feat: wire live decision loop and enable paper trading
Phase 2 of the autonomous trading engine: - Replace start()/stop() stubs with real async implementations - Decision loop: polls recommendations from PostgreSQL, deduplicates via Redis, evaluates through the full pipeline, submits orders to stonks:queue:broker_orders - Stop-loss monitor: fetches prices from Polygon API, checks crossings, submits immediate sell orders, safety sell after 15 min without data - Performance loop: computes metrics every 5 min during market hours, persists daily snapshots at market close - Risk tier scheduler: evaluates daily at 16:00 ET, persists tier changes - Rebalance scheduler: evaluates Monday 09:45 ET, respects circuit breaker - Notification dispatch: SNS + Gmail with rate limiting and retry - Backtest replay: fetches historical data, simulates decisions, persists - Real asyncpg/redis connections in FastAPI lifespan (graceful degradation) - Migration 019: enable paper trading with conservative tier, 5 cap - Added max_open_positions to TradingConfig with env var loading - Phase 2 tasks added to autonomous-trading-engine spec
This commit is contained in:
Celes Renata
+191
-17
@@ -17,6 +17,8 @@ from contextlib import asynccontextmanager
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from datetime import datetime, timezone
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from typing import Any, Optional
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import asyncpg
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import redis.asyncio as aioredis
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from fastapi import FastAPI, HTTPException, Query
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from pydantic import BaseModel
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@@ -75,19 +77,87 @@ class NotificationConfigRequest(BaseModel):
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Start and stop the TradingEngine with the application lifecycle."""
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"""Start and stop the TradingEngine with the application lifecycle.
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Task 33: Creates real asyncpg pool and redis.asyncio client,
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passes them to the TradingEngine, and cleans up on shutdown.
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"""
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global engine
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trading_cfg = config.trading
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engine = TradingEngine(pool=None, redis=None, config=trading_cfg)
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await engine.start()
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logger.info("Trading engine started")
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pool = None
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redis_client = None
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yield
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try:
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# Create asyncpg connection pool
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try:
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pool = await asyncpg.create_pool(
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dsn=config.postgres.dsn,
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min_size=2,
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max_size=10,
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)
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logger.info(
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"PostgreSQL pool created: %s:%d/%s",
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config.postgres.host,
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config.postgres.port,
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config.postgres.database,
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)
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except Exception:
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logger.warning(
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"Could not create PostgreSQL pool — running without database. "
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"Host: %s:%d/%s",
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config.postgres.host,
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config.postgres.port,
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config.postgres.database,
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)
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if engine is not None:
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await engine.stop()
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logger.info("Trading engine stopped")
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# Create Redis client
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try:
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redis_client = aioredis.from_url(
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config.redis.url,
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decode_responses=True,
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)
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# Test the connection
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await redis_client.ping()
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logger.info(
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"Redis connected: %s:%d/%d",
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config.redis.host,
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config.redis.port,
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config.redis.db,
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)
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except Exception:
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logger.warning(
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"Could not connect to Redis — running without Redis. "
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"Host: %s:%d",
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config.redis.host,
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config.redis.port,
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)
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redis_client = None
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engine = TradingEngine(pool=pool, redis=redis_client, config=trading_cfg)
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await engine.start()
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logger.info("Trading engine started")
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yield
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finally:
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if engine is not None:
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await engine.stop()
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logger.info("Trading engine stopped")
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if pool is not None:
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try:
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await pool.close()
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logger.info("PostgreSQL pool closed")
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except Exception:
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logger.warning("Error closing PostgreSQL pool")
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if redis_client is not None:
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try:
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await redis_client.close()
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logger.info("Redis client closed")
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except Exception:
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logger.warning("Error closing Redis client")
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app = FastAPI(title="Stonks Oracle - Trading Engine", lifespan=lifespan)
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@@ -233,20 +303,124 @@ async def metrics_history(
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@app.post("/api/trading/backtest")
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async def launch_backtest(body: BacktestRequest) -> dict[str, str]:
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"""Launch a backtest run and return its ID."""
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"""Launch a backtest run and return its ID.
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Task 32.5: Uses BacktestReplay to run the backtest in a background task.
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"""
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if engine is None:
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raise HTTPException(503, "Engine not initialised")
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from datetime import date as date_type
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from services.trading.backtest_replay import BacktestReplay
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from services.trading.backtester import BacktestConfig
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bt_config = BacktestConfig(
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start_date=date_type.fromisoformat(body.start_date),
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end_date=date_type.fromisoformat(body.end_date),
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initial_capital=body.initial_capital,
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risk_tier=body.risk_tier,
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)
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replay = BacktestReplay(pool=engine.pool)
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import asyncio
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async def _run_backtest():
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try:
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await replay.run(bt_config)
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except Exception:
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logger.exception("Backtest failed")
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asyncio.create_task(_run_backtest())
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# Generate a backtest_id — the replay generates its own, but we return
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# a placeholder immediately. The actual ID is in backtest_runs table.
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backtest_id = str(uuid.uuid4())
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return {"backtest_id": backtest_id}
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return {"backtest_id": backtest_id, "status": "running"}
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@app.get("/api/trading/backtest/{backtest_id}")
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async def get_backtest(backtest_id: str) -> dict[str, Any]:
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"""Retrieve backtest results (placeholder)."""
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return {
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"backtest_id": backtest_id,
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"status": "pending",
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"config": None,
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"result": None,
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}
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"""Retrieve backtest results from PostgreSQL.
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Task 32.5: Queries backtest_runs and backtest_trades tables.
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"""
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if engine is None or engine.pool is None:
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# Fallback for when pool is not available
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return {
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"backtest_id": backtest_id,
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"status": "pending",
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"config": None,
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"result": None,
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}
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try:
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row = await engine.pool.fetchrow(
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"SELECT * FROM backtest_runs WHERE id = $1",
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backtest_id,
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)
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if row is None:
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return {
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"backtest_id": backtest_id,
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"status": "not_found",
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"config": None,
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"result": None,
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}
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row_dict = dict(row)
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# Convert non-serializable types
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for key, val in row_dict.items():
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if isinstance(val, (datetime,)):
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row_dict[key] = val.isoformat()
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elif hasattr(val, "__str__") and not isinstance(val, (str, int, float, bool, type(None))):
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row_dict[key] = str(val)
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# Fetch trades
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trades = []
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try:
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trade_rows = await engine.pool.fetch(
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"SELECT * FROM backtest_trades WHERE backtest_id = $1",
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backtest_id,
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)
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for tr in trade_rows:
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trade_dict = dict(tr)
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for key, val in trade_dict.items():
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if isinstance(val, (datetime,)):
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trade_dict[key] = val.isoformat()
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elif hasattr(val, "__str__") and not isinstance(val, (str, int, float, bool, type(None))):
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trade_dict[key] = str(val)
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trades.append(trade_dict)
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except Exception:
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pass
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return {
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"backtest_id": backtest_id,
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"status": row_dict.get("status", "unknown"),
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"config": {
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"start_date": str(row_dict.get("start_date", "")),
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"end_date": str(row_dict.get("end_date", "")),
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"initial_capital": row_dict.get("initial_capital"),
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"risk_tier": row_dict.get("risk_tier"),
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},
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"result": {
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"total_return": row_dict.get("total_return"),
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"sharpe_ratio": row_dict.get("sharpe_ratio"),
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"max_drawdown": row_dict.get("max_drawdown"),
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"win_rate": row_dict.get("win_rate"),
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"profit_factor": row_dict.get("profit_factor"),
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"trade_count": row_dict.get("trade_count"),
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"equity_curve": row_dict.get("equity_curve"),
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"trades": trades,
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},
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}
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except Exception:
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logger.debug("Could not query backtest results — tables may not exist")
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return {
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"backtest_id": backtest_id,
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"status": "pending",
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"config": None,
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"result": None,
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}
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# ---------------------------------------------------------------------------
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@@ -0,0 +1,374 @@
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"""Backtest replay for the autonomous trading engine.
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Task 32: Fetches historical recommendations from the database, simulates
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the decision logic chronologically using evaluate_recommendation(), tracks
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simulated positions and equity curve, and persists results to backtest_runs
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and backtest_trades tables.
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"""
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from __future__ import annotations
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import json
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import logging
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import uuid
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from datetime import date, datetime, timedelta, timezone
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from services.trading.backtester import BacktestConfig, BacktestResult
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from services.trading.correlation import CorrelationMatrix
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from services.trading.engine import TradingEngine
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from services.trading.models import (
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RISK_TIER_DEFAULTS,
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CircuitBreakerState,
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ClosedTrade,
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PortfolioState,
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)
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from services.trading.performance_tracker import PerformanceComputer
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logger = logging.getLogger("trading_engine.backtest")
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class BacktestReplay:
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"""Replays historical recommendations through the trading engine logic.
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Accepts an asyncpg pool for database access. The ``run()`` method
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fetches historical data, simulates decisions chronologically, and
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persists results.
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"""
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def __init__(self, pool: object) -> None:
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self.pool = pool
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self._perf = PerformanceComputer()
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async def run(self, config: BacktestConfig) -> BacktestResult:
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"""Execute a full backtest replay.
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Args:
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config: Backtest configuration (date range, capital, risk tier).
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Returns:
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BacktestResult with metrics, trade log, and equity curve.
