feat: Add Phase 4 advanced metrics and components
- Add advanced metrics dashboard with trade analytics - Add new trading components (EntryTypeAnalysis, MultiDayPositionTracker, NewsEventTracker, etc.) - Add strategy mode selector and trend confirmation - Add risk automation panel and slippage correlation analysis - Add daily trading plan enhancements with modal components - Add custom hooks (useApi, useLocalStorage, useAdvancedTradeMetrics) - Add broker service integration and trading API - Add test setup and vitest configuration - Include parquet data files for live market data - Add comprehensive documentation in docs/ folder
This commit is contained in:
Krikorios
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from fastapi import APIRouter, HTTPException, Depends
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from sqlalchemy.orm import Session, selectinload
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from typing import Dict, Optional, Any, List
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from datetime import datetime, timezone
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from app.db.database import get_db
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from app.models.models import Simulation, Trade, Position, TradeAction, TradeMetadata
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from app.services.risk import validate_order
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from pydantic import BaseModel
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router = APIRouter(prefix="/trading", tags=["Trading"])
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# Pydantic models for request/response
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class TradeRequest(BaseModel):
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action: str
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quantity: float
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price: float
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symbol: str = "XAU/USD"
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notes: Optional[str] = None
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stop_loss: Optional[float] = None
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take_profit: Optional[float] = None
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source: Optional[str] = None
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platform: Optional[str] = None
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risk_percent: Optional[float] = None
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entry_time: Optional[str] = None
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class PortfolioState(BaseModel):
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cash: float
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initial_capital: float
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position: Optional[Dict[str, Any]] = None
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trades: List[Dict[str, Any]]
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equity_history: List[Dict[str, Any]]
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total_pnl: float
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total_pnl_percent: float
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def get_or_create_simulation(db: Session, user_id: str = "default") -> Simulation:
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"""Get existing simulation or create a new one"""
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simulation = db.query(Simulation).filter(Simulation.user_id == user_id).first()
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if not simulation:
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simulation = Simulation(
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user_id=user_id,
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symbol="XAU/USD",
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initial_capital=100000.0,
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current_capital=100000.0,
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total_pnl=0.0,
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total_pnl_percent=0.0
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)
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db.add(simulation)
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db.commit()
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db.refresh(simulation)
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return simulation
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def _compute_equity_at_price(simulation: Simulation, price: float, db: Session) -> float:
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"""Calculate equity based on current position and price"""
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position = db.query(Position).filter(
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Position.simulation_id == simulation.id
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).first()
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qty = position.quantity if position else 0.0
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return float(simulation.current_capital + qty * price)
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def get_portfolio_state_from_db(simulation: Simulation, db: Session) -> PortfolioState:
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"""Convert DB simulation to portfolio state"""
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# Get current position
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position = db.query(Position).filter(
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Position.simulation_id == simulation.id
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).first()
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position_dict = None
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if position:
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position_dict = {
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"symbol": position.symbol,
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"quantity": position.quantity,
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"avg_price": position.avg_price,
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"current_price": position.current_price,
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"unrealized_pnl": position.unrealized_pnl,
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"unrealized_pnl_percent": position.unrealized_pnl_percent
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}
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# Get all trades
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trades = db.query(Trade).options(selectinload(Trade.details)).filter(
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Trade.simulation_id == simulation.id
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).order_by(Trade.timestamp).all()
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trades_list = []
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for trade in trades:
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details = trade.details
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trades_list.append({
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"id": trade.id,
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"action": trade.action.value,
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"quantity": trade.quantity,
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"price": trade.price,
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"total": trade.total,
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"pnl": trade.pnl,
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"timestamp": int(trade.timestamp.timestamp()) if trade.timestamp else None,
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"stop_loss": details.stop_loss if details else None,
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"take_profit": details.take_profit if details else None,
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"notes": details.notes if details else None,
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"source": details.source if details else None,
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"platform": details.platform if details else None,
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"risk_percent": details.risk_percent if details else None,
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"entry_time": details.entry_time.isoformat() if details and details.entry_time else None,
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})
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# Build equity history from trades
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equity_history = []
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running_equity = simulation.initial_capital
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for trade in trades:
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if trade.action == TradeAction.SELL and trade.pnl:
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running_equity += trade.pnl
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equity_history.append({
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"time": int(trade.timestamp.timestamp()) if trade.timestamp else 0,
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"equity": running_equity
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})
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return PortfolioState(
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cash=simulation.current_capital,
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initial_capital=simulation.initial_capital,
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position=position_dict,
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trades=trades_list,
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equity_history=equity_history,
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total_pnl=simulation.total_pnl,
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total_pnl_percent=simulation.total_pnl_percent
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)
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@router.post("/execute")
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async def execute_trade(
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trade_request: TradeRequest,
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db: Session = Depends(get_db),
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user_id: str = "default"
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):
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"""
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Execute a trade and persist to database.
