The-Ouroboros/tests/test_daily_review.py

"""Tests for DailyReviewer."""

from __future__ import annotations

import json
import sqlite3
from types import SimpleNamespace
from unittest.mock import AsyncMock, MagicMock

import pytest

from src.context.layer import ContextLayer
from src.context.store import ContextStore
from src.db import init_db, log_trade
from src.evolution.daily_review import DailyReviewer
from src.evolution.scorecard import DailyScorecard
from src.logging.decision_logger import DecisionLogger

from datetime import UTC, datetime

TODAY = datetime.now(UTC).strftime("%Y-%m-%d")


@pytest.fixture
def db_conn() -> sqlite3.Connection:
    return init_db(":memory:")


@pytest.fixture
def context_store(db_conn: sqlite3.Connection) -> ContextStore:
    return ContextStore(db_conn)


def _log_decision(
    logger: DecisionLogger,
    *,
    stock_code: str,
    market: str,
    action: str,
    confidence: int,
    scenario_match: dict[str, float] | None = None,
) -> str:
    return logger.log_decision(
        stock_code=stock_code,
        market=market,
        exchange_code="KRX" if market == "KR" else "NASDAQ",
        action=action,
        confidence=confidence,
        rationale="test",
        context_snapshot={"scenario_match": scenario_match or {}},
        input_data={"stock_code": stock_code},
    )


def test_generate_scorecard_market_scoped(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    reviewer = DailyReviewer(db_conn, context_store)
    logger = DecisionLogger(db_conn)

    buy_id = _log_decision(
        logger,
        stock_code="005930",
        market="KR",
        action="BUY",
        confidence=90,
        scenario_match={"rsi": 29.0},
    )
    _log_decision(
        logger,
        stock_code="000660",
        market="KR",
        action="HOLD",
        confidence=60,
    )
    _log_decision(
        logger,
        stock_code="AAPL",
        market="US",
        action="SELL",
        confidence=80,
        scenario_match={"volume_ratio": 2.1},
    )

    log_trade(
        db_conn,
        "005930",
        "BUY",
        90,
        "buy",
        quantity=1,
        price=100.0,
        pnl=10.0,
        market="KR",
        exchange_code="KRX",
        decision_id=buy_id,
    )
    log_trade(
        db_conn,
        "000660",
        "HOLD",
        60,
        "hold",
        quantity=0,
        price=0.0,
        pnl=0.0,
        market="KR",
        exchange_code="KRX",
    )
    log_trade(
        db_conn,
        "AAPL",
        "SELL",
        80,
        "sell",
        quantity=1,
        price=200.0,
        pnl=-5.0,
        market="US",
        exchange_code="NASDAQ",
    )

    scorecard = reviewer.generate_scorecard(TODAY, "KR")

    assert scorecard.market == "KR"
    assert scorecard.total_decisions == 2
    assert scorecard.buys == 1
    assert scorecard.sells == 0
    assert scorecard.holds == 1
    assert scorecard.total_pnl == 10.0
    assert scorecard.win_rate == 100.0
    assert scorecard.avg_confidence == 75.0
    assert scorecard.scenario_match_rate == 50.0


def test_generate_scorecard_top_winners_and_losers(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    reviewer = DailyReviewer(db_conn, context_store)
    logger = DecisionLogger(db_conn)

    for code, pnl in [("005930", 30.0), ("000660", 10.0), ("035420", -15.0), ("051910", -5.0)]:
        decision_id = _log_decision(
            logger,
            stock_code=code,
            market="KR",
            action="BUY" if pnl >= 0 else "SELL",
            confidence=80,
            scenario_match={"rsi": 30.0},
        )
        log_trade(
            db_conn,
            code,
            "BUY" if pnl >= 0 else "SELL",
            80,
            "test",
            quantity=1,
            price=100.0,
            pnl=pnl,
            market="KR",
            exchange_code="KRX",
            decision_id=decision_id,
        )

    scorecard = reviewer.generate_scorecard(TODAY, "KR")
    assert scorecard.top_winners == ["005930", "000660"]
    assert scorecard.top_losers == ["035420", "051910"]


def test_generate_scorecard_empty_day(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    reviewer = DailyReviewer(db_conn, context_store)
    scorecard = reviewer.generate_scorecard(TODAY, "KR")

    assert scorecard.total_decisions == 0
    assert scorecard.total_pnl == 0.0
    assert scorecard.win_rate == 0.0
    assert scorecard.avg_confidence == 0.0
    assert scorecard.scenario_match_rate == 0.0
    assert scorecard.top_winners == []
    assert scorecard.top_losers == []


@pytest.mark.asyncio
async def test_generate_lessons_without_gemini_returns_empty(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    reviewer = DailyReviewer(db_conn, context_store, gemini_client=None)
    lessons = await reviewer.generate_lessons(
        DailyScorecard(
            date="2026-02-14",
            market="KR",
            total_decisions=1,
            buys=1,
            sells=0,
            holds=0,
            total_pnl=5.0,
            win_rate=100.0,
            avg_confidence=90.0,
            scenario_match_rate=100.0,
        )
    )
    assert lessons == []