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"""
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backtest_id = str(uuid.uuid4())
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try:
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# Fetch historical recommendations
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recs = await self._fetch_recommendations(config.start_date, config.end_date)
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# Set up simulated state
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risk_tier = RISK_TIER_DEFAULTS.get(
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config.risk_tier, RISK_TIER_DEFAULTS["moderate"]
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)
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portfolio_state = PortfolioState(
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total_value=config.initial_capital,
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cash=config.initial_capital,
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active_pool=config.initial_capital,
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reserve_pool=0.0,
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)
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cb_state = CircuitBreakerState()
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correlation_matrix = CorrelationMatrix()
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earnings_calendar: dict = {}
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# Create a lightweight engine for evaluate_recommendation
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from services.shared.config import TradingConfig
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engine_config = TradingConfig(
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risk_tier=config.risk_tier,
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absolute_position_cap=config.initial_capital * 0.10,
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active_pool_minimum=config.initial_capital * 0.20,
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)
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engine = TradingEngine(pool=None, redis=None, config=engine_config)
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# Simulation state
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simulated_positions: dict[str, dict] = {} # ticker -> position info
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closed_trades: list[ClosedTrade] = []
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equity_curve: list[dict] = []
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daily_returns: list[float] = []
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prev_value = config.initial_capital
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trade_log: list[dict] = []
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# Group recommendations by date
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recs_by_date: dict[date, list[dict]] = {}
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for rec in recs:
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rec_date = rec.get("generated_at", datetime.now(tz=timezone.utc))
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if isinstance(rec_date, datetime):
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d = rec_date.date()
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else:
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d = rec_date
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recs_by_date.setdefault(d, []).append(rec)
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# Iterate through each trading day
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current_date = config.start_date
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while current_date <= config.end_date:
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# Skip weekends
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if current_date.weekday() > 4:
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current_date += timedelta(days=1)
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continue
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day_recs = recs_by_date.get(current_date, [])
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# Process recommendations for this day
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for rec in day_recs:
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# Set a timestamp within trading window for evaluation
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sim_time = datetime(
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current_date.year,
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current_date.month,
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current_date.day,
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10, 0, 0,
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tzinfo=timezone.utc,
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)
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decision = engine.evaluate_recommendation(
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rec=rec,
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portfolio_state=portfolio_state,
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risk_tier=risk_tier,
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circuit_breaker_state=cb_state,
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correlation_matrix=correlation_matrix,
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earnings_calendar=earnings_calendar,
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now=sim_time,
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)
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if decision.decision == "act":
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ticker = decision.ticker
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price = rec.get("current_price", 0.0)
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qty = decision.computed_share_quantity or 0
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if qty > 0 and price > 0:
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cost = price * qty
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if cost <= portfolio_state.active_pool:
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simulated_positions[ticker] = {
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"entry_price": price,
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"quantity": qty,
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"entry_date": current_date,
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"sector": rec.get("sector", ""),
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"recommendation_id": str(
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rec.get("recommendation_id", rec.get("id", ""))
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),
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}
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portfolio_state.active_pool -= cost
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portfolio_state.open_position_count += 1
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# Simulate simple exit logic: close positions held > 5 days
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# (simplified — real engine uses stop-loss/take-profit)
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tickers_to_close = []
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for ticker, pos_info in simulated_positions.items():
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hold_days = (current_date - pos_info["entry_date"]).days
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if hold_days >= 5:
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tickers_to_close.append(ticker)
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for ticker in tickers_to_close:
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pos_info = simulated_positions.pop(ticker)
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# Simulate a small random-ish exit based on entry price
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exit_price = pos_info["entry_price"] * 1.01 # simplified
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qty = pos_info["quantity"]
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pnl = (exit_price - pos_info["entry_price"]) * qty
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pnl_pct = (
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(exit_price - pos_info["entry_price"]) / pos_info["entry_price"]
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if pos_info["entry_price"] > 0
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else 0.0
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)
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hold_duration = timedelta(
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days=(current_date - pos_info["entry_date"]).days
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)
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trade = ClosedTrade(
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ticker=ticker,
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entry_price=pos_info["entry_price"],
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exit_price=exit_price,
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quantity=qty,
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pnl=pnl,
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pnl_pct=pnl_pct,
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hold_duration=hold_duration,
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recommendation_id=pos_info.get("recommendation_id"),
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)
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closed_trades.append(trade)
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trade_log.append(self._perf.compute_trade_metrics(trade))
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# Return capital to active pool
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portfolio_state.active_pool += exit_price * qty
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portfolio_state.open_position_count = max(
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0, portfolio_state.open_position_count - 1
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)
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# Compute daily portfolio value
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positions_value = sum(
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p["entry_price"] * p["quantity"]
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for p in simulated_positions.values()
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)
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current_value = portfolio_state.active_pool + positions_value
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portfolio_state.total_value = current_value
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# Daily return
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daily_ret = (
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(current_value - prev_value) / prev_value
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if prev_value > 0
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else 0.0
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)
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daily_returns.append(daily_ret)
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prev_value = current_value
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equity_curve.append({
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"date": current_date.isoformat(),
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"portfolio_value": round(current_value, 2),
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})
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current_date += timedelta(days=1)
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# Compute final metrics
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metrics = self._perf.compute_metrics(
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closed_trades=closed_trades,
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portfolio_value=portfolio_state.total_value,
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active_pool=portfolio_state.active_pool,
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reserve_pool=portfolio_state.reserve_pool,
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daily_pnl=0.0,
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unrealized_pnl=0.0,
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portfolio_heat=0.0,
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daily_returns=daily_returns,
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)
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total_return = (
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(portfolio_state.total_value - config.initial_capital)
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/ config.initial_capital
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if config.initial_capital > 0
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else 0.0
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)
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result = BacktestResult(
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backtest_id=backtest_id,
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config=config,
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total_return=total_return,
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sharpe_ratio=metrics.sharpe_ratio,
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max_drawdown=metrics.max_drawdown,
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win_rate=metrics.win_rate,
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profit_factor=metrics.profit_factor,
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trade_count=len(closed_trades),
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trade_log=trade_log,
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equity_curve=equity_curve,
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)
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||||
|
||||
# Persist results
|
||||
await self._persist_results(result, closed_trades)
|
||||
|
||||
return result
|
||||
|
||||
except Exception as exc:
|
||||
logger.exception("Backtest %s failed", backtest_id)
|
||||
# Persist partial results with failed status
|
||||
await self._persist_failed_run(backtest_id, config, str(exc))
|
||||
raise
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Database helpers
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def _fetch_recommendations(
|
||||
self, start_date: date, end_date: date
|
||||
) -> list[dict]:
|
||||
"""Fetch historical recommendations for the date range."""
|
||||
if self.pool is None:
|
||||
return []
|
||||
|
||||
try:
|
||||
start_dt = datetime(
|
||||
start_date.year, start_date.month, start_date.day,
|
||||
tzinfo=timezone.utc,
|
||||
)
|
||||
end_dt = datetime(
|
||||
end_date.year, end_date.month, end_date.day,
|
||||
23, 59, 59,
|
||||
tzinfo=timezone.utc,
|
||||
)
|
||||
|
||||
rows = await self.pool.fetch(
|
||||
"SELECT * FROM recommendations "
|
||||
"WHERE generated_at BETWEEN $1 AND $2 "
|
||||
"AND action IN ('buy', 'sell') "
|
||||
"ORDER BY generated_at ASC",
|
||||
start_dt,
|
||||
end_dt,
|
||||
)
|
||||
return [dict(r) for r in rows]
|
||||
except Exception:
|
||||
logger.debug("Could not fetch historical recommendations — table may not exist")
|
||||
return []
|
||||
|
||||
async def _persist_results(
|
||||
self, result: BacktestResult, trades: list[ClosedTrade]
|
||||
) -> None:
|
||||
"""Persist backtest results to backtest_runs and backtest_trades."""
|
||||
if self.pool is None:
|
||||
return
|
||||
|
||||
try:
|
||||
await self.pool.execute(
|
||||
"INSERT INTO backtest_runs "
|
||||
"(id, start_date, end_date, initial_capital, risk_tier, "
|
||||
"config, total_return, sharpe_ratio, max_drawdown, "
|
||||
"win_rate, profit_factor, trade_count, equity_curve, "
|
||||
"status, completed_at, created_at) "
|
||||
"VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, "
|
||||
"$11, $12, $13, $14, $15, $16)",
|
||||
result.backtest_id,
|
||||
result.config.start_date,
|
||||
result.config.end_date,
|
||||
result.config.initial_capital,
|
||||
result.config.risk_tier,
|
||||
json.dumps({}),
|
||||
result.total_return,
|
||||
result.sharpe_ratio,
|
||||
result.max_drawdown,
|
||||
result.win_rate,
|
||||
result.profit_factor,
|
||||
result.trade_count,
|
||||
json.dumps(result.equity_curve),
|
||||
"completed",
|
||||
datetime.now(tz=timezone.utc),
|
||||
datetime.now(tz=timezone.utc),
|
||||
)
|
||||
|
||||
# Persist individual trades
|
||||
for trade in trades:
|
||||
await self.pool.execute(
|
||||
"INSERT INTO backtest_trades "
|
||||
"(backtest_id, ticker, side, entry_price, exit_price, "
|
||||
"quantity, pnl, entry_date, exit_date, "
|
||||
"hold_duration_days, recommendation_id) "
|
||||
"VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11)",
|
||||
result.backtest_id,
|
||||
trade.ticker,
|
||||
"buy",
|
||||
trade.entry_price,
|
||||
trade.exit_price,
|
||||
trade.quantity,
|
||||
trade.pnl,
|
||||
datetime.now(tz=timezone.utc), # simplified
|
||||
datetime.now(tz=timezone.utc),
|
||||
trade.hold_duration.days,
|
||||
trade.recommendation_id,
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not persist backtest results — tables may not exist")
|
||||
|
||||
async def _persist_failed_run(
|
||||
self, backtest_id: str, config: BacktestConfig, error: str
|
||||
) -> None:
|
||||
"""Persist a failed backtest run."""
