知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
250 lines
8.7 KiB
Python
250 lines
8.7 KiB
Python
# -*- coding: utf-8 -*-
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"""Data models."""
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from typing import Any
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from dataclasses import dataclass, field
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from datetime import datetime
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@dataclass
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class HardFilterConfig:
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exclude_st: bool = True
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price_min: float | None = None
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price_max: float | None = None
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amount_min: float | None = None
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market_cap_min: float | None = None
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market_cap_max: float | None = None
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pe_ttm_min: float | None = None
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pe_ttm_max: float | None = None
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pb_min: float | None = None
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pb_max: float | None = None
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volume_ratio_min: float | None = None
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turnover_rate_min: float | None = None
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change_pct_min: float | None = None
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change_pct_max: float | None = None
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change_60d_min: float | None = None
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change_60d_max: float | None = None
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require_ma_bullish: bool = False
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require_price_above_ma20: bool = False
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signal_score_min: int | None = None
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macd_status_whitelist: list[str] | None = None
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rsi_status_whitelist: list[str] | None = None
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breakout_20d_pct_min: float | None = None
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breakout_20d_pct_max: float | None = None
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range_20d_pct_max: float | None = None
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volume_ratio_20d_min: float | None = None
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volume_ratio_20d_max: float | None = None
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body_pct_min: float | None = None
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body_pct_max: float | None = None
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pullback_to_ma20_pct_min: float | None = None
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pullback_to_ma20_pct_max: float | None = None
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consolidation_days_20d_min: int | None = None
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consolidation_days_20d_max: int | None = None
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volatility_20d_pct_min: float | None = None
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volatility_20d_pct_max: float | None = None
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max_drawdown_20d_pct_min: float | None = None
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max_drawdown_20d_pct_max: float | None = None
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atr_20_pct_min: float | None = None
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atr_20_pct_max: float | None = None
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@dataclass
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class ScreeningConfig:
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enabled: bool = False
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market_scope: list[str] = field(default_factory=lambda: ["cn"])
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hard_filters: HardFilterConfig = field(default_factory=HardFilterConfig)
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tech_weight: float = 0.35
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factor_weights: dict[str, float] = field(default_factory=dict)
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scoring_profile: dict[str, Any] = field(default_factory=dict)
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risk_profile: dict[str, Any] = field(default_factory=dict)
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portfolio_profile: dict[str, Any] = field(default_factory=dict)
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scorecard_profile: dict[str, Any] = field(default_factory=dict)
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event_profile: dict[str, Any] = field(default_factory=dict)
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ranking_hints: str = ""
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max_output: int = 5
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@dataclass
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class Strategy:
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name: str
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display_name: str
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description: str
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version: str = "1"
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category: str = "trend"
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tags: list[str] = field(default_factory=list)
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screening: ScreeningConfig = field(default_factory=ScreeningConfig)
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@dataclass
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class StrategyInfo:
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"""Strategy metadata for list_strategies()."""
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name: str
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display_name: str
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description: str
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version: str
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category: str
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tags: list[str]
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market_scope: list[str]
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@dataclass
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class Pick:
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rank: int
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code: str
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name: str
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final_score: float
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screen_score: float
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llm_score: float | None = None
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ranking_reason: str = ""
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risk_summary: str = ""
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price: float = 0.0
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change_pct: float = 0.0
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amount: float = 0.0
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total_mv: float | None = None
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turnover_rate: float | None = None
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volume_ratio: float | None = None
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pe_ratio: float | None = None
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pb_ratio: float | None = None
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industry: str = ""
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concepts: str = ""
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industry_rank: int | None = None
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industry_change_pct: float | None = None
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industry_heat_score: float | None = None
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concept_heat_score: float | None = None
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board_heat_score: float | None = None
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board_heat_latest_score: float | None = None
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board_heat_trend_score: float | None = None
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board_heat_persistence_score: float | None = None
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board_heat_cooling_score: float | None = None
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board_heat_observations: int | None = None
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board_heat_state: str = ""
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board_heat_summary: str = ""
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change_60d: float | None = None
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signal_score: float | None = None
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ma_bullish: bool | None = None
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price_above_ma20: bool | None = None
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macd_status: str = ""
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rsi_status: str = ""
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breakout_20d_pct: float | None = None
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range_20d_pct: float | None = None
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volume_ratio_20d: float | None = None
