2569718930@qq.com
e9cc9a5eb1
InstitutionalLandingPage.tsx 补充 "use client" 指令以通过 Next.js 15 构建。 polymarket_readonly.py 集成 WebSocket 报价缓存加速价格获取。 city_payloads.py 复用 Polymarket 层构建真实市场扫描数据替代空返回。 Constraint: 市场扫描需在无 Polymarket 价格 UI 的前提下提供数据 Tested: npm run build 通过
221 lines
9.0 KiB
Python
221 lines
9.0 KiB
Python
"""City payload builders for API-facing response shapes."""
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from __future__ import annotations
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from typing import Any, Dict, Optional
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from web.core import _is_excluded_model_name
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TURKISH_MGM_CITIES = {"ankara", "istanbul"}
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_polymarket_layer = None
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def _get_polymarket_layer():
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global _polymarket_layer
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if _polymarket_layer is None:
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from src.data_collection.polymarket_readonly import PolymarketReadOnlyLayer
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_polymarket_layer = PolymarketReadOnlyLayer()
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return _polymarket_layer
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def _top_probability_bucket(distribution: Any) -> Optional[Dict[str, Any]]:
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if not isinstance(distribution, list):
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return None
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candidates = [row for row in distribution if isinstance(row, dict)]
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if not candidates:
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return None
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return max(candidates, key=lambda row: float(row.get("probability") or -1.0))
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def build_city_summary_payload(data: Dict[str, Any]) -> Dict[str, Any]:
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return {
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"name": data.get("name"),
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"display_name": data.get("display_name"),
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"icao": data.get("risk", {}).get("icao"),
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"utc_offset_seconds": data.get("utc_offset_seconds"),
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"local_time": data.get("local_time"),
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"temp_symbol": data.get("temp_symbol"),
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"current": {
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"temp": data.get("current", {}).get("temp"),
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"obs_time": data.get("current", {}).get("obs_time"),
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"settlement_source": data.get("current", {}).get("settlement_source"),
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"settlement_source_label": data.get("current", {}).get(
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"settlement_source_label"
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),
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},
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"deb": {"prediction": data.get("deb", {}).get("prediction")},
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"deviation_monitor": data.get("deviation_monitor") or {},
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"risk": {
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"level": data.get("risk", {}).get("level"),
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"warning": data.get("risk", {}).get("warning"),
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},
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"updated_at": data.get("updated_at"),
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}
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def build_city_market_scan_payload(
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data: Dict[str, Any],
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market_slug: Optional[str] = None,
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target_date: Optional[str] = None,
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lite: bool = False,
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scan_filters: Optional[Dict[str, Any]] = None,
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) -> Dict[str, Any]:
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local_date = str(data.get("local_date") or "").strip()
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requested_date = str(target_date or "").strip()
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selected_date = requested_date or local_date
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try:
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layer = _get_polymarket_layer()
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probabilities = data.get("probabilities") or {}
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distribution = probabilities.get("distribution") or []
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top_bucket = _top_probability_bucket(distribution)
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model_probability = (
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float(top_bucket.get("probability"))
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if (isinstance(top_bucket, dict) and top_bucket.get("probability") is not None)
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else None
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)
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scan = layer.build_market_scan(
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city=data.get("name"),
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target_date=selected_date,
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temperature_bucket=top_bucket,
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model_probability=model_probability,
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probability_distribution=distribution,
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temp_symbol=str(data.get("temp_symbol") or ""),
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forced_market_slug=market_slug,
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include_related_buckets=not lite,
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scan_filters=scan_filters,
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)
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return {
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"market_scan": scan,
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"selected_date": selected_date,
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"fetched_at": data.get("updated_at"),
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}
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except Exception:
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import traceback
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traceback.print_exc()
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return {
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"market_scan": {"available": False},
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"selected_date": selected_date,
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"fetched_at": data.get("updated_at"),
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}
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def build_city_detail_payload(
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data: Dict[str, Any],
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market_slug: Optional[str] = None,
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target_date: Optional[str] = None,
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) -> Dict[str, Any]:
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market_payload = build_city_market_scan_payload(
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data,
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market_slug=market_slug,
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target_date=target_date,
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)
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market_scan = market_payload.get("market_scan")
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return {
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"city": data.get("name"),
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"fetched_at": data.get("updated_at"),
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"overview": {
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"name": data.get("name"),
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"display_name": data.get("display_name"),