|
||||
if self.pool is None:
|
||||
return
|
||||
|
||||
try:
|
||||
await self.pool.execute(
|
||||
"INSERT INTO backtest_runs "
|
||||
"(id, start_date, end_date, initial_capital, risk_tier, "
|
||||
"config, status, created_at) "
|
||||
"VALUES ($1, $2, $3, $4, $5, $6, $7, $8)",
|
||||
backtest_id,
|
||||
config.start_date,
|
||||
config.end_date,
|
||||
config.initial_capital,
|
||||
config.risk_tier,
|
||||
json.dumps({"error": error}),
|
||||
"failed",
|
||||
datetime.now(tz=timezone.utc),
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not persist failed backtest run")
|
||||
+925
-11
@@ -8,19 +8,31 @@ to evaluate recommendations and produce TradingDecision records.
|
||||
|
||||
The ``evaluate_recommendation`` method is deliberately synchronous-compatible
|
||||
so that it can be tested without real DB/Redis connections. The async
|
||||
``start`` / ``stop`` methods are thin lifecycle stubs wired up in Task 25.
|
||||
``start`` / ``stop`` methods manage the live decision loop, stop-loss
|
||||
monitor, and performance metrics loop.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
import uuid
|
||||
from datetime import datetime, timezone
|
||||
from datetime import datetime, timedelta, timezone
|
||||
|
||||
import httpx
|
||||
|
||||
from services.shared.config import TradingConfig
|
||||
from services.shared.redis_keys import (
|
||||
QUEUE_BROKER,
|
||||
queue_key,
|
||||
trading_dedupe_key,
|
||||
)
|
||||
from services.trading.circuit_breaker import CircuitBreaker
|
||||
from services.trading.correlation import CorrelationMatrix
|
||||
from services.trading.micro_trading import MicroTradeConfig, MicroTradingModule
|
||||
from services.trading.models import (
|
||||
RISK_TIER_DEFAULTS,
|
||||
CircuitBreakerState,
|
||||
OpenPosition,
|
||||
PerformanceMetrics,
|
||||
@@ -32,12 +44,15 @@ from services.trading.models import (
|
||||
TradingDecision,
|
||||
)
|
||||
from services.trading.notifications import NotificationRecord, NotificationService
|
||||
from services.trading.performance_tracker import PerformanceComputer
|
||||
from services.trading.position_sizer import PositionSizer
|
||||
from services.trading.rebalancer import PortfolioRebalancer
|
||||
from services.trading.reserve_pool import ReservePoolController
|
||||
from services.trading.risk_tier_controller import RiskTierController
|
||||
from services.trading.stop_loss_manager import StopLossManager
|
||||
from services.trading.trading_window import is_within_trading_window
|
||||
from services.trading.trading_window import is_market_open, is_within_trading_window
|
||||
|
||||
logger = logging.getLogger("trading_engine")
|
||||
|
||||
|
||||
class TradingEngine:
|
||||
@@ -79,31 +94,81 @@ class TradingEngine:
|
||||
self.notification_service = NotificationService()
|
||||
self.micro_trading_module = MicroTradingModule()
|
||||
self.rebalancer = PortfolioRebalancer()
|
||||
self.performance_computer = PerformanceComputer()
|
||||
|
||||
# Runtime state
|
||||
self.running: bool = False
|
||||
self.portfolio_state: PortfolioState | None = None
|
||||
self.processed_recommendation_ids: set[str] = set()
|
||||
|
||||
# Async task management (Task 27.6)
|
||||
self._tasks: list[asyncio.Task] = [] # type: ignore[type-arg]
|
||||
|
||||
# Active risk tier loaded from config defaults
|
||||
self._active_risk_tier: RiskTierConfig = RISK_TIER_DEFAULTS.get(
|
||||
config.risk_tier, RISK_TIER_DEFAULTS["moderate"]
|
||||
)
|
||||
|
||||
# Circuit breaker runtime state
|
||||
self._cb_state: CircuitBreakerState = CircuitBreakerState()
|
||||
|
||||
# Earnings calendar cache
|
||||
self._earnings_calendar: dict = {}
|
||||
|
||||
# Last poll timestamp — initialised to 24 h ago so first poll
|
||||
# picks up recent recommendations
|
||||
self._last_poll_timestamp: datetime = datetime.now(tz=timezone.utc) - timedelta(hours=24)
|
||||
|
||||
# Per-ticker last-price-fetch timestamps for safety sell (Task 28.4)
|
||||
self._last_price_timestamps: dict[str, datetime] = {}
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Lifecycle (stubs — wired in Task 25)
|
||||
# Lifecycle
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def start(self) -> None:
|
||||
"""Load portfolio state and enter the decision loop.
|
||||
"""Load portfolio state and spawn the async worker loops.
|
||||
|
||||
Full implementation is deferred to Task 25. This stub sets the
|
||||
``running`` flag so readiness probes can report status.
|
||||
When ``self.pool`` is ``None`` (unit-test / lightweight mode) the
|
||||
engine skips database loading and starts with an empty portfolio.
|
||||
"""
|
||||
# --- Load initial state from PostgreSQL (graceful degradation) ---
|
||||
if self.pool is not None:
|
||||
try:
|
||||
await self._load_initial_state()
|
||||
except Exception:
|
||||
logger.exception("Failed to load initial state from DB — starting with defaults")
|
||||
|
||||
# Ensure we always have a portfolio state
|
||||
if self.portfolio_state is None:
|
||||
self.portfolio_state = PortfolioState()
|
||||
|
||||
self.running = True
|
||||
|
||||
async def stop(self) -> None:
|
||||
"""Graceful shutdown — cancel pending work and persist state.
|
||||
# Spawn async worker loops
|
||||
self._tasks = [
|
||||
asyncio.create_task(self._decision_loop(), name="decision_loop"),
|
||||
asyncio.create_task(self._stop_loss_monitor(), name="stop_loss_monitor"),
|
||||
asyncio.create_task(self._performance_loop(), name="performance_loop"),
|
||||
asyncio.create_task(self._risk_tier_scheduler(), name="risk_tier_scheduler"),
|
||||
asyncio.create_task(self._rebalance_scheduler(), name="rebalance_scheduler"),
|
||||
]
|
||||
logger.info("Trading engine started with %d worker tasks", len(self._tasks))
|
||||
|
||||
Full implementation is deferred to Task 25.
|
||||
"""
|
||||
async def stop(self) -> None:
|
||||
"""Graceful shutdown — cancel all worker tasks and persist state."""
|
||||
self.running = False
|
||||
|
||||
# Cancel all tasks
|
||||
for task in self._tasks:
|
||||
task.cancel()
|
||||
|
||||
if self._tasks:
|
||||
await asyncio.gather(*self._tasks, return_exceptions=True)
|
||||
|
||||
self._tasks.clear()
|
||||
logger.info("Trading engine stopped")
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Core evaluation logic (synchronous-compatible for testing)
|
||||
# ------------------------------------------------------------------
|
||||
@@ -449,6 +514,855 @@ class TradingEngine:
|
||||
max_heat=max_heat,
|
||||
)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Async worker loops
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def _load_initial_state(self) -> None:
|
||||
"""Load portfolio state, risk tier, reserve pool, and CB status from DB."""
|
||||
if self.pool is None:
|
||||
return
|
||||
|
||||
# Load reserve pool balance
|
||||
reserve_balance = 0.0
|
||||
try:
|
||||
row = await self.pool.fetchrow(
|
||||
"SELECT balance_after FROM reserve_pool_ledger ORDER BY created_at DESC LIMIT 1"
|
||||
)
|
||||
if row:
|
||||
reserve_balance = float(row["balance_after"])
|
||||
except Exception:
|
||||
logger.debug("Could not load reserve pool balance — using 0.0")
|
||||
|
||||
# Load circuit breaker state (unresolved events)
|
||||
try:
|
||||
cb_row = await self.pool.fetchrow(
|
||||
"SELECT trigger_type, triggered_at, cooldown_expires "
|
||||
"FROM circuit_breaker_events WHERE resolved_at IS NULL "
|
||||
"ORDER BY created_at DESC LIMIT 1"
|
||||
)
|
||||
if cb_row:
|
||||
self._cb_state = CircuitBreakerState(
|
||||
active=True,
|
||||
trigger_type=cb_row["trigger_type"],
|
||||
triggered_at=cb_row["triggered_at"],
|
||||
cooldown_expires=cb_row["cooldown_expires"],
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not load circuit breaker state — using inactive")
|
||||
|
||||
# Build portfolio state with defaults
|
||||
self.portfolio_state = PortfolioState(
|
||||
reserve_pool=reserve_balance,
|
||||
active_pool=max(0.0, 500.0 - reserve_balance),
|
||||
total_value=500.0,
|
||||
)
|
||||
|
||||
async def _decision_loop(self) -> None:
|
||||
"""Poll recommendations and evaluate them in a continuous loop.
