64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
"""Pydantic schemas for trade setup endpoints."""
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from __future__ import annotations
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from datetime import date, datetime
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from pydantic import BaseModel, Field
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class TradeTargetResponse(BaseModel):
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price: float
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distance_from_entry: float
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distance_atr_multiple: float
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rr_ratio: float
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probability: float
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classification: str
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sr_level_id: int
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sr_strength: float
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is_primary: bool = False
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class RecommendationSummaryResponse(BaseModel):
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action: str
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reasoning: str | None
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risk_level: str | None
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composite_score: float
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class TradeSetupContextAsOfResponse(BaseModel):
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setup_detected_at: datetime
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score_computed_at: datetime | None = None
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sentiment_at: datetime | None = None
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price_date: date | None = None
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price_updated_at: datetime | None = None
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class TradeSetupResponse(BaseModel):
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"""A single trade setup detected by the R:R scanner."""
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id: int
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symbol: str
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direction: str
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entry_price: float
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stop_loss: float
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target: float
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rr_ratio: float
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composite_score: float
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detected_at: datetime
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confidence_score: float | None = None
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targets: list[TradeTargetResponse] = Field(default_factory=list)
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conflict_flags: list[str] = Field(default_factory=list)
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recommended_action: str | None = None
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reasoning: str | None = None
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risk_level: str | None = None
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actual_outcome: str | None = None
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outcome_date: date | None = None
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evaluated_at: datetime | None = None
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current_price: float | None = None
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momentum_percentile: float | None = None
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strategy_rank: float | None = None
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volatility_percentile: float | None = None
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context_as_of: TradeSetupContextAsOfResponse | None = None
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recommendation_summary: RecommendationSummaryResponse | None = None
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