dennisthiessen
da83f027e1
Answers "why does a too-far-progressed setup still show": setups are only recalculated by the scheduled R:R scan and manual fetch; at creation entry == current price (0% progress), so over-progression is a between-scans drift effect and must be judged at read time. - /trades now attaches current_price (latest close per ticker). - Qualification drops setups whose R:R recomputed from the current price falls below min_rr — i.e. price already ran toward target (reward consumed) or through the stop. Reuses the existing min_rr threshold instead of a separate progress %; far cleaner (a 3:1 is already ~1:1 by 33% progress). Skipped for historical setups (no current_price). - Fix: useFetchSymbolData now invalidates the trades queries, so a fetch/ recompute actually refreshes confidence/setups in the UI (was the cause of the stale 100% confidence lingering after recompute). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
52 lines
1.3 KiB
Python
52 lines
1.3 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 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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recommendation_summary: RecommendationSummaryResponse | None = None
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