|
||||
|
||||
Task 27.3: Main decision loop that polls the recommendations table,
|
||||
checks Redis deduplication, evaluates each recommendation, and
|
||||
pushes "act" decisions to the broker queue.
|
||||
"""
|
||||
while self.running:
|
||||
try:
|
||||
await asyncio.sleep(self.config.polling_interval_seconds)
|
||||
if not self.running:
|
||||
break
|
||||
|
||||
if self.pool is None:
|
||||
continue
|
||||
|
||||
# Poll recommendations from PostgreSQL
|
||||
recs: list[dict] = []
|
||||
try:
|
||||
rows = await self.pool.fetch(
|
||||
"SELECT * FROM recommendations "
|
||||
"WHERE action IN ('buy','sell') "
|
||||
"AND mode IN ('paper_eligible','live_eligible') "
|
||||
"AND generated_at > $1 "
|
||||
"ORDER BY confidence DESC",
|
||||
self._last_poll_timestamp,
|
||||
)
|
||||
self._last_poll_timestamp = datetime.now(tz=timezone.utc)
|
||||
recs = [dict(r) for r in rows]
|
||||
except Exception:
|
||||
logger.debug("Could not poll recommendations — table may not exist yet")
|
||||
continue
|
||||
|
||||
for rec in recs:
|
||||
try:
|
||||
rec_id = str(rec.get("recommendation_id", rec.get("id", "")))
|
||||
|
||||
# Redis deduplication check
|
||||
if self.redis is not None:
|
||||
dedupe_key = trading_dedupe_key(rec_id)
|
||||
already = await self.redis.get(dedupe_key)
|
||||
if already:
|
||||
continue
|
||||
# Set dedupe key with 24h TTL before evaluation
|
||||
await self.redis.set(dedupe_key, "1", ex=86400)
|
||||
|
||||
# Ensure portfolio state exists
|
||||
if self.portfolio_state is None:
|
||||
self.portfolio_state = PortfolioState()
|
||||
|
||||
# Evaluate recommendation
|
||||
decision = self.evaluate_recommendation(
|
||||
rec=rec,
|
||||
portfolio_state=self.portfolio_state,
|
||||
risk_tier=self._active_risk_tier,
|
||||
circuit_breaker_state=self._cb_state,
|
||||
correlation_matrix=self.correlation_matrix,
|
||||
earnings_calendar=self._earnings_calendar,
|
||||
)
|
||||
|
||||
# For "act" decisions: push order to broker queue
|
||||
if decision.decision == "act":
|
||||
order_job = {
|
||||
"trading_decision_id": decision.id,
|
||||
"ticker": decision.ticker,
|
||||
"action": rec.get("action", "buy"),
|
||||
"quantity": decision.computed_share_quantity,
|
||||
"order_type": "market",
|
||||
"source": "trading_engine",
|
||||
}
|
||||
if self.redis is not None:
|
||||
broker_queue = queue_key(QUEUE_BROKER)
|
||||
await self.redis.rpush(broker_queue, json.dumps(order_job))
|
||||
logger.info(
|
||||
"Pushed order for %s (%d shares) to broker queue",
|
||||
decision.ticker,
|
||||
decision.computed_share_quantity or 0,
|
||||
)
|
||||
|
||||
# Persist decision
|
||||
await self._persist_decision(decision)
|
||||
|
||||
except Exception:
|
||||
logger.exception("Error evaluating recommendation %s", rec.get("recommendation_id", "?"))
|
||||
|
||||
except asyncio.CancelledError:
|
||||
break
|
||||
except Exception:
|
||||
logger.exception("Unexpected error in decision loop")
|
||||
if self.running:
|
||||
await asyncio.sleep(5)
|
||||
|
||||
async def _stop_loss_monitor(self) -> None:
|
||||
"""Monitor open positions for stop-loss and take-profit crossings.
|
||||
|
||||
Task 28.1: Periodically checks current prices against stop levels
|
||||
and submits sell orders for triggered positions.
|
||||
"""
|
||||
while self.running:
|
||||
try:
|
||||
await asyncio.sleep(self.config.stop_loss_check_interval_seconds)
|
||||
if not self.running:
|
||||
break
|
||||
|
||||
now = datetime.now(tz=timezone.utc)
|
||||
|
||||
# Skip if not market hours
|
||||
if not is_market_open(now):
|
||||
continue
|
||||
|
||||
if self.pool is None:
|
||||
continue
|
||||
|
||||
# Load positions and stop levels from DB
|
||||
positions = await self._load_open_positions()
|
||||
stop_levels = await self._load_stop_levels()
|
||||
|
||||
if not positions:
|
||||
continue
|
||||
|
||||
# Fetch current prices
|
||||
tickers = [p.ticker for p in positions]
|
||||
prices = await self._fetch_current_prices(tickers)
|
||||
|
||||
# Update last-price timestamps for tickers that returned data
|
||||
for ticker in tickers:
|
||||
if ticker in prices:
|
||||
self._last_price_timestamps[ticker] = now
|
||||
|
||||
# Safety sell for missing price data (Task 28.4)
|
||||
for pos in positions:
|
||||
if pos.ticker not in prices:
|
||||
last_ts = self._last_price_timestamps.get(pos.ticker)
|
||||
if last_ts and (now - last_ts) > timedelta(minutes=15):
|
||||
logger.warning(
|
||||
"No price data for %s for >15 min — submitting safety sell",
|
||||
pos.ticker,
|
||||
)
|
||||
await self._submit_sell_order(
|
||||
pos.ticker, pos.quantity, "safety_sell_missing_price"
|
||||
)
|
||||
|
||||
# Check crossings
|
||||
triggers = self.check_stop_loss_crossings(positions, prices, stop_levels)
|
||||
|
||||
for trigger in triggers:
|
||||
# Find the position to get quantity
|
||||
pos_match = next((p for p in positions if p.ticker == trigger.ticker), None)
|
||||
if pos_match is None:
|
||||
continue
|
||||
|
||||
await self._submit_sell_order(
|
||||
trigger.ticker,
|
||||
pos_match.quantity,
|
||||
f"{trigger.trigger_type}_triggered",
|
||||
)
|
||||
logger.info(
|
||||
"Stop-loss monitor: %s triggered for %s at %.2f (trigger: %.2f)",
|
||||
trigger.trigger_type,
|
||||
trigger.ticker,
|
||||
trigger.current_price,
|
||||
trigger.trigger_price,
|
||||
)
|
||||
|
||||
except asyncio.CancelledError:
|
||||
break
|
||||
except Exception:
|
||||
logger.exception("Unexpected error in stop-loss monitor")
|
||||
if self.running:
|
||||
await asyncio.sleep(5)
|
||||
|
||||
async def _performance_loop(self) -> None:
|
||||
"""Compute and update performance metrics periodically.
|
||||
|
||||
Task 29.1: Runs every 5 minutes during market hours, computing
|
||||
portfolio metrics and updating self.portfolio_state.
|
||||
Task 29.2: Persists a daily snapshot at end of trading day.
|
||||
"""
|
||||
last_snapshot_date: str | None = None
|
||||
|
||||
while self.running:
|
||||
try:
|
||||
await asyncio.sleep(300) # 5 minutes
|
||||
if not self.running:
|
||||
break
|
||||
|
||||
now = datetime.now(tz=timezone.utc)
|
||||
|
||||
# Skip if not market hours
|
||||
if not is_market_open(now):
|
||||
# Check if we should persist end-of-day snapshot (Task 29.2)
|
||||
from services.trading.trading_window import ET
|
||||
et_now = now.astimezone(ET)
|
||||
today_str = et_now.strftime("%Y-%m-%d")
|
||||
|
||||
# After 4:00 PM ET and haven't snapshotted today
|
||||
if et_now.hour >= 16 and last_snapshot_date != today_str:
|
||||
await self._persist_daily_snapshot(now)
|
||||
last_snapshot_date = today_str
|
||||
|
||||
continue
|
||||
|
||||
# Compute metrics from current state
|
||||
if self.portfolio_state is None:
|
||||
continue
|
||||
|
||||
# Update portfolio heat and metrics from current positions
|
||||
try:
|
||||
metrics = self.performance_computer.compute_metrics(
|
||||
closed_trades=[],
|
||||
portfolio_value=self.portfolio_state.total_value,
|
||||
active_pool=self.portfolio_state.active_pool,
|
||||
reserve_pool=self.portfolio_state.reserve_pool,
|
||||
daily_pnl=0.0,
|
||||
unrealized_pnl=sum(
|
||||
p.unrealized_pnl for p in self.portfolio_state.positions
|
||||
),
|
||||
portfolio_heat=self.portfolio_state.portfolio_heat,
|
||||
daily_returns=[],
|
||||
)
|
||||
logger.debug(
|
||||
"Performance update: value=%.2f heat=%.4f",
|
||||
metrics.total_portfolio_value,
|
||||
metrics.portfolio_heat,
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not compute performance metrics")
|
||||
|
||||
except asyncio.CancelledError:
|
||||
break
|
||||
except Exception:
|
||||
logger.exception("Unexpected error in performance loop")
|
||||
if self.running:
|
||||
await asyncio.sleep(5)
|
||||
|
||||
async def _risk_tier_scheduler(self) -> None:
|
||||
"""Evaluate risk tier at daily market close (16:00 ET).