@pytest.mark.asyncio
async def test_generate_lessons_parses_json_array(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    mock_gemini = MagicMock()
    mock_gemini.decide = AsyncMock(
        return_value=SimpleNamespace(rationale='["Cut losers earlier", "Reduce midday churn"]')
    )
    reviewer = DailyReviewer(db_conn, context_store, gemini_client=mock_gemini)

    lessons = await reviewer.generate_lessons(
        DailyScorecard(
            date="2026-02-14",
            market="KR",
            total_decisions=3,
            buys=1,
            sells=1,
            holds=1,
            total_pnl=-2.5,
            win_rate=50.0,
            avg_confidence=70.0,
            scenario_match_rate=66.7,
        )
    )
    assert lessons == ["Cut losers earlier", "Reduce midday churn"]


@pytest.mark.asyncio
async def test_generate_lessons_fallback_to_lines(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    mock_gemini = MagicMock()
    mock_gemini.decide = AsyncMock(
        return_value=SimpleNamespace(rationale="- Keep risk tighter\n- Increase selectivity")
    )
    reviewer = DailyReviewer(db_conn, context_store, gemini_client=mock_gemini)

    lessons = await reviewer.generate_lessons(
        DailyScorecard(
            date="2026-02-14",
            market="US",
            total_decisions=2,
            buys=1,
            sells=1,
            holds=0,
            total_pnl=1.0,
            win_rate=50.0,
            avg_confidence=75.0,
            scenario_match_rate=100.0,
        )
    )
    assert lessons == ["Keep risk tighter", "Increase selectivity"]


@pytest.mark.asyncio
async def test_generate_lessons_handles_gemini_error(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    mock_gemini = MagicMock()
    mock_gemini.decide = AsyncMock(side_effect=RuntimeError("boom"))
    reviewer = DailyReviewer(db_conn, context_store, gemini_client=mock_gemini)

    lessons = await reviewer.generate_lessons(
        DailyScorecard(
            date="2026-02-14",
            market="US",
            total_decisions=0,
            buys=0,
            sells=0,
            holds=0,
            total_pnl=0.0,
            win_rate=0.0,
            avg_confidence=0.0,
            scenario_match_rate=0.0,
        )
    )
    assert lessons == []


def test_store_scorecard_in_context(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    reviewer = DailyReviewer(db_conn, context_store)
    scorecard = DailyScorecard(
        date="2026-02-14",
        market="KR",
        total_decisions=5,
        buys=2,
        sells=1,
        holds=2,
        total_pnl=15.0,
        win_rate=66.67,
        avg_confidence=82.0,
        scenario_match_rate=80.0,
        lessons=["Keep position sizing stable"],
        cross_market_note="US risk-off",
    )

    reviewer.store_scorecard_in_context(scorecard)

    stored = context_store.get_context(
        ContextLayer.L6_DAILY,
        "2026-02-14",
        "scorecard_KR",
    )
    assert stored is not None
    assert stored["market"] == "KR"
    assert stored["total_pnl"] == 15.0
    assert stored["lessons"] == ["Keep position sizing stable"]


def test_store_scorecard_key_is_market_scoped(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    reviewer = DailyReviewer(db_conn, context_store)
    kr = DailyScorecard(
        date="2026-02-14",
        market="KR",
        total_decisions=1,
        buys=1,
        sells=0,
        holds=0,
        total_pnl=1.0,
        win_rate=100.0,
        avg_confidence=90.0,
        scenario_match_rate=100.0,
    )
    us = DailyScorecard(
        date="2026-02-14",
        market="US",
        total_decisions=1,
        buys=0,
        sells=1,
        holds=0,
        total_pnl=-1.0,
        win_rate=0.0,
        avg_confidence=70.0,
        scenario_match_rate=100.0,
    )

    reviewer.store_scorecard_in_context(kr)
    reviewer.store_scorecard_in_context(us)

    kr_ctx = context_store.get_context(ContextLayer.L6_DAILY, "2026-02-14", "scorecard_KR")
    us_ctx = context_store.get_context(ContextLayer.L6_DAILY, "2026-02-14", "scorecard_US")

    assert kr_ctx["market"] == "KR"
    assert us_ctx["market"] == "US"
    assert kr_ctx["total_pnl"] == 1.0
    assert us_ctx["total_pnl"] == -1.0


def test_generate_scorecard_handles_invalid_context_snapshot(
    db_conn: sqlite3.Connection, context_store: ContextStore,
) -> None:
    reviewer = DailyReviewer(db_conn, context_store)
    db_conn.execute(
        """
        INSERT INTO decision_logs (
            decision_id, timestamp, stock_code, market, exchange_code,
            action, confidence, rationale, context_snapshot, input_data
        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
        """,
        (
            "d1",
            "2026-02-14T09:00:00+00:00",
            "005930",
            "KR",
            "KRX",
            "HOLD",
            50,
            "test",
            "{invalid_json",
            json.dumps({}),
        ),
    )
    db_conn.commit()

    scorecard = reviewer.generate_scorecard("2026-02-14", "KR")
    assert scorecard.total_decisions == 1
    assert scorecard.scenario_match_rate == 0.0