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Define data contracts for the proactive strategy system: - StockCondition: AND-combined condition fields (RSI, volume, price) - StockScenario: condition-action rules with stop loss/take profit - StockPlaybook: per-stock scenario collection - GlobalRule: portfolio-level rules (e.g. REDUCE_ALL on loss limit) - DayPlaybook: complete daily playbook per market with validation - CrossMarketContext: cross-market awareness (KR↔US) - ScenarioAction, MarketOutlook, PlaybookStatus enums 33 tests covering validation, serialization, edge cases. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
367 lines
11 KiB
Python
367 lines
11 KiB
Python
"""Tests for strategy/playbook Pydantic models."""
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from __future__ import annotations
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from datetime import date
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import pytest
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from pydantic import ValidationError
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from src.strategy.models import (
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CrossMarketContext,
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DayPlaybook,
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GlobalRule,
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MarketOutlook,
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PlaybookStatus,
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ScenarioAction,
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StockCondition,
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StockPlaybook,
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StockScenario,
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)
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# ---------------------------------------------------------------------------
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# StockCondition
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# ---------------------------------------------------------------------------
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class TestStockCondition:
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def test_empty_condition(self) -> None:
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cond = StockCondition()
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assert not cond.has_any_condition()
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def test_single_field(self) -> None:
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cond = StockCondition(rsi_below=30.0)
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assert cond.has_any_condition()
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def test_multiple_fields(self) -> None:
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cond = StockCondition(rsi_below=25.0, volume_ratio_above=3.0)
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assert cond.has_any_condition()
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def test_all_fields(self) -> None:
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cond = StockCondition(
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rsi_below=30,
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rsi_above=10,
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volume_ratio_above=2.0,
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volume_ratio_below=10.0,
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price_above=1000,
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price_below=50000,
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price_change_pct_above=-5.0,
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price_change_pct_below=5.0,
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)
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assert cond.has_any_condition()
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# ---------------------------------------------------------------------------
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# StockScenario
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# ---------------------------------------------------------------------------
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class TestStockScenario:
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def test_valid_scenario(self) -> None:
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s = StockScenario(
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condition=StockCondition(rsi_below=25.0),
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action=ScenarioAction.BUY,
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confidence=85,
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allocation_pct=15.0,
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stop_loss_pct=-2.0,
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take_profit_pct=3.0,
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rationale="Oversold bounce expected",
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)
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assert s.action == ScenarioAction.BUY
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assert s.confidence == 85
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def test_confidence_too_high(self) -> None:
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with pytest.raises(ValidationError):
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StockScenario(
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condition=StockCondition(),
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action=ScenarioAction.BUY,
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confidence=101,
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)
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def test_confidence_too_low(self) -> None:
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with pytest.raises(ValidationError):
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StockScenario(
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condition=StockCondition(),
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action=ScenarioAction.BUY,
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confidence=-1,
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)
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def test_allocation_too_high(self) -> None:
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with pytest.raises(ValidationError):
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StockScenario(
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condition=StockCondition(),
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action=ScenarioAction.BUY,
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confidence=80,
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allocation_pct=101.0,
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)
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def test_stop_loss_must_be_negative(self) -> None:
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with pytest.raises(ValidationError):
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StockScenario(
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condition=StockCondition(),
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action=ScenarioAction.BUY,
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confidence=80,
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stop_loss_pct=1.0,
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)
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def test_take_profit_must_be_positive(self) -> None:
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with pytest.raises(ValidationError):
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StockScenario(
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condition=StockCondition(),
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action=ScenarioAction.BUY,
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confidence=80,
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take_profit_pct=-1.0,
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)
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def test_defaults(self) -> None:
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s = StockScenario(
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condition=StockCondition(),
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action=ScenarioAction.HOLD,
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confidence=50,
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)
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assert s.allocation_pct == 10.0
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assert s.stop_loss_pct == -2.0
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assert s.take_profit_pct == 3.0
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assert s.rationale == ""
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# ---------------------------------------------------------------------------
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# StockPlaybook
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# ---------------------------------------------------------------------------
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class TestStockPlaybook:
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def test_valid_playbook(self) -> None:
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pb = StockPlaybook(
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stock_code="005930",
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stock_name="Samsung Electronics",
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scenarios=[
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StockScenario(
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condition=StockCondition(rsi_below=25.0),
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action=ScenarioAction.BUY,
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confidence=85,
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),
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],
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)
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assert pb.stock_code == "005930"
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assert len(pb.scenarios) == 1
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def test_empty_scenarios_rejected(self) -> None:
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with pytest.raises(ValidationError):
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StockPlaybook(
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stock_code="005930",
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scenarios=[],
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)
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def test_multiple_scenarios(self) -> None:
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pb = StockPlaybook(
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stock_code="AAPL",
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scenarios=[
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StockScenario(
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condition=StockCondition(rsi_below=25.0),
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action=ScenarioAction.BUY,
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confidence=85,
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),
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StockScenario(
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condition=StockCondition(rsi_above=75.0),
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action=ScenarioAction.SELL,
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confidence=80,
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),
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],
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)
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assert len(pb.scenarios) == 2
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# ---------------------------------------------------------------------------
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# GlobalRule
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# ---------------------------------------------------------------------------
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class TestGlobalRule:
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def test_valid_rule(self) -> None:
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rule = GlobalRule(
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condition="portfolio_pnl_pct < -2.0",