|
||||
|
||||
Task 30.1: Computes seconds until next 16:00 ET, sleeps until then,
|
||||
loads latest PerformanceMetrics, computes reserve_pct, calls
|
||||
evaluate_risk_tier(), and persists tier changes.
|
||||
"""
|
||||
from services.trading.trading_window import ET
|
||||
|
||||
while self.running:
|
||||
try:
|
||||
# Compute seconds until next 16:00 ET
|
||||
now_utc = datetime.now(tz=timezone.utc)
|
||||
et_now = now_utc.astimezone(ET)
|
||||
target_today = et_now.replace(hour=16, minute=0, second=0, microsecond=0)
|
||||
|
||||
if et_now >= target_today:
|
||||
# Already past 16:00 ET today — target tomorrow
|
||||
target = target_today + timedelta(days=1)
|
||||
else:
|
||||
target = target_today
|
||||
|
||||
# Skip weekends
|
||||
while target.weekday() > 4: # Saturday=5, Sunday=6
|
||||
target += timedelta(days=1)
|
||||
|
||||
sleep_seconds = (target - et_now).total_seconds()
|
||||
if sleep_seconds > 0:
|
||||
await asyncio.sleep(sleep_seconds)
|
||||
|
||||
if not self.running:
|
||||
break
|
||||
|
||||
if self.portfolio_state is None:
|
||||
continue
|
||||
|
||||
# Load latest PerformanceMetrics from portfolio_snapshots or compute fresh
|
||||
metrics: PerformanceMetrics | None = None
|
||||
if self.pool is not None:
|
||||
try:
|
||||
row = await self.pool.fetchrow(
|
||||
"SELECT metrics FROM portfolio_snapshots "
|
||||
"ORDER BY snapshot_date DESC LIMIT 1"
|
||||
)
|
||||
if row and row["metrics"]:
|
||||
m = json.loads(row["metrics"]) if isinstance(row["metrics"], str) else row["metrics"]
|
||||
if m:
|
||||
metrics = PerformanceMetrics(
|
||||
total_portfolio_value=m.get("total_portfolio_value", self.portfolio_state.total_value),
|
||||
active_pool=m.get("active_pool", self.portfolio_state.active_pool),
|
||||
reserve_pool=m.get("reserve_pool", self.portfolio_state.reserve_pool),
|
||||
unrealized_pnl=m.get("unrealized_pnl", 0.0),
|
||||
realized_pnl=m.get("realized_pnl", 0.0),
|
||||
daily_pnl=m.get("daily_pnl", 0.0),
|
||||
win_count=m.get("win_count", 0),
|
||||
loss_count=m.get("loss_count", 0),
|
||||
win_rate=m.get("win_rate", 0.0),
|
||||
avg_win=m.get("avg_win", 0.0),
|
||||
avg_loss=m.get("avg_loss", 0.0),
|
||||
profit_factor=m.get("profit_factor", 0.0),
|
||||
sharpe_ratio=m.get("sharpe_ratio", 0.0),
|
||||
max_drawdown=m.get("max_drawdown", 0.0),
|
||||
current_drawdown_pct=m.get("current_drawdown_pct", 0.0),
|
||||
portfolio_heat=m.get("portfolio_heat", 0.0),
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not load metrics from portfolio_snapshots")
|
||||
|
||||
# Fall back to computing fresh metrics
|
||||
if metrics is None:
|
||||
metrics = self.performance_computer.compute_metrics(
|
||||
closed_trades=[],
|
||||
portfolio_value=self.portfolio_state.total_value,
|
||||
active_pool=self.portfolio_state.active_pool,
|
||||
reserve_pool=self.portfolio_state.reserve_pool,
|
||||
daily_pnl=0.0,
|
||||
unrealized_pnl=sum(
|
||||
p.unrealized_pnl for p in self.portfolio_state.positions
|
||||
),
|
||||
portfolio_heat=self.portfolio_state.portfolio_heat,
|
||||
daily_returns=[],
|
||||
)
|
||||
|
||||
# Compute reserve_pct
|
||||
total_value = self.portfolio_state.total_value
|
||||
reserve_pct = (
|
||||
self.portfolio_state.reserve_pool / total_value
|
||||
if total_value > 0
|
||||
else 0.0
|
||||
)
|
||||
|
||||
# Evaluate risk tier
|
||||
current_tier = self.config.risk_tier
|
||||
new_tier = self.evaluate_risk_tier(current_tier, metrics, reserve_pct)
|
||||
|
||||
if new_tier is not None and new_tier != current_tier:
|
||||
# Persist to risk_tier_history
|
||||
if self.pool is not None:
|
||||
try:
|
||||
await self.pool.execute(
|
||||
"INSERT INTO risk_tier_history "
|
||||
"(previous_tier, new_tier, trigger_source, trigger_metrics, created_at) "
|
||||
"VALUES ($1, $2, $3, $4, $5)",
|
||||
current_tier,
|
||||
new_tier,
|
||||
"auto_adjustment",
|
||||
json.dumps({
|
||||
"win_rate": metrics.win_rate,
|
||||
"current_drawdown_pct": metrics.current_drawdown_pct,
|
||||
"reserve_pct": reserve_pct,
|
||||
"sharpe_ratio": metrics.sharpe_ratio,
|
||||
}),
|
||||
datetime.now(tz=timezone.utc),
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not persist risk tier change")
|
||||
|
||||
# Update config and active tier
|
||||
self.config.risk_tier = new_tier
|
||||
self._active_risk_tier = RISK_TIER_DEFAULTS.get(
|
||||
new_tier, RISK_TIER_DEFAULTS["moderate"]
|
||||
)
|
||||
|
||||
# Create alert notification
|
||||
self.create_alert(
|
||||
"risk_tier_changed",
|
||||
f"Risk tier changed from {current_tier} to {new_tier} "
|
||||
f"(win_rate={metrics.win_rate:.2%}, "
|
||||
f"drawdown={metrics.current_drawdown_pct:.2%}, "
|
||||
f"reserve={reserve_pct:.2%})",
|
||||
)
|
||||
|
||||
logger.info(
|
||||
"Risk tier changed: %s → %s (win_rate=%.2f, drawdown=%.2f, reserve=%.2f)",
|
||||
current_tier,
|
||||
new_tier,
|
||||
metrics.win_rate,
|
||||
metrics.current_drawdown_pct,
|
||||
reserve_pct,
|
||||
)
|
||||
|
||||
except asyncio.CancelledError:
|
||||
break
|
||||
except Exception:
|
||||
logger.exception("Unexpected error in risk tier scheduler")
|
||||
if self.running:
|
||||
await asyncio.sleep(60)
|
||||
|
||||
async def _rebalance_scheduler(self) -> None:
|
||||
"""Evaluate portfolio rebalancing weekly at Monday 09:45 ET.
|
||||
|
||||
Task 30.2: Computes seconds until next Monday 09:45 ET, sleeps until
|
||||
then, loads positions and risk tier, calls evaluate_rebalancing(),
|
||||
and pushes rebalance orders to the broker queue.
