Add FastAPI backend for energy trading system

Implements FastAPI backend with ML model support for energy trading,
including price prediction models and RL-based battery trading policy.
Features dashboard, trading, backtest, and settings API routes with
WebSocket support for real-time updates.

backend/app/api/routes/dashboard.py

@@ -0,0 +1,48 @@
+from typing import List
+from fastapi import APIRouter, Depends, Query
+from app.models.schemas import DashboardSummary, ArbitrageOpportunity, PriceData, BatteryState
+from app.services import DataService
+
+router = APIRouter()
+data_service = DataService()
+
+
+@router.on_event("startup")
+async def startup():
+    await data_service.initialize()
+
+
+@router.get("/summary", response_model=DashboardSummary)
+async def get_summary():
+    summary = data_service.get_dashboard_summary()
+    return DashboardSummary(**summary)
+
+
+@router.get("/prices")
+async def get_latest_prices():
+    return {"regions": data_service.get_latest_prices()}
+
+
+@router.get("/prices/history")
+async def get_price_history(
+    region: str = Query(..., description="Region code (FR, BE, DE, NL, UK)"),
+    start: str = Query(None, description="Start date (YYYY-MM-DD)"),
+    end: str = Query(None, description="End date (YYYY-MM-DD)"),
+    limit: int = Query(1000, description="Maximum number of records"),
+):
+    data = data_service.get_price_history(region, start, end, limit)
+    return {"region": region, "data": data}
+
+
+@router.get("/battery")
+async def get_battery_states():
+    batteries = data_service.get_battery_states()
+    return {"batteries": batteries}
+
+
+@router.get("/arbitrage")
+async def get_arbitrage_opportunities(
+    min_spread: float = Query(None, description="Minimum spread in EUR/MWh")
+):
+    opportunities = data_service.get_arbitrage_opportunities(min_spread)
+    return {"opportunities": opportunities, "count": len(opportunities)}