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- Validates risk rules
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- Updates cash/position in DB
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- Records trade with timestamp
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- Returns updated portfolio state
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"""
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try:
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action = trade_request.action.upper()
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quantity = trade_request.quantity
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price = trade_request.price
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if action not in ["BUY", "SELL"]:
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raise HTTPException(status_code=400, detail="Action must be BUY or SELL")
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# Get or create simulation
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simulation = get_or_create_simulation(db, user_id)
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# Build state dict for risk validation
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position = db.query(Position).filter(
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Position.simulation_id == simulation.id
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).first()
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state_dict = {
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"cash": simulation.current_capital,
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"position": {
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"quantity": position.quantity,
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"avg_price": position.avg_price
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} if position else None
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}
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# Risk validation
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try:
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validate_order(state_dict, action, quantity, price)
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except ValueError as ve:
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raise HTTPException(status_code=400, detail=str(ve))
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total = quantity * price
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pnl = None
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if action == "BUY":
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if total > simulation.current_capital:
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raise HTTPException(status_code=400, detail="Insufficient funds")
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simulation.current_capital -= total
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if not position:
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# Create new position
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position = Position(
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simulation_id=simulation.id,
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symbol=trade_request.symbol,
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quantity=quantity,
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avg_price=price,
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current_price=price,
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unrealized_pnl=0.0,
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unrealized_pnl_percent=0.0
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)
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db.add(position)
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else:
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# Update existing position (average up)
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new_qty = position.quantity + quantity
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new_avg = (position.avg_price * position.quantity + price * quantity) / new_qty
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position.quantity = new_qty
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position.avg_price = new_avg
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position.current_price = price
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elif action == "SELL":
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if not position or quantity > position.quantity:
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raise HTTPException(status_code=400, detail="Insufficient position")
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simulation.current_capital += total
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pnl = (price - position.avg_price) * quantity
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# Update simulation totals
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simulation.total_pnl += pnl
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if simulation.initial_capital > 0:
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simulation.total_pnl_percent = (simulation.total_pnl / simulation.initial_capital) * 100
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position.quantity -= quantity
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if position.quantity == 0:
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# Close position
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db.delete(position)
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position = None
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else:
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position.current_price = price
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# Create trade record
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trade_timestamp = datetime.now(timezone.utc)
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trade = Trade(
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simulation_id=simulation.id,
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action=TradeAction[action],
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quantity=quantity,
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price=price,
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total=total,
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pnl=pnl,
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timestamp=trade_timestamp
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)
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db.add(trade)
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db.flush()
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entry_time_dt = None
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if trade_request.entry_time:
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try:
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entry_time_dt = datetime.fromisoformat(trade_request.entry_time)
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if entry_time_dt.tzinfo is None:
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entry_time_dt = entry_time_dt.replace(tzinfo=timezone.utc)
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except ValueError:
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entry_time_dt = trade_timestamp
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metadata_fields = (
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trade_request.source,
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trade_request.platform,
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trade_request.notes,
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trade_request.stop_loss,
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trade_request.take_profit,
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trade_request.risk_percent,
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entry_time_dt,
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)
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if any(field is not None for field in metadata_fields):
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trade_metadata = TradeMetadata(
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trade_id=trade.id,
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source=trade_request.source,
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platform=trade_request.platform,
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notes=trade_request.notes,
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stop_loss=trade_request.stop_loss,
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take_profit=trade_request.take_profit,
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risk_percent=trade_request.risk_percent,
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entry_time=entry_time_dt,
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)
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db.add(trade_metadata)
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# Commit all changes
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db.commit()
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db.refresh(simulation)
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# Return updated portfolio state
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portfolio_state = get_portfolio_state_from_db(simulation, db)
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return {
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"trade": {
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"id": trade.id,
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"action": action,
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"quantity": quantity,
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"price": price,
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"total": total,
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"pnl": pnl,
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"timestamp": int(trade.timestamp.timestamp()) if trade.timestamp else None,
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"stop_loss": trade_request.stop_loss,