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action=ScenarioAction.REDUCE_ALL,
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rationale="Risk limit approaching",
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)
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assert rule.action == ScenarioAction.REDUCE_ALL
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def test_hold_rule(self) -> None:
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rule = GlobalRule(
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condition="volatility_index > 30",
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action=ScenarioAction.HOLD,
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)
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assert rule.rationale == ""
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# ---------------------------------------------------------------------------
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# CrossMarketContext
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# ---------------------------------------------------------------------------
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class TestCrossMarketContext:
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def test_valid_context(self) -> None:
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ctx = CrossMarketContext(
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market="US",
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date="2026-02-07",
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total_pnl=-1.5,
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win_rate=40.0,
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index_change_pct=-2.3,
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key_events=["Fed rate decision"],
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lessons=["Avoid tech sector on rate hike days"],
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)
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assert ctx.market == "US"
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assert len(ctx.key_events) == 1
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def test_defaults(self) -> None:
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ctx = CrossMarketContext(market="KR", date="2026-02-07")
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assert ctx.total_pnl == 0.0
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assert ctx.key_events == []
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assert ctx.lessons == []
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# ---------------------------------------------------------------------------
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# DayPlaybook
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# ---------------------------------------------------------------------------
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def _make_scenario(rsi_below: float = 25.0) -> StockScenario:
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return StockScenario(
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condition=StockCondition(rsi_below=rsi_below),
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action=ScenarioAction.BUY,
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confidence=85,
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)
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def _make_playbook(**kwargs) -> DayPlaybook:
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defaults = {
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"date": date(2026, 2, 7),
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"market": "KR",
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"stock_playbooks": [
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StockPlaybook(stock_code="005930", scenarios=[_make_scenario()]),
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],
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}
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defaults.update(kwargs)
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return DayPlaybook(**defaults)
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class TestDayPlaybook:
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def test_valid_playbook(self) -> None:
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pb = _make_playbook()
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assert pb.market == "KR"
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assert pb.date == date(2026, 2, 7)
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assert pb.default_action == ScenarioAction.HOLD
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assert pb.scenario_count == 1
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assert pb.stock_count == 1
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def test_generated_at_auto_set(self) -> None:
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pb = _make_playbook()
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assert pb.generated_at != ""
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def test_explicit_generated_at(self) -> None:
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pb = _make_playbook(generated_at="2026-02-07T08:30:00")
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assert pb.generated_at == "2026-02-07T08:30:00"
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def test_duplicate_stocks_rejected(self) -> None:
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with pytest.raises(ValidationError):
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DayPlaybook(
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date=date(2026, 2, 7),
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market="KR",
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stock_playbooks=[
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StockPlaybook(stock_code="005930", scenarios=[_make_scenario()]),
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StockPlaybook(stock_code="005930", scenarios=[_make_scenario(30)]),
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],
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)
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def test_empty_stock_playbooks_allowed(self) -> None:
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pb = DayPlaybook(
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date=date(2026, 2, 7),
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market="KR",
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stock_playbooks=[],
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)
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assert pb.stock_count == 0
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assert pb.scenario_count == 0
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def test_get_stock_playbook_found(self) -> None:
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pb = _make_playbook()
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result = pb.get_stock_playbook("005930")
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assert result is not None
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assert result.stock_code == "005930"
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def test_get_stock_playbook_not_found(self) -> None:
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pb = _make_playbook()
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result = pb.get_stock_playbook("AAPL")
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assert result is None
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def test_with_global_rules(self) -> None:
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pb = _make_playbook(
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global_rules=[
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GlobalRule(
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condition="portfolio_pnl_pct < -2.0",
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action=ScenarioAction.REDUCE_ALL,
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),
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],
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)
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assert len(pb.global_rules) == 1
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def test_with_cross_market_context(self) -> None:
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ctx = CrossMarketContext(market="US", date="2026-02-07", total_pnl=-1.5)
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pb = _make_playbook(cross_market=ctx)
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assert pb.cross_market is not None
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assert pb.cross_market.market == "US"
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def test_market_outlook(self) -> None:
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pb = _make_playbook(market_outlook=MarketOutlook.BEARISH)
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assert pb.market_outlook == MarketOutlook.BEARISH
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def test_multiple_stocks_multiple_scenarios(self) -> None:
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pb = DayPlaybook(
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date=date(2026, 2, 7),
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market="US",
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stock_playbooks=[
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StockPlaybook(
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stock_code="AAPL",
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scenarios=[_make_scenario(), _make_scenario(30)],
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),
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StockPlaybook(
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stock_code="MSFT",
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scenarios=[_make_scenario()],
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),
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],
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)
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assert pb.stock_count == 2
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assert pb.scenario_count == 3
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def test_serialization_roundtrip(self) -> None:
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pb = _make_playbook(
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market_outlook=MarketOutlook.BULLISH,
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cross_market=CrossMarketContext(market="US", date="2026-02-07"),
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)
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json_str = pb.model_dump_json()
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restored = DayPlaybook.model_validate_json(json_str)
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assert restored.market == pb.market
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assert restored.date == pb.date
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assert restored.scenario_count == pb.scenario_count
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assert restored.cross_market is not None
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# ---------------------------------------------------------------------------
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# Enums
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# ---------------------------------------------------------------------------
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class TestEnums:
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def test_scenario_action_values(self) -> None:
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assert ScenarioAction.BUY.value == "BUY"
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assert ScenarioAction.SELL.value == "SELL"
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assert ScenarioAction.HOLD.value == "HOLD"
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assert ScenarioAction.REDUCE_ALL.value == "REDUCE_ALL"
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def test_market_outlook_values(self) -> None:
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assert len(MarketOutlook) == 5
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def test_playbook_status_values(self) -> None:
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assert PlaybookStatus.READY.value == "ready"
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assert PlaybookStatus.EXPIRED.value == "expired"
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