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"icao": data.get("risk", {}).get("icao"),
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"airport": data.get("risk", {}).get("airport"),
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"lat": data.get("lat"),
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"lon": data.get("lon"),
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"local_time": data.get("local_time"),
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"local_date": data.get("local_date"),
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"temp_symbol": data.get("temp_symbol"),
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"current_temp": data.get("current", {}).get("temp"),
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"settlement_source": data.get("current", {}).get("settlement_source"),
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"settlement_source_label": data.get("current", {}).get(
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"settlement_source_label"
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),
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"settlement_station": data.get("settlement_station") or {},
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"deb_prediction": data.get("deb", {}).get("prediction"),
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"risk_level": data.get("risk", {}).get("level"),
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"risk_warning": data.get("risk", {}).get("warning"),
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"updated_at": data.get("updated_at"),
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},
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"official": {
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"available": bool(data.get("current", {}).get("temp") is not None),
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"metar": {
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"observation_time": data.get("airport_current", {}).get("obs_time"),
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"obs_age_min": data.get("airport_current", {}).get("obs_age_min"),
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"report_time": data.get("airport_current", {}).get("report_time"),
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"receipt_time": data.get("airport_current", {}).get("receipt_time"),
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"raw_metar": data.get("airport_current", {}).get("raw_metar"),
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"current": data.get("airport_current") or {},
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},
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"taf": data.get("taf") or {},
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"weather_gov": {},
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"mgm": data.get("mgm") or {},
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"mgm_nearby": data.get("mgm_nearby") or [],
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"nearby_source": data.get("nearby_source")
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or (
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"mgm"
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if str(data.get("name") or "").lower() in TURKISH_MGM_CITIES
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else "metar_cluster"
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),
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"airport_primary": data.get("airport_primary") or {},
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"airport_primary_today_obs": data.get("airport_primary_today_obs") or [],
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"official_nearby": data.get("official_nearby") or [],
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"official_network_source": data.get("official_network_source"),
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"official_network_status": data.get("official_network_status") or {},
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"network_lead_signal": data.get("network_lead_signal") or {},
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"network_spread_signal": data.get("network_spread_signal") or {},
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"center_station_candidate": data.get("center_station_candidate"),
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"airport_vs_network_delta": data.get("airport_vs_network_delta"),
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},
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"timeseries": {
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"metar_recent_obs": data.get("metar_recent_obs") or [],
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"metar_today_obs": data.get("metar_today_obs") or [],
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"settlement_today_obs": data.get("settlement_today_obs") or [],
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"hourly": data.get("hourly") or {},
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"mgm_hourly": (data.get("mgm") or {}).get("hourly", []),
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"forecast_daily": (data.get("forecast") or {}).get("daily", []),
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},
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"models": {
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k: v
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for k, v in (data.get("multi_model") or {}).items()
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if not _is_excluded_model_name(k)
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},
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"deb": data.get("deb") or {},
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"multi_model_daily": data.get("multi_model_daily") or {},
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"probabilities": data.get("probabilities") or {"mu": None, "distribution": []},
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"dynamic_commentary": data.get("dynamic_commentary")
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or {"summary": "", "notes": []},
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"intraday_meteorology": data.get("intraday_meteorology")
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or _build_intraday_meteorology(data),
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"vertical_profile_signal": data.get("vertical_profile_signal") or {},
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"taf": data.get("taf") or {},
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"market_scan": market_scan,
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"risk": data.get("risk"),
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"settlement_station": data.get("settlement_station") or {},
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"airport_primary": data.get("airport_primary") or {},
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"official_nearby": data.get("official_nearby") or [],
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"official_network_source": data.get("official_network_source"),
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"official_network_status": data.get("official_network_status") or {},
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"network_lead_signal": data.get("network_lead_signal") or {},
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"network_spread_signal": data.get("network_spread_signal") or {},
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"center_station_candidate": data.get("center_station_candidate"),
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"airport_vs_network_delta": data.get("airport_vs_network_delta"),
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"airport_current": data.get("airport_current") or {},
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"amos": data.get("amos") or {},
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"nearby_source": data.get("nearby_source")
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or (
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"mgm"
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if str(data.get("name") or "").lower() in TURKISH_MGM_CITIES
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else "metar_cluster"
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),
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"ai_analysis": data.get("ai_analysis") or "",
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"errors": {},
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}
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def _build_intraday_meteorology(data: Dict[str, Any]) -> Dict[str, Any]:
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from web.analysis_service import _build_intraday_meteorology as build_intraday
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return build_intraday(data)
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