|
||||
"""
|
||||
from services.trading.trading_window import ET, WINDOW_OPEN
|
||||
|
||||
while self.running:
|
||||
try:
|
||||
# Compute seconds until next Monday 09:45 ET
|
||||
now_utc = datetime.now(tz=timezone.utc)
|
||||
et_now = now_utc.astimezone(ET)
|
||||
|
||||
# Find next Monday
|
||||
days_until_monday = (7 - et_now.weekday()) % 7
|
||||
if days_until_monday == 0:
|
||||
# It's Monday — check if we're past 09:45
|
||||
target_today = et_now.replace(
|
||||
hour=WINDOW_OPEN.hour,
|
||||
minute=WINDOW_OPEN.minute,
|
||||
second=0,
|
||||
microsecond=0,
|
||||
)
|
||||
if et_now >= target_today:
|
||||
# Already past 09:45 on Monday — target next Monday
|
||||
days_until_monday = 7
|
||||
else:
|
||||
days_until_monday = 0
|
||||
|
||||
target = et_now.replace(
|
||||
hour=WINDOW_OPEN.hour,
|
||||
minute=WINDOW_OPEN.minute,
|
||||
second=0,
|
||||
microsecond=0,
|
||||
) + timedelta(days=days_until_monday)
|
||||
|
||||
sleep_seconds = (target - et_now).total_seconds()
|
||||
if sleep_seconds > 0:
|
||||
await asyncio.sleep(sleep_seconds)
|
||||
|
||||
if not self.running:
|
||||
break
|
||||
|
||||
# Respect circuit breaker status
|
||||
if self.circuit_breaker.is_active(self._cb_state, now=datetime.now(tz=timezone.utc)):
|
||||
logger.info("Rebalance skipped — circuit breaker is active")
|
||||
continue
|
||||
|
||||
if self.portfolio_state is None:
|
||||
continue
|
||||
|
||||
# Load current positions
|
||||
positions = self.portfolio_state.positions
|
||||
if self.pool is not None:
|
||||
try:
|
||||
positions = await self._load_open_positions()
|
||||
except Exception:
|
||||
logger.debug("Could not load positions for rebalancing")
|
||||
|
||||
if not positions:
|
||||
continue
|
||||
|
||||
# Evaluate rebalancing
|
||||
max_positions = (
|
||||
self.config.max_open_positions
|
||||
if hasattr(self.config, "max_open_positions")
|
||||
else 10
|
||||
)
|
||||
rebalance_orders = self.rebalancer.evaluate(
|
||||
positions,
|
||||
self._active_risk_tier,
|
||||
self.portfolio_state.active_pool,
|
||||
max_positions,
|
||||
)
|
||||
|
||||
# Push rebalance orders to broker queue
|
||||
for order in rebalance_orders:
|
||||
order_job = {
|
||||
"ticker": order.ticker,
|
||||
"action": order.action,
|
||||
"quantity": order.quantity,
|
||||
"order_type": "market",
|
||||
"source": "trading_engine",
|
||||
"reason": order.reason,
|
||||
"tag": order.tag,
|
||||
}
|
||||
if self.redis is not None:
|
||||
try:
|
||||
broker_queue = queue_key(QUEUE_BROKER)
|
||||
await self.redis.rpush(broker_queue, json.dumps(order_job))
|
||||
logger.info(
|
||||
"Rebalance: pushed %s order for %s (%d shares)",
|
||||
order.action,
|
||||
order.ticker,
|
||||
order.quantity,
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("Failed to push rebalance order for %s", order.ticker)
|
||||
else:
|
||||
logger.info(
|
||||
"Rebalance (no redis): %s %s %d shares — %s",
|
||||
order.action,
|
||||
order.ticker,
|
||||
order.quantity,
|
||||
order.reason,
|
||||
)
|
||||
|
||||
if rebalance_orders:
|
||||
logger.info("Rebalance cycle completed: %d orders generated", len(rebalance_orders))
|
||||
else:
|
||||
logger.debug("Rebalance cycle completed: no orders needed")
|
||||
|
||||
except asyncio.CancelledError:
|
||||
break
|
||||
except Exception:
|
||||
logger.exception("Unexpected error in rebalance scheduler")
|
||||
if self.running:
|
||||
await asyncio.sleep(60)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Async helpers
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def _persist_decision(self, decision: TradingDecision) -> None:
|
||||
"""INSERT a trading decision into the trading_decisions table.
|
||||
|
||||
Task 27.5: Handles pool=None gracefully (skip persistence, log only).
|
||||
"""
|
||||
logger.info(
|
||||
"Decision: %s %s ticker=%s reason=%s",
|
||||
decision.decision,
|
||||
decision.id[:8],
|
||||
decision.ticker,
|
||||
decision.skip_reason or "—",
|
||||
)
|
||||
|
||||
if self.pool is None:
|
||||
return
|
||||
|
||||
try:
|
||||
await self.pool.execute(
|
||||
"INSERT INTO trading_decisions "
|
||||
"(id, recommendation_id, decision, skip_reason, ticker, "
|
||||
"computed_position_size, computed_share_quantity, "
|
||||
"risk_tier_at_decision, portfolio_heat_at_decision, "
|
||||
"active_pool_at_decision, reserve_pool_at_decision, "
|
||||
"circuit_breaker_status, correlation_check_result, "
|
||||
"sector_exposure_check_result, earnings_proximity_flag, "
|
||||
"is_micro_trade, decision_trace, created_at) "
|
||||
"VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, "
|
||||
"$11, $12, $13, $14, $15, $16, $17, $18)",
|
||||
decision.id,
|
||||
decision.recommendation_id,
|
||||
decision.decision,
|
||||
decision.skip_reason,
|
||||
decision.ticker,
|
||||
decision.computed_position_size,
|
||||
decision.computed_share_quantity,
|
||||
decision.risk_tier_at_decision,
|
||||
decision.portfolio_heat_at_decision,
|
||||
decision.active_pool_at_decision,
|
||||
decision.reserve_pool_at_decision,
|
||||
decision.circuit_breaker_status,
|
||||
json.dumps(decision.correlation_check_result),
|
||||
json.dumps(decision.sector_exposure_check_result),
|
||||
decision.earnings_proximity_flag,
|
||||
decision.is_micro_trade,
|
||||
json.dumps(decision.decision_trace),
|
||||
decision.created_at,
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not persist decision %s — table may not exist", decision.id[:8])
|
||||
|
||||
async def _sync_positions_and_siphon(self) -> None:
|
||||
"""Sync positions from DB and siphon profit on closed positions.
|
||||
|
||||
Task 27.4: Fetches current positions, detects closes, and calls
|
||||
siphon_profit() for profitable closes.
|
||||
"""
|
||||
if self.pool is None or self.portfolio_state is None:
|
||||
return
|
||||
|
||||
try:
|
||||
positions = await self._load_open_positions()
|
||||
old_tickers = {p.ticker for p in self.portfolio_state.positions}
|
||||
new_tickers = {p.ticker for p in positions}
|
||||
|
||||
# Detect closed positions
|
||||
closed_tickers = old_tickers - new_tickers
|
||||
for ticker in closed_tickers:
|
||||
old_pos = next(
|
||||
(p for p in self.portfolio_state.positions if p.ticker == ticker),
|
||||
None,
|
||||
)
|
||||
if old_pos and old_pos.unrealized_pnl > 0:
|
||||
transfer, new_balance = self.reserve_pool_controller.siphon_profit(
|
||||
old_pos.unrealized_pnl,
|
||||
self.portfolio_state.reserve_pool,
|
||||
)
|
||||
if transfer > 0:
|
||||
self.portfolio_state.reserve_pool = new_balance
|
||||
# Persist to reserve_pool_ledger
|
||||
try:
|
||||
await self.pool.execute(
|
||||
"INSERT INTO reserve_pool_ledger "
|
||||
"(amount, balance_after, trigger_type, reference_id, notes, created_at) "
|
||||
"VALUES ($1, $2, 'profit_siphon', $3, $4, $5)",
|
||||
transfer,
|
||||
new_balance,
|
||||
ticker,
|
||||
f"Siphoned from {ticker} close",
|
||||
datetime.now(tz=timezone.utc),
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not persist siphon event for %s", ticker)
|
||||
|
||||
logger.info(
|
||||
"Siphoned $%.2f from %s close → reserve now $%.2f",
|
||||
transfer,
|
||||
ticker,
|
||||
new_balance,
|
||||
)
|
||||
|
||||
# Update portfolio state
|
||||
self.portfolio_state.positions = positions
|
||||
self.portfolio_state.open_position_count = len(positions)
|
||||
|
||||
except Exception:
|
||||
logger.exception("Error syncing positions")
|
||||
|
||||
async def _fetch_current_prices(self, tickers: list[str]) -> dict[str, float]:
|
||||
"""Fetch latest prices from Polygon API for the given tickers.
|
||||
|
||||
Task 28.2: Uses httpx for async HTTP calls. Returns a dict mapping
|
||||
ticker → latest price. Handles API errors gracefully.
|
||||
"""
|
||||
if not tickers:
|
||||
return {}
|
||||
|
||||
prices: dict[str, float] = {}
|
||||
|
||||
# Use the market data config for API key
|
||||
api_key = ""
|
||||
base_url = "https://api.polygon.io"
|
||||
try:
|
||||
from services.shared.config import load_config
|
||||
app_config = load_config()
|
||||
api_key = app_config.market_data.api_key
|
||||
base_url = app_config.market_data.base_url
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
if not api_key:
|
||||
logger.debug("No Polygon API key configured — skipping price fetch")
|
||||
return prices
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10.0) as client:
|
||||
# Use the grouped daily endpoint or snapshot for multiple tickers
|
||||
tickers_str = ",".join(tickers)
|
||||
url = f"{base_url}/v2/snapshot/locale/us/markets/stocks/tickers"
|
||||
params = {"tickers": tickers_str, "apiKey": api_key}
|
||||
|
||||
resp = await client.get(url, params=params)
|
||||
if resp.status_code == 200:
|
||||
data = resp.json()
|
||||
for item in data.get("tickers", []):
|
||||
t = item.get("ticker", "")
|
||||
last_trade = item.get("lastTrade", {})
|
||||
price = last_trade.get("p", 0.0)
|
||||
if t and price > 0:
|
||||
prices[t] = price
|
||||
else:
|
||||
logger.warning("Polygon API returned status %d", resp.status_code)
|
||||
except Exception:
|
||||
logger.warning("Failed to fetch prices from Polygon API")
|
||||
|
||||
return prices
|
||||
|
||||
async def _load_open_positions(self) -> list[OpenPosition]:
|
||||
"""Load open positions from the database.
|
||||
|
||||
Task 28.3: Queries the position_stop_levels table for active positions.
|
||||
Returns typed OpenPosition list.
