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- Add DailyScorecard dataclass with market-scoped fields - Fields: date, market, decisions, pnl, win_rate, scenario_match_rate, lessons, cross_market_note - Export from src/evolution/__init__.py Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
82 lines
2.0 KiB
Python
82 lines
2.0 KiB
Python
"""Tests for DailyScorecard model."""
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from __future__ import annotations
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from src.evolution.scorecard import DailyScorecard
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def test_scorecard_initialization() -> None:
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scorecard = DailyScorecard(
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date="2026-02-08",
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market="KR",
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total_decisions=10,
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buys=3,
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sells=2,
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holds=5,
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total_pnl=1234.5,
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win_rate=60.0,
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avg_confidence=78.5,
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scenario_match_rate=70.0,
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top_winners=["005930", "000660"],
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top_losers=["035420"],
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lessons=["Avoid chasing breakouts"],
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cross_market_note="US volatility spillover",
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)
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assert scorecard.market == "KR"
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assert scorecard.total_decisions == 10
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assert scorecard.total_pnl == 1234.5
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assert scorecard.top_winners == ["005930", "000660"]
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assert scorecard.lessons == ["Avoid chasing breakouts"]
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assert scorecard.cross_market_note == "US volatility spillover"
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def test_scorecard_defaults() -> None:
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scorecard = DailyScorecard(
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date="2026-02-08",
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market="US",
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total_decisions=0,
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buys=0,
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sells=0,
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holds=0,
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total_pnl=0.0,
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win_rate=0.0,
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avg_confidence=0.0,
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scenario_match_rate=0.0,
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)
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assert scorecard.top_winners == []
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assert scorecard.top_losers == []
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assert scorecard.lessons == []
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assert scorecard.cross_market_note == ""
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def test_scorecard_list_isolation() -> None:
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a = DailyScorecard(
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date="2026-02-08",
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market="KR",
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total_decisions=1,
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buys=1,
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sells=0,
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holds=0,
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total_pnl=10.0,
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win_rate=100.0,
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avg_confidence=90.0,
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scenario_match_rate=100.0,
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)
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b = DailyScorecard(
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date="2026-02-08",
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market="US",
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total_decisions=1,
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buys=0,
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sells=1,
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holds=0,
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total_pnl=-5.0,
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win_rate=0.0,
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avg_confidence=60.0,
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scenario_match_rate=50.0,
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)
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a.top_winners.append("005930")
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assert b.top_winners == []
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