2569718930@qq.com
85 lines
2.6 KiB
Python
85 lines
2.6 KiB
Python
from __future__ import annotations
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from typing import Any, Dict, List, Optional
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from web.core import _sf as _safe_float
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def build_ranked_scan_terminal_result(
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*,
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city_results: List[Dict[str, Any]],
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filters: Dict[str, Any],
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total_city_count: int,
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failed_city_count: int,
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) -> Dict[str, Any]:
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primary_rows: List[Dict[str, Any]] = []
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primary_scores: List[float] = []
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candidate_total = 0
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for result in city_results:
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candidate_total += int(result.get("candidate_total") or 0)
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primary_rows.extend(result.get("rows") or [])
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primary_scores.extend(result.get("primary_scores") or [])
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primary_rows.sort(
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key=lambda row: (
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float(row.get("final_score") or 0.0),
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float(row.get("edge_percent") or 0.0),
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),
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reverse=True,
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)
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ranked_rows: List[Dict[str, Any]] = [
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{
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**row,
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"rank": index,
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}
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for index, row in enumerate(primary_rows[: filters["limit"]], start=1)
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]
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unique_market_volume: Dict[str, float] = {}
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for row in primary_rows:
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market_key = str(row.get("market_key") or row.get("id") or "").strip()
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if not market_key:
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continue
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unique_market_volume[market_key] = max(
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unique_market_volume.get(market_key, 0.0),
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float(row.get("volume") or 0.0),
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)
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avg_edge: Optional[float] = None
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if primary_rows:
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edge_values = [
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float(row.get("edge_percent") or 0.0)
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for row in primary_rows
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if _safe_float(row.get("edge_percent")) is not None
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]
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if edge_values:
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avg_edge = sum(edge_values) / len(edge_values)
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avg_confidence: Optional[float] = None
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if primary_scores:
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avg_confidence = sum(primary_scores) / len(primary_scores)
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top_signal = ranked_rows[0] if ranked_rows else None
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summary = {
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"recommended_count": len(primary_rows),
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"visible_count": len(ranked_rows),
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"candidate_total": candidate_total,
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"avg_edge_percent": avg_edge,
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"avg_primary_confidence": avg_confidence,
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"tradable_market_count": len(unique_market_volume),
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"total_volume": sum(unique_market_volume.values()),
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"resolved_market_type": "maxtemp",
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"total_city_count": total_city_count,
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"scanned_city_count": len(city_results),
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"failed_city_count": failed_city_count,
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}
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return {
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"primary_rows": primary_rows,
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"ranked_rows": ranked_rows,
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"summary": summary,
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"top_signal": top_signal,
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}
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