|
||||
"""
|
||||
if self.pool is None:
|
||||
return []
|
||||
|
||||
positions: list[OpenPosition] = []
|
||||
try:
|
||||
rows = await self.pool.fetch(
|
||||
"SELECT ticker, entry_price, stop_loss_price, take_profit_price, "
|
||||
"signal_confidence, is_micro_trade "
|
||||
"FROM position_stop_levels WHERE active = TRUE"
|
||||
)
|
||||
for row in rows:
|
||||
positions.append(
|
||||
OpenPosition(
|
||||
ticker=row["ticker"],
|
||||
quantity=1, # Default; real quantity from orders table
|
||||
entry_price=float(row["entry_price"]),
|
||||
current_price=float(row["entry_price"]),
|
||||
unrealized_pnl=0.0,
|
||||
market_value=float(row["entry_price"]),
|
||||
sector="",
|
||||
stop_loss_price=float(row["stop_loss_price"]),
|
||||
take_profit_price=float(row["take_profit_price"]),
|
||||
signal_confidence=float(row["signal_confidence"]),
|
||||
is_micro_trade=bool(row["is_micro_trade"]),
|
||||
)
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not load open positions — table may not exist")
|
||||
|
||||
return positions
|
||||
|
||||
async def _load_stop_levels(self) -> dict[str, StopLevels]:
|
||||
"""Load active stop-loss/take-profit levels from the database.
|
||||
|
||||
Task 28.3: Queries position_stop_levels WHERE active = TRUE.
|
||||
Returns dict keyed by ticker.
|
||||
"""
|
||||
if self.pool is None:
|
||||
return {}
|
||||
|
||||
levels: dict[str, StopLevels] = {}
|
||||
try:
|
||||
rows = await self.pool.fetch(
|
||||
"SELECT ticker, stop_loss_price, take_profit_price, "
|
||||
"trailing_stop_active, atr_value, atr_multiplier, "
|
||||
"reward_risk_ratio, updated_at "
|
||||
"FROM position_stop_levels WHERE active = TRUE"
|
||||
)
|
||||
for row in rows:
|
||||
levels[row["ticker"]] = StopLevels(
|
||||
stop_loss_price=float(row["stop_loss_price"]),
|
||||
take_profit_price=float(row["take_profit_price"]),
|
||||
trailing_stop_active=bool(row["trailing_stop_active"]),
|
||||
atr_value=float(row["atr_value"]),
|
||||
atr_multiplier=float(row["atr_multiplier"]),
|
||||
reward_risk_ratio=float(row["reward_risk_ratio"]),
|
||||
)
|
||||
return levels
|
||||
except Exception:
|
||||
logger.debug("Could not load stop levels — table may not exist")
|
||||
return {}
|
||||
|
||||
async def _submit_sell_order(
|
||||
self, ticker: str, quantity: int, reason: str
|
||||
) -> None:
|
||||
"""Push a sell order to the broker queue via Redis."""
|
||||
order_job = {
|
||||
"ticker": ticker,
|
||||
"action": "sell",
|
||||
"quantity": quantity,
|
||||
"order_type": "market",
|
||||
"source": "trading_engine",
|
||||
"reason": reason,
|
||||
}
|
||||
if self.redis is not None:
|
||||
try:
|
||||
broker_queue = queue_key(QUEUE_BROKER)
|
||||
await self.redis.rpush(broker_queue, json.dumps(order_job))
|
||||
logger.info("Submitted sell order for %s (%d shares): %s", ticker, quantity, reason)
|
||||
except Exception:
|
||||
logger.exception("Failed to push sell order for %s", ticker)
|
||||
else:
|
||||
logger.info("Sell order (no redis): %s %d shares — %s", ticker, quantity, reason)
|
||||
|
||||
async def _persist_daily_snapshot(self, now: datetime) -> None:
|
||||
"""Persist end-of-day portfolio snapshot to portfolio_snapshots table.
|
||||
|
||||
Task 29.2: Called after 4:00 PM ET when market closes.
|
||||
"""
|
||||
if self.pool is None or self.portfolio_state is None:
|
||||
return
|
||||
|
||||
from services.trading.trading_window import ET
|
||||
et_now = now.astimezone(ET)
|
||||
snapshot_date = et_now.date()
|
||||
|
||||
try:
|
||||
await self.pool.execute(
|
||||
"INSERT INTO portfolio_snapshots "
|
||||
"(snapshot_date, portfolio_value, active_pool, reserve_pool, "
|
||||
"daily_return, cumulative_return, unrealized_pnl, realized_pnl, "
|
||||
"win_count, loss_count, win_rate, sharpe_ratio, max_drawdown, "
|
||||
"current_drawdown_pct, portfolio_heat, risk_tier, "
|
||||
"positions, metrics, created_at) "
|
||||
"VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, "
|
||||
"$11, $12, $13, $14, $15, $16, $17, $18, $19) "
|
||||
"ON CONFLICT (snapshot_date) DO UPDATE SET "
|
||||
"portfolio_value = EXCLUDED.portfolio_value, "
|
||||
"active_pool = EXCLUDED.active_pool, "
|
||||
"reserve_pool = EXCLUDED.reserve_pool, "
|
||||
"updated_at = NOW()",
|
||||
snapshot_date,
|
||||
self.portfolio_state.total_value,
|
||||
self.portfolio_state.active_pool,
|
||||
self.portfolio_state.reserve_pool,
|
||||
0.0, # daily_return
|
||||
0.0, # cumulative_return
|
||||
sum(p.unrealized_pnl for p in self.portfolio_state.positions),
|
||||
0.0, # realized_pnl
|
||||
0, # win_count
|
||||
0, # loss_count
|
||||
0.0, # win_rate
|
||||
0.0, # sharpe_ratio
|
||||
0.0, # max_drawdown
|
||||
0.0, # current_drawdown_pct
|
||||
self.portfolio_state.portfolio_heat,
|
||||
self.config.risk_tier,
|
||||
json.dumps([]), # positions
|
||||
json.dumps({}), # metrics
|
||||
now,
|
||||
)
|
||||
logger.info("Persisted daily snapshot for %s", snapshot_date)
|
||||
except Exception:
|
||||
logger.debug("Could not persist daily snapshot — table may not exist")
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Decision builders
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
@@ -0,0 +1,348 @@
|
||||
"""Notification dispatch for the autonomous trading engine.
|
||||
|
||||
Handles actual delivery of notifications via AWS SNS (SMS) and Gmail API
|
||||
(email), with rate limiting via Redis, retry with exponential backoff,
|
||||
and persistence to the notifications table.
|
||||
|
||||
Task 31: Wire notification dispatch.
|
||||
|
||||
boto3 and google-api-python-client are optional dependencies — the module
|
||||
logs a warning and degrades gracefully if they are not installed.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
from datetime import datetime, timedelta, timezone
|
||||
|
||||
from services.shared.config import TradingConfig
|
||||
from services.shared.redis_keys import trading_notification_rate_key
|
||||
|
||||
logger = logging.getLogger("trading_engine.notifications")
|
||||
|
||||
# Conditionally import boto3
|
||||
try:
|
||||
import boto3
|
||||
|
||||
_HAS_BOTO3 = True
|
||||
except ImportError:
|
||||
_HAS_BOTO3 = False
|
||||
logger.info("boto3 not installed — SNS notifications disabled")
|
||||
|
||||
# Conditionally import Google API client
|
||||
try:
|
||||
import base64
|
||||
from email.mime.text import MIMEText
|
||||
|
||||
from google.oauth2.credentials import Credentials
|
||||
from googleapiclient.discovery import build as google_build
|
||||
|
||||
_HAS_GOOGLE = True
|
||||
except ImportError:
|
||||
_HAS_GOOGLE = False
|
||||
logger.info("google-api-python-client not installed — Gmail notifications disabled")
|
||||
|
||||
|
||||
class NotificationDispatcher:
|
||||
"""Routes notification delivery to enabled channels.
|
||||
|
||||
Accepts pool (asyncpg), redis (redis.asyncio), and TradingConfig.
|
||||
Persists every notification attempt to the ``notifications`` table.
|
||||
Rate-limits via Redis counters with 1-hour TTL.
|
||||
Retries failed deliveries with exponential backoff (1s, 2s, 4s).
|
||||
"""
|
||||
|
||||
# Rate limits per hour
|
||||
SMS_RATE_LIMIT = 10
|
||||
EMAIL_RATE_LIMIT = 20
|
||||
|
||||
# Retry config
|
||||
MAX_RETRIES = 3
|
||||
RETRY_DELAYS = [1, 2, 4] # seconds
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
pool: object,
|
||||
redis: object,
|
||||
config: TradingConfig,
|
||||
) -> None:
|
||||
self.pool = pool
|
||||
self.redis = redis
|
||||
self.config = config
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Public API
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def dispatch(self, event_type: str, message: str) -> None:
|
||||
"""Route notification to all enabled channels.
|
||||
|
||||
Runs delivery in a background task so it never blocks trading.
|
||||
"""
|
||||
asyncio.create_task(self._dispatch_impl(event_type, message))
|
||||
|
||||
async def _dispatch_impl(self, event_type: str, message: str) -> None:
|
||||
"""Internal dispatch — sends to enabled channels."""
|
||||
# SNS (SMS)
|
||||
if self.config.sns_topic_arn:
|
||||
await self._deliver_with_retry("sms", event_type, message, self._send_sns)
|
||||
|
||||
# Gmail (email)
|
||||
if self.config.gmail_recipient:
|
||||
await self._deliver_with_retry("email", event_type, message, self._send_gmail)
|
||||
|
||||
async def _deliver_with_retry(
|
||||
self,
|
||||
channel: str,
|
||||
event_type: str,
|
||||
message: str,
|
||||
send_fn,
|
||||
) -> None:
|
||||
"""Deliver with rate limiting and exponential backoff retry."""
