2569718930@qq.com
129 lines
3.9 KiB
Python
129 lines
3.9 KiB
Python
from __future__ import annotations
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import hashlib
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import json
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from datetime import datetime
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from typing import Any, Dict, List, Optional
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SCAN_PAYLOAD_FULL_RUNWAY_HISTORY_ROWS = 9
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SCAN_PAYLOAD_DEFERRED_RUNWAY_POINTS = 12
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def _compact_runway_history_points(
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history: Any,
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*,
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max_points: int,
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) -> Dict[str, List[Dict[str, Any]]]:
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if not isinstance(history, dict) or max_points <= 0:
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return {}
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compacted: Dict[str, List[Dict[str, Any]]] = {}
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for runway, points in history.items():
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if not isinstance(points, list) or not points:
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continue
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compacted[str(runway)] = points[-max_points:]
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return compacted
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def compact_ranked_scan_rows_for_payload(
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rows: List[Dict[str, Any]],
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*,
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full_history_rows: int = SCAN_PAYLOAD_FULL_RUNWAY_HISTORY_ROWS,
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deferred_runway_points: int = SCAN_PAYLOAD_DEFERRED_RUNWAY_POINTS,
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) -> List[Dict[str, Any]]:
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compacted_rows: List[Dict[str, Any]] = []
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for index, row in enumerate(rows):
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if index < full_history_rows:
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compacted_rows.append(row)
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continue
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history = row.get("runway_plate_history")
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if not isinstance(history, dict) or not history:
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compacted_rows.append(row)
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continue
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next_row = dict(row)
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next_row["runway_plate_history"] = _compact_runway_history_points(
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history,
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max_points=deferred_runway_points,
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)
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compacted_rows.append(next_row)
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return compacted_rows
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def build_scan_terminal_snapshot_id(
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filters: Dict[str, Any],
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rows: List[Dict[str, Any]],
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summary: Dict[str, Any],
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top_signal: Optional[Dict[str, Any]],
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) -> str:
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seed_payload = {
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"filters": filters,
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"summary": {
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"candidate_total": summary.get("candidate_total"),
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"tradable_market_count": summary.get("tradable_market_count"),
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"avg_edge_percent": summary.get("avg_edge_percent"),
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},
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"top_signal": {
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"id": (top_signal or {}).get("id"),
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"edge_percent": (top_signal or {}).get("edge_percent"),
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"final_score": (top_signal or {}).get("final_score"),
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},
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"rows": [
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{
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"id": row.get("id"),
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"edge_percent": row.get("edge_percent"),
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"final_score": row.get("final_score"),
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}
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for row in rows[:10]
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],
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}
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digest = hashlib.md5(
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json.dumps(seed_payload, ensure_ascii=True, sort_keys=True).encode("utf-8")
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).hexdigest()
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return f"scan-{digest[:10]}"
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def build_stale_scan_terminal_payload(
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*,
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filters: Dict[str, Any],
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success_payload: Dict[str, Any],
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error_message: str,
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failed_at: Optional[str],
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) -> Dict[str, Any]:
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payload = dict(success_payload)
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payload["status"] = "stale"
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payload["stale"] = True
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payload["stale_reason"] = error_message
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payload["last_success_at"] = success_payload.get("generated_at")
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payload["last_failed_at"] = failed_at
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payload["filters"] = filters
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return payload
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def build_failed_scan_terminal_payload(
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*,
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filters: Dict[str, Any],
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error_message: str,
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failed_at: Optional[str] = None,
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) -> Dict[str, Any]:
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return {
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"generated_at": datetime.utcnow().isoformat() + "Z",
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"snapshot_id": None,
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"status": "failed",
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"stale": False,
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"stale_reason": error_message,
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"last_success_at": None,
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"last_failed_at": failed_at or (datetime.utcnow().isoformat() + "Z"),
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"filters": filters,
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"summary": {
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"recommended_count": 0,
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"visible_count": 0,
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"candidate_total": 0,
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"avg_edge_percent": None,
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"avg_primary_confidence": None,
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"tradable_market_count": 0,
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"total_volume": 0.0,
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"resolved_market_type": "maxtemp",
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},
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"top_signal": None,
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"rows": [],
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}
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