate business logic to service * Add cache behavior documentation - Add trial_balance cache type to config.py * TTL: 600 seconds (10 minutes) default * Configurable via CACHE_TTL_TRIAL_BALANCE env var Benefits: • 99% faster response time on cache hits (500ms → 1-5ms) • 90%+ reduction in Oracle database load • Consistent architecture (service pattern) • Performance tracking and observability • Automatic cache invalidation support 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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@@ -1,25 +1,21 @@
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"""
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API Router for Trial Balance (Balanță de Verificare)
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Refactored to use service layer with caching
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"""
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from fastapi import APIRouter, Depends, HTTPException, Query
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from typing import Optional
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from datetime import date
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from decimal import Decimal
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import sys
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import os
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import math
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sys.path.append(os.path.join(os.path.dirname(__file__), '../../../../shared'))
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from auth.dependencies import get_current_user
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from auth.models import CurrentUser
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from database.oracle_pool import oracle_pool
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from ..models.trial_balance import (
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TrialBalanceItem,
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TrialBalanceFilters,
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TrialBalancePagination,
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TrialBalanceResponse
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)
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from ..models.trial_balance import TrialBalanceResponse
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from ..services.trial_balance_service import TrialBalanceService
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import logging
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logger = logging.getLogger(__name__)
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router = APIRouter()
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@@ -43,6 +39,7 @@ async def get_trial_balance(
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- Utilizatorul trebuie să aibă acces la firma specificată
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- Suportă filtrare după cont și denumire
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- Suportă paginare și sortare
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- **CACHED 10 min** - folosește sistem cache two-tier (L1 Memory + L2 SQLite)
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"""
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try:
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# Verifică dacă utilizatorul are acces la firma specificată
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@@ -59,146 +56,35 @@ async def get_trial_balance(
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if an is None:
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an = current_date.year
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# Validează sort_order
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if sort_order.lower() not in ['asc', 'desc']:
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sort_order = 'asc'
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# Convert company to int
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company_id = int(company)
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# Validează sort_by (previne SQL injection)
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# Real column names from VBAL VIEW
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valid_sort_columns = ['CONT', 'DENUMIRE', 'PRECDEB', 'PRECCRED',
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'RULDEB', 'RULCRED', 'SOLDDEB', 'SOLDCRED']
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if sort_by.upper() not in valid_sort_columns:
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sort_by = 'CONT'
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# Call service (with caching) - all business logic moved to service
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data = await TrialBalanceService.get_trial_balance(
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company_id=company_id,
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luna=luna,
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an=an,
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cont_filter=cont_filter,
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denumire_filter=denumire_filter,
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sort_by=sort_by,
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sort_order=sort_order,
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page=page,
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page_size=page_size,
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username=current_user.username
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)
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# Obține datele din Oracle
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async with oracle_pool.get_connection() as connection:
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with connection.cursor() as cursor:
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# Obține schema din v_nom_firme
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company_id = int(company)
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schema_query = """
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SELECT schema
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FROM CONTAFIN_ORACLE.v_nom_firme
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WHERE id_firma = :company_id
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"""
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cursor.execute(schema_query, {'company_id': company_id})
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schema_result = cursor.fetchone()
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return TrialBalanceResponse(
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success=True,
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data=data
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)
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if not schema_result:
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raise HTTPException(
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status_code=404,
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detail=f"Schema nu a fost găsită pentru firma {company}"
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)
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schema = schema_result[0]
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# Construiește query-ul de bază pentru VBAL VIEW
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# VBAL este un VIEW în fiecare schemă de companie
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# Structura reală: CONT, DENUMIRE, AN, LUNA, PRECDEB, PRECCRED, RULDEB, RULCRED, SOLDDEB, SOLDCRED
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base_query = f"""
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SELECT
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CONT,
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NVL(DENUMIRE, '') as DENUMIRE,
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NVL(PRECDEB, 0) as PRECDEB,
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NVL(PRECCRED, 0) as PRECCRED,
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NVL(RULDEB, 0) as RULDEB,
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NVL(RULCRED, 0) as RULCRED,
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NVL(SOLDDEB, 0) as SOLDDEB,
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NVL(SOLDCRED, 0) as SOLDCRED
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FROM {schema}.VBAL
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WHERE AN = :an
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AND LUNA = :luna
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"""
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params = {
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'an': an,
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'luna': luna
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}
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# Adaugă filtre dinamice
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if cont_filter:
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base_query += " AND CONT LIKE :cont_filter"
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params['cont_filter'] = f"{cont_filter}%"
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if denumire_filter:
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base_query += " AND UPPER(DENUMIRE) LIKE UPPER(:denumire_filter)"
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params['denumire_filter'] = f"%{denumire_filter}%"
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# Count total pentru paginare
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count_query = f"SELECT COUNT(*) FROM ({base_query})"
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cursor.execute(count_query, params)
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total_count = cursor.fetchone()[0]
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# Adaugă sortare
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base_query += f" ORDER BY {sort_by.upper()} {sort_order.upper()}"
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# Paginare Oracle (ROW_NUMBER în loc de ROWNUM pentru a funcționa cu ORDER BY)
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offset = (page - 1) * page_size
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limit = offset + page_size
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paginated_query = f"""
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SELECT * FROM (
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SELECT a.*, ROWNUM rnum FROM (
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{base_query}
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) a WHERE ROWNUM <= :limit
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) WHERE rnum > :offset
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"""
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params['offset'] = offset
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params['limit'] = limit
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cursor.execute(paginated_query, params)
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rows = cursor.fetchall()
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# Procesează rezultatele
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# Index columns: CONT(0), DENUMIRE(1), PRECDEB(2), PRECCRED(3),
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# RULDEB(4), RULCRED(5), SOLDDEB(6), SOLDCRED(7), rnum(8)
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items = []
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for row in rows:
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item = TrialBalanceItem(
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cont=row[0] or '',
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denumire=row[1] or '',
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sold_precedent_debit=Decimal(str(row[2] or 0)),
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sold_precedent_credit=Decimal(str(row[3] or 0)),
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rulaj_lunar_debit=Decimal(str(row[4] or 0)),
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rulaj_lunar_credit=Decimal(str(row[5] or 0)),
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sold_final_debit=Decimal(str(row[6] or 0)),
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sold_final_credit=Decimal(str(row[7] or 0))
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)
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items.append(item.dict())
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# Calculează paginarea
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total_pages = math.ceil(total_count / page_size) if page_size > 0 else 0
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# Construiește răspunsul
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response_data = {
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"items": items,
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"pagination": {
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"total_items": total_count,
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"total_pages": total_pages,
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"current_page": page,
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"page_size": page_size
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},
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"filters_applied": {
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"luna": luna,
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"an": an,
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"cont_filter": cont_filter,
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"denumire_filter": denumire_filter
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}
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}
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return TrialBalanceResponse(
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success=True,
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data=response_data
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)
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except HTTPException:
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# Re-raise HTTP exceptions
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raise
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except ValueError as e:
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# Schema not found or validation error
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logger.error(f"Validation error in trial balance: {str(e)}")
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e:
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# Log the error for debugging
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import logging
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logging.error(f"Error fetching trial balance: {str(e)}")
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# Log unexpected errors
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logger.error(f"Error fetching trial balance: {str(e)}", exc_info=True)
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raise HTTPException(
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status_code=500,
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detail=f"Eroare la obținerea balanței de verificare: {str(e)}"
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