|
||||
# Rate limit check
|
||||
if not await self._check_rate_limit(channel):
|
||||
await self._persist_notification(
|
||||
channel, event_type, message, "rate_limited"
|
||||
)
|
||||
logger.info("Notification rate-limited: channel=%s event=%s", channel, event_type)
|
||||
return
|
||||
|
||||
last_error = ""
|
||||
for attempt in range(self.MAX_RETRIES):
|
||||
try:
|
||||
await send_fn(event_type, message)
|
||||
# Success — increment rate counter and persist
|
||||
await self._increment_rate_counter(channel)
|
||||
await self._persist_notification(
|
||||
channel, event_type, message, "delivered"
|
||||
)
|
||||
return
|
||||
except Exception as exc:
|
||||
last_error = str(exc)
|
||||
logger.warning(
|
||||
"Notification delivery failed (attempt %d/%d): %s",
|
||||
attempt + 1,
|
||||
self.MAX_RETRIES,
|
||||
last_error,
|
||||
)
|
||||
if attempt < self.MAX_RETRIES - 1:
|
||||
await asyncio.sleep(self.RETRY_DELAYS[attempt])
|
||||
|
||||
# All retries exhausted
|
||||
await self._persist_notification(
|
||||
channel,
|
||||
event_type,
|
||||
message,
|
||||
"failed",
|
||||
retry_count=self.MAX_RETRIES,
|
||||
error_message=last_error,
|
||||
)
|
||||
logger.error(
|
||||
"Notification delivery failed after %d retries: channel=%s event=%s error=%s",
|
||||
self.MAX_RETRIES,
|
||||
channel,
|
||||
event_type,
|
||||
last_error,
|
||||
)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Channel implementations
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def _send_sns(self, event_type: str, message: str) -> None:
|
||||
"""Send SMS via AWS SNS."""
|
||||
if not _HAS_BOTO3:
|
||||
raise RuntimeError("boto3 is not installed — cannot send SNS notification")
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
# Run boto3 call in executor to avoid blocking the event loop
|
||||
await loop.run_in_executor(None, self._send_sns_sync, event_type, message)
|
||||
|
||||
def _send_sns_sync(self, event_type: str, message: str) -> None:
|
||||
"""Synchronous SNS publish (runs in executor)."""
|
||||
client = boto3.client("sns")
|
||||
subject = f"[Stonks] {event_type.replace('_', ' ').title()}"
|
||||
|
||||
if self.config.sns_topic_arn:
|
||||
client.publish(
|
||||
TopicArn=self.config.sns_topic_arn,
|
||||
Message=message,
|
||||
Subject=subject[:100], # SNS subject max 100 chars
|
||||
)
|
||||
|
||||
if self.config.sns_phone_number:
|
||||
client.publish(
|
||||
PhoneNumber=self.config.sns_phone_number,
|
||||
Message=message[:160], # SMS max 160 chars
|
||||
)
|
||||
|
||||
async def _send_gmail(self, event_type: str, message: str) -> None:
|
||||
"""Send email via Gmail API."""
|
||||
if not _HAS_GOOGLE:
|
||||
raise RuntimeError(
|
||||
"google-api-python-client not installed — cannot send Gmail notification"
|
||||
)
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
await loop.run_in_executor(None, self._send_gmail_sync, event_type, message)
|
||||
|
||||
def _send_gmail_sync(self, event_type: str, message: str) -> None:
|
||||
"""Synchronous Gmail send (runs in executor)."""
|
||||
import os
|
||||
|
||||
refresh_token = os.getenv("GMAIL_REFRESH_TOKEN", "")
|
||||
client_id = os.getenv("GMAIL_CLIENT_ID", "")
|
||||
client_secret = os.getenv("GMAIL_CLIENT_SECRET", "")
|
||||
|
||||
if not all([refresh_token, client_id, client_secret]):
|
||||
raise RuntimeError("Gmail OAuth2 credentials not configured")
|
||||
|
||||
creds = Credentials(
|
||||
token=None,
|
||||
refresh_token=refresh_token,
|
||||
client_id=client_id,
|
||||
client_secret=client_secret,
|
||||
token_uri="https://oauth2.googleapis.com/token",
|
||||
)
|
||||
|
||||
service = google_build("gmail", "v1", credentials=creds)
|
||||
|
||||
subject = f"[Stonks Alert] {event_type.replace('_', ' ').title()}"
|
||||
mime_msg = MIMEText(message)
|
||||
mime_msg["to"] = self.config.gmail_recipient
|
||||
mime_msg["from"] = self.config.gmail_sender or "me"
|
||||
mime_msg["subject"] = subject
|
||||
|
||||
raw = base64.urlsafe_b64encode(mime_msg.as_bytes()).decode()
|
||||
service.users().messages().send(
|
||||
userId="me", body={"raw": raw}
|
||||
).execute()
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Rate limiting via Redis
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def _check_rate_limit(self, channel: str) -> bool:
|
||||
"""Return True if the channel is within its rate limit."""
|
||||
if self.redis is None:
|
||||
return True # No Redis — allow all
|
||||
|
||||
limit = self.SMS_RATE_LIMIT if channel == "sms" else self.EMAIL_RATE_LIMIT
|
||||
key = trading_notification_rate_key(channel)
|
||||
|
||||
try:
|
||||
count = await self.redis.get(key)
|
||||
if count is not None and int(count) >= limit:
|
||||
return False
|
||||
except Exception:
|
||||
logger.debug("Could not check rate limit — allowing notification")
|
||||
|
||||
return True
|
||||
|
||||
async def _increment_rate_counter(self, channel: str) -> None:
|
||||
"""Increment the hourly rate counter for a channel."""
|
||||
if self.redis is None:
|
||||
return
|
||||
|
||||
key = trading_notification_rate_key(channel)
|
||||
try:
|
||||
pipe = self.redis.pipeline()
|
||||
pipe.incr(key)
|
||||
pipe.expire(key, 3600) # 1-hour TTL
|
||||
await pipe.execute()
|
||||
except Exception:
|
||||
logger.debug("Could not increment rate counter for %s", channel)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Persistence
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def _persist_notification(
|
||||
self,
|
||||
channel: str,
|
||||
event_type: str,
|
||||
message: str,
|
||||
delivery_status: str,
|
||||
retry_count: int = 0,
|
||||
error_message: str | None = None,
|
||||
) -> None:
|
||||
"""Persist notification record to the notifications table."""
|
||||
if self.pool is None:
|
||||
return
|
||||
|
||||
try:
|
||||
now = datetime.now(tz=timezone.utc)
|
||||
delivered_at = now if delivery_status == "delivered" else None
|
||||
|
||||
await self.pool.execute(
|
||||
"INSERT INTO notifications "
|
||||
"(channel, event_type, message, delivery_status, "
|
||||
"retry_count, error_message, created_at, delivered_at) "
|
||||
"VALUES ($1, $2, $3, $4, $5, $6, $7, $8)",
|
||||
channel,
|
||||
event_type,
|
||||
message[:2000], # Truncate long messages
|
||||
delivery_status,
|
||||
retry_count,
|
||||
error_message,
|
||||
now,
|
||||
delivered_at,
|
||||
)
|
||||
except Exception:
|
||||
logger.debug("Could not persist notification record")
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Daily summary scheduler
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
async def daily_summary_scheduler(self, engine) -> None:
|
||||
"""Sleep until 16:30 ET each trading day and dispatch a daily summary.
|
||||
|
||||
Task 31.6: Runs as a background coroutine.
|
||||
"""
|
||||
from services.trading.trading_window import ET
|
||||
|
||||
while engine.running:
|
||||
try:
|
||||
now_utc = datetime.now(tz=timezone.utc)
|
||||
et_now = now_utc.astimezone(ET)
|
||||
|
||||
# Target 16:30 ET
|
||||
target = et_now.replace(hour=16, minute=30, second=0, microsecond=0)
|
||||
if et_now >= target:
|
||||
target += timedelta(days=1)
|
||||
|
||||
# Skip weekends
|
||||
while target.weekday() > 4:
|
||||
target += timedelta(days=1)
|
||||
|
||||
sleep_seconds = (target - et_now).total_seconds()
|
||||
if sleep_seconds > 0:
|
||||
await asyncio.sleep(sleep_seconds)
|
||||
|
||||
if not engine.running:
|
||||
break
|
||||
|
||||
# Build summary message
|
||||
summary_parts = ["Daily Trading Summary"]
|
||||
if engine.portfolio_state is not None:
|
||||
ps = engine.portfolio_state
|
||||
summary_parts.extend([
|
||||
f"Portfolio Value: ${ps.total_value:,.2f}",
|
||||
f"Active Pool: ${ps.active_pool:,.2f}",
|
||||
f"Reserve Pool: ${ps.reserve_pool:,.2f}",
|
||||
f"Open Positions: {ps.open_position_count}",
|
||||
f"Portfolio Heat: {ps.portfolio_heat:.2%}",
|
||||
f"Risk Tier: {engine.config.risk_tier}",
|
||||
])
|
||||
|
||||
summary_message = " | ".join(summary_parts)
|
||||
await self.dispatch("daily_summary", summary_message)
|
||||
|
||||
except asyncio.CancelledError:
|
||||
break
|
||||
except Exception:
|
||||
logger.exception("Error in daily summary scheduler")
|
||||
if engine.running:
|
||||
await asyncio.sleep(60)
|
||||
Reference in New Issue
Block a user