kbt-devops
fe76bc7629
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.
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
from typing import List
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from fastapi import APIRouter, Depends, Query
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from app.models.schemas import DashboardSummary, ArbitrageOpportunity, PriceData, BatteryState
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from app.services import DataService
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router = APIRouter()
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data_service = DataService()
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@router.on_event("startup")
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async def startup():
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await data_service.initialize()
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@router.get("/summary", response_model=DashboardSummary)
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async def get_summary():
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summary = data_service.get_dashboard_summary()
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return DashboardSummary(**summary)
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@router.get("/prices")
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async def get_latest_prices():
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return {"regions": data_service.get_latest_prices()}
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@router.get("/prices/history")
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async def get_price_history(
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region: str = Query(..., description="Region code (FR, BE, DE, NL, UK)"),
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start: str = Query(None, description="Start date (YYYY-MM-DD)"),
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end: str = Query(None, description="End date (YYYY-MM-DD)"),
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limit: int = Query(1000, description="Maximum number of records"),
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):
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data = data_service.get_price_history(region, start, end, limit)
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return {"region": region, "data": data}
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@router.get("/battery")
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async def get_battery_states():
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batteries = data_service.get_battery_states()
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return {"batteries": batteries}
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@router.get("/arbitrage")
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async def get_arbitrage_opportunities(
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min_spread: float = Query(None, description="Minimum spread in EUR/MWh")
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):
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opportunities = data_service.get_arbitrage_opportunities(min_spread)
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return {"opportunities": opportunities, "count": len(opportunities)}
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