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body_pct: float | None = None
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pullback_to_ma20_pct: float | None = None
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consolidation_days_20d: int | None = None
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volatility_20d_pct: float | None = None
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max_drawdown_20d_pct: float | None = None
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atr_20_pct: float | None = None
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daily_quality_score: float | None = None
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daily_quality_flags: str = ""
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daily_source: str = ""
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factor_scores: dict[str, float] = field(default_factory=dict)
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llm_confidence: float | None = None
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llm_sector: str = ""
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llm_theme: str = ""
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llm_tags: list[str] = field(default_factory=list)
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llm_catalysts: list[str] = field(default_factory=list)
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llm_risks: list[str] = field(default_factory=list)
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llm_thesis: str = ""
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llm_style_fit: str = ""
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llm_watch_items: list[str] = field(default_factory=list)
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llm_invalidators: list[str] = field(default_factory=list)
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risk_score: float | None = None
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risk_level: str = ""
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risk_penalty: float = 0.0
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risk_flags: list[str] = field(default_factory=list)
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excluded_by_risk: bool = False
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portfolio_penalty: float = 0.0
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portfolio_flags: list[str] = field(default_factory=list)
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post_analysis_status: dict[str, str] = field(default_factory=dict)
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post_analysis_summaries: dict[str, str] = field(default_factory=dict)
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post_analysis_score_deltas: dict[str, float] = field(default_factory=dict)
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post_analysis_results: dict[str, Any] = field(default_factory=dict)
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post_analysis_tags: list[str] = field(default_factory=list)
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dsa_context: dict[str, Any] = field(default_factory=dict)
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dsa_news: list[dict[str, Any]] = field(default_factory=list)
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dsa_analysis_summary: str = ""
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deep_analysis_status: str = "not_requested"
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deep_analysis_query_id: str = ""
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deep_analysis_summary: str = ""
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deep_analysis_error: str = ""
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deep_analysis_result: dict[str, Any] | None = None
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deep_analysis_signal_score: int | None = None
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deep_analysis_sentiment_score: int | None = None
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deep_analysis_operation_advice: str = ""
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deep_analysis_trend_prediction: str = ""
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deep_analysis_risk_flags: list[str] = field(default_factory=list)
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@dataclass
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class ScreenResult:
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strategy: str
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market: str
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strategy_version: str = ""
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strategy_category: str = ""
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snapshot_count: int = 0
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after_filter_count: int = 0
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picks: list[Pick] = field(default_factory=list)
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run_id: str = ""
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llm_ranked: bool = False
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llm_market_view: str = ""
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llm_selection_logic: str = ""
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llm_portfolio_risk: str = ""
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llm_coverage: float | None = None
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llm_parse_errors: list[str] = field(default_factory=list)
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degradation: list[str] = field(default_factory=list)
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snapshot_source: str = ""
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source_errors: list[str] = field(default_factory=list)
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deep_analysis_requested: bool = False
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post_analyzers: list[str] = field(default_factory=list)
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daily_enriched: bool = False
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daily_enrich_count: int = 0
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risk_enabled: bool = True
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portfolio_diversity_enabled: bool = True
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portfolio_concentration_notes: list[str] = field(default_factory=list)
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saved_path: str = ""
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created_at: str = field(default_factory=lambda: datetime.now().isoformat())
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@dataclass
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class PickEvaluation:
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code: str
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name: str
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rank: int
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entry_price: float
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current_price: float | None = None
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return_pct: float | None = None
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final_score: float = 0.0
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status: str = "missing"
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llm_sector: str = ""
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llm_theme: str = ""
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llm_tags: list[str] = field(default_factory=list)
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risk_level: str = ""
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risk_flags: list[str] = field(default_factory=list)
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portfolio_flags: list[str] = field(default_factory=list)
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shape_status: str = ""
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shape_tags: list[str] = field(default_factory=list)
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path_status: str = ""
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path_days: int | None = None
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path_end_return_pct: float | None = None
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max_drawdown_pct: float | None = None
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max_runup_pct: float | None = None
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@dataclass
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class EvaluationResult:
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run_id: str
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strategy: str
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market: str
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created_at: str
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evaluated_at: str = field(default_factory=lambda: datetime.now().isoformat())
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elapsed_days: int | None = None
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snapshot_source: str = ""
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source_errors: list[str] = field(default_factory=list)
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picks: list[PickEvaluation] = field(default_factory=list)
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average_return_pct: float | None = None
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median_return_pct: float | None = None
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win_rate: float | None = None
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missing_codes: list[str] = field(default_factory=list)
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degradation: list[str] = field(default_factory=list)
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saved_path: str = ""
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