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"take_profit": trade_request.take_profit,
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"notes": trade_request.notes,
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"source": trade_request.source,
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"platform": trade_request.platform,
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"risk_percent": trade_request.risk_percent,
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"entry_time": entry_time_dt.isoformat() if entry_time_dt else None,
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},
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"portfolio": portfolio_state.dict()
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}
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except HTTPException:
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raise
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except Exception as e:
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db.rollback()
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raise HTTPException(status_code=500, detail=f"Trade execution failed: {str(e)}")
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@router.get("/portfolio")
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async def get_portfolio(
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db: Session = Depends(get_db),
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user_id: str = "default"
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):
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"""Get current portfolio state from database"""
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try:
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simulation = get_or_create_simulation(db, user_id)
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portfolio_state = get_portfolio_state_from_db(simulation, db)
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return portfolio_state.dict()
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Failed to get portfolio: {str(e)}")
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@router.post("/reset")
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async def reset_simulation(
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db: Session = Depends(get_db),
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user_id: str = "default"
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):
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"""Reset simulation to initial state"""
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try:
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simulation = db.query(Simulation).filter(Simulation.user_id == user_id).first()
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if simulation:
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# Delete all trades and positions (cascade will handle this)
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db.delete(simulation)
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db.commit()
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# Create new simulation
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new_simulation = Simulation(
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user_id=user_id,
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symbol="XAU/USD",
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initial_capital=100000.0,
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current_capital=100000.0,
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total_pnl=0.0,
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total_pnl_percent=0.0
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)
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db.add(new_simulation)
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db.commit()
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db.refresh(new_simulation)
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portfolio_state = get_portfolio_state_from_db(new_simulation, db)
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return {
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"message": "Simulation reset successfully",
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"portfolio": portfolio_state.dict()
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}
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except Exception as e:
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db.rollback()
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raise HTTPException(status_code=500, detail=f"Reset failed: {str(e)}")
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@router.get("/history")
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async def get_trade_history(
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db: Session = Depends(get_db),
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user_id: str = "default",
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limit: int = 100
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):
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"""Get trade history from database"""
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try:
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simulation = get_or_create_simulation(db, user_id)
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trades = db.query(Trade).options(selectinload(Trade.details)).filter(
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Trade.simulation_id == simulation.id
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).order_by(Trade.timestamp.desc()).limit(limit).all()
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return [
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{
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"id": trade.id,
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"action": trade.action.value,
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"quantity": trade.quantity,
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"price": trade.price,
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"total": trade.total,
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"pnl": trade.pnl,
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"timestamp": int(trade.timestamp.timestamp()) if trade.timestamp else None,
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"stop_loss": trade.details.stop_loss if trade.details else None,
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"take_profit": trade.details.take_profit if trade.details else None,
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"notes": trade.details.notes if trade.details else None,
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"source": trade.details.source if trade.details else None,
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"platform": trade.details.platform if trade.details else None,
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"risk_percent": trade.details.risk_percent if trade.details else None,
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"entry_time": trade.details.entry_time.isoformat() if trade.details and trade.details.entry_time else None,
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}
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for trade in trades
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]
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Failed to get history: {str(e)}")
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@router.get("/stats")
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async def get_trading_stats(
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db: Session = Depends(get_db),
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user_id: str = "default"
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):
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"""Get trading statistics"""
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try:
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simulation = get_or_create_simulation(db, user_id)
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trades = db.query(Trade).filter(
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Trade.simulation_id == simulation.id
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).all()
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total_trades = len(trades)
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winning_trades = sum(1 for t in trades if t.pnl and t.pnl > 0)
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losing_trades = sum(1 for t in trades if t.pnl and t.pnl < 0)
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total_profit = sum(t.pnl for t in trades if t.pnl and t.pnl > 0)
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total_loss = sum(abs(t.pnl) for t in trades if t.pnl and t.pnl < 0)
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win_rate = (winning_trades / total_trades * 100) if total_trades > 0 else 0
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profit_factor = (total_profit / total_loss) if total_loss > 0 else 0
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return {
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"total_trades": total_trades,
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"winning_trades": winning_trades,
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"losing_trades": losing_trades,
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"win_rate": round(win_rate, 2),
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"total_pnl": simulation.total_pnl,
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"total_pnl_percent": simulation.total_pnl_percent,
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"total_profit": total_profit,
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"total_loss": total_loss,
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"profit_factor": round(profit_factor, 2),
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"current_capital": simulation.current_capital,
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"initial_capital": simulation.initial_capital
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Failed to get stats: {str(e)}")
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