feat: link decision outcomes to trades via decision_id (issue #92)
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Add decision_id column to trades table, capture log_decision() return value, and update original BUY decision outcome on SELL execution. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
35
src/db.py
35
src/db.py
@@ -6,6 +6,7 @@ import json
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import sqlite3
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from datetime import UTC, datetime
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from pathlib import Path
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from typing import Any
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def init_db(db_path: str) -> sqlite3.Connection:
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@@ -26,7 +27,8 @@ def init_db(db_path: str) -> sqlite3.Connection:
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price REAL,
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pnl REAL DEFAULT 0.0,
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market TEXT DEFAULT 'KR',
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exchange_code TEXT DEFAULT 'KRX'
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exchange_code TEXT DEFAULT 'KRX',
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decision_id TEXT
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)
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"""
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)
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@@ -41,6 +43,8 @@ def init_db(db_path: str) -> sqlite3.Connection:
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conn.execute("ALTER TABLE trades ADD COLUMN exchange_code TEXT DEFAULT 'KRX'")
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if "selection_context" not in columns:
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conn.execute("ALTER TABLE trades ADD COLUMN selection_context TEXT")
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if "decision_id" not in columns:
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conn.execute("ALTER TABLE trades ADD COLUMN decision_id TEXT")
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# Context tree tables for multi-layered memory management
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conn.execute(
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@@ -143,6 +147,7 @@ def log_trade(
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market: str = "KR",
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exchange_code: str = "KRX",
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selection_context: dict[str, any] | None = None,
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decision_id: str | None = None,
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) -> None:
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"""Insert a trade record into the database.
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@@ -166,9 +171,9 @@ def log_trade(
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"""
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INSERT INTO trades (
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timestamp, stock_code, action, confidence, rationale,
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quantity, price, pnl, market, exchange_code, selection_context
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quantity, price, pnl, market, exchange_code, selection_context, decision_id
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)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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""",
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(
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datetime.now(UTC).isoformat(),
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@@ -182,6 +187,30 @@ def log_trade(
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market,
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exchange_code,
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context_json,
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decision_id,
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),
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)
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conn.commit()
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def get_latest_buy_trade(
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conn: sqlite3.Connection, stock_code: str, market: str
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) -> dict[str, Any] | None:
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"""Fetch the most recent BUY trade for a stock and market."""
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cursor = conn.execute(
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"""
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SELECT decision_id, price, quantity
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FROM trades
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WHERE stock_code = ?
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AND market = ?
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AND action = 'BUY'
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AND decision_id IS NOT NULL
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ORDER BY timestamp DESC
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LIMIT 1
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""",
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(stock_code, market),
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)
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row = cursor.fetchone()
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if not row:
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return None
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return {"decision_id": row[0], "price": row[1], "quantity": row[2]}
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44
src/main.py
44
src/main.py
@@ -26,7 +26,7 @@ from src.context.store import ContextStore
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from src.core.criticality import CriticalityAssessor
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from src.core.priority_queue import PriorityTaskQueue
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from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected, RiskManager
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from src.db import init_db, log_trade
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from src.db import get_latest_buy_trade, init_db, log_trade
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from src.logging.decision_logger import DecisionLogger
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from src.logging_config import setup_logging
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from src.markets.schedule import MarketInfo, get_next_market_open, get_open_markets
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@@ -279,7 +279,7 @@ async def trading_cycle(
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"pnl_pct": pnl_pct,
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}
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decision_logger.log_decision(
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decision_id = decision_logger.log_decision(
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stock_code=stock_code,
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market=market.code,
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exchange_code=market.exchange_code,
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@@ -291,6 +291,9 @@ async def trading_cycle(
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)
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# 3. Execute if actionable
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quantity = 0
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trade_price = current_price
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trade_pnl = 0.0
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if decision.action in ("BUY", "SELL"):
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# Determine order size (simplified: 1 lot)
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quantity = 1
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@@ -346,6 +349,18 @@ async def trading_cycle(
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except Exception as exc:
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logger.warning("Telegram notification failed: %s", exc)
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if decision.action == "SELL":
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buy_trade = get_latest_buy_trade(db_conn, stock_code, market.code)
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if buy_trade and buy_trade.get("price") is not None:
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buy_price = float(buy_trade["price"])
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buy_qty = int(buy_trade.get("quantity") or 1)
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trade_pnl = (trade_price - buy_price) * buy_qty
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decision_logger.update_outcome(
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decision_id=buy_trade["decision_id"],
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pnl=trade_pnl,
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accuracy=1 if trade_pnl > 0 else 0,
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)
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# 6. Log trade with selection context
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selection_context = None
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if stock_code in market_candidates:
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@@ -363,9 +378,13 @@ async def trading_cycle(
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action=decision.action,
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confidence=decision.confidence,
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rationale=decision.rationale,
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quantity=quantity,
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price=trade_price,
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pnl=trade_pnl,
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market=market.code,
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exchange_code=market.exchange_code,
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selection_context=selection_context,
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decision_id=decision_id,
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)
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# 7. Latency monitoring
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@@ -600,7 +619,7 @@ async def run_daily_session(
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"pnl_pct": pnl_pct,
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}
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decision_logger.log_decision(
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decision_id = decision_logger.log_decision(
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stock_code=stock_code,
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market=market.code,
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exchange_code=market.exchange_code,
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@@ -612,6 +631,9 @@ async def run_daily_session(
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)
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# Execute if actionable
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quantity = 0
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trade_price = stock_data["current_price"]
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trade_pnl = 0.0
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if decision.action in ("BUY", "SELL"):
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quantity = 1
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order_amount = stock_data["current_price"] * quantity
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@@ -684,6 +706,18 @@ async def run_daily_session(
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)
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continue
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if decision.action == "SELL":
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buy_trade = get_latest_buy_trade(db_conn, stock_code, market.code)
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if buy_trade and buy_trade.get("price") is not None:
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buy_price = float(buy_trade["price"])
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buy_qty = int(buy_trade.get("quantity") or 1)
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trade_pnl = (trade_price - buy_price) * buy_qty
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decision_logger.update_outcome(
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decision_id=buy_trade["decision_id"],
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pnl=trade_pnl,
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accuracy=1 if trade_pnl > 0 else 0,
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)
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# Log trade
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log_trade(
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conn=db_conn,
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@@ -691,8 +725,12 @@ async def run_daily_session(
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action=decision.action,
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confidence=decision.confidence,
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rationale=decision.rationale,
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quantity=quantity,
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price=trade_price,
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pnl=trade_pnl,
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market=market.code,
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exchange_code=market.exchange_code,
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decision_id=decision_id,
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)
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logger.info("Daily trading session completed")
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