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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CLAUDE.md
99
CLAUDE.md
@@ -32,8 +32,9 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
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### Key Architectural Decisions
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- **Shared Database Pool**: Singleton `OraclePool` in `shared/database/oracle_pool.py` (python-oracledb with connection pooling)
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- **Centralized Auth**: JWT-based auth in `shared/auth/` with middleware auto-injecting `request.state.user`
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- **Two-Tier Cache System**: Hybrid L1 (Memory) + L2 (SQLite) cache in `backend/app/cache/` - **MANDATORY for all new endpoints**
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- **SSH Tunnel**: Required for Oracle DB connections (development/Linux) - see Database Setup
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- **FastAPI Structure**: Routers in `backend/app/routers/`, schemas in `backend/app/schemas/`, Oracle stored procedures (no ORM)
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- **FastAPI Structure**: Services in `backend/app/services/` with `@cached` decorator, routers in `backend/app/routers/`, models in `backend/app/models/` or `schemas/`
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- **Telegram Bot**: Standalone SQLite database for bot data, communicates with backend via HTTP API
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---
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@@ -91,22 +92,92 @@ TELEGRAM_BOT_INTERNAL_API=http://localhost:8002
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## 📝 Common Development Tasks
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### Adding a New API Endpoint
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1. Create router in `reports-app/backend/app/routers/your_router.py`
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2. Define Pydantic schemas in `app/schemas/`
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3. Use `oracle_pool.get_connection()` context manager for DB queries
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4. Register router in `app/main.py`: `app.include_router(your_router, prefix="/api/your_prefix")`
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**IMPORTANT**: Always use the cache system for database queries to improve performance.
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**Example**:
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1. Create **service** in `reports-app/backend/app/services/your_service.py` (NOT in router!)
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2. Define Pydantic schemas in `app/schemas/` or `app/models/`
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3. **Add caching** using `@cached` decorator in service methods
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4. Create router in `reports-app/backend/app/routers/your_router.py` (calls service)
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5. Register router in `app/main.py`: `app.include_router(your_router, prefix="/api/your_prefix")`
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**Service Example with Caching** (RECOMMENDED):
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```python
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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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cursor.execute("""
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SELECT pack_name.procedure_name(:param1, :param2)
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FROM DUAL
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""", {'param1': value1, 'param2': value2})
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result = cursor.fetchone()
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# app/services/your_service.py
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from app.cache.decorators import cached
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from database.oracle_pool import oracle_pool
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class YourService:
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@staticmethod
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@cached(cache_type='schema', key_params=['company_id'])
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async def _get_schema(company_id: int) -> str:
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"""Get schema for company (CACHED 24h)"""
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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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cursor.execute("""
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SELECT schema FROM CONTAFIN_ORACLE.v_nom_firme
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WHERE id_firma = :company_id
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""", {'company_id': company_id})
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result = cursor.fetchone()
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return result[0] if result else None
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@staticmethod
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@cached(cache_type='your_data', key_params=['filter_params', 'username'])
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async def get_your_data(filter_params: YourFilter, username: str) -> YourResponse:
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"""
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Get your data from Oracle (CACHED 10 min)
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Cache automatically:
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- Generates unique key from filter_params + username
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- Stores in L1 (memory) + L2 (SQLite)
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- Returns cached data on subsequent calls
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- Tracks performance metrics
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"""
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schema = await YourService._get_schema(filter_params.company_id)
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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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cursor.execute(f"""
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SELECT * FROM {schema}.your_table
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WHERE your_condition = :param
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""", {'param': filter_params.param})
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rows = cursor.fetchall()
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# Process results...
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return YourResponse(data=processed_data)
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```
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**Router Example** (calls service):
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```python
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# app/routers/your_router.py
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from app.services.your_service import YourService
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@router.get("/", response_model=YourResponse)
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async def get_your_data(
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filter_params: YourFilter = Depends(),
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current_user: CurrentUser = Depends(get_current_user)
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):
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"""Get your data - delegated to service with caching"""
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return await YourService.get_your_data(filter_params, current_user.username)
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```
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**Cache Configuration** (add to `app/cache/config.py` if new cache type):
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```python
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# Add TTL for your cache type
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ttl_your_data: int = int(os.getenv('CACHE_TTL_YOUR_DATA', '600')) # 10 min default
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# Add to get_ttl_for_type() method:
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'your_data': self.ttl_your_data,
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```
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**Cache Best Practices**:
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- ✅ Use `@cached` decorator for ALL database queries
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- ✅ Place logic in services (NOT routers)
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- ✅ Cache schema lookups separately (long TTL: 24h)
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- ✅ Choose appropriate TTL (frequently changing data: 5-10 min, static data: 30 min - 24h)
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- ✅ Include `username` in `key_params` for user-specific data
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- ✅ Include filter parameters in `key_params` for query variations
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- ❌ Don't query Oracle directly in routers (use services with caching)
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- ❌ Don't skip caching for performance-critical endpoints
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### Adding a New Frontend Page/Component
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**IMPORTANT**: Follow the established CSS architecture and design system.
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@@ -181,7 +252,7 @@ const response = await api.get('/endpoint');
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→ **`README.md`** - Project overview, setup, development commands, testing, deployment
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### Architecture & Planning
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- `docs/ARCHITECTURE_SCHEMA.md` - Architecture diagrams and schemas
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- **`docs/ARCHITECTURE_SCHEMA.md`** - Architecture diagrams, cache system, and schemas
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- `docs/MICROSERVICES_GUIDE.md` - Microservices architecture details
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- `DEVELOPMENT_BLUEPRINT.md` - Detailed development plan
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