612 lines
22 KiB
Python
612 lines
22 KiB
Python
from __future__ import annotations
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import os
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import time
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from copy import deepcopy
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from datetime import datetime
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from typing import Optional
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from fastapi import APIRouter, HTTPException
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from loguru import logger
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from src.analysis.deb_algorithm import load_history
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from src.database.db_manager import DBManager
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from src.database.runtime_state import (
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DailyRecordRepository,
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STATE_STORAGE_SQLITE,
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TruthRecordRepository, # noqa: F401 - compatibility export for ops/truth-history
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get_state_storage_mode,
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)
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from src.analysis.settlement_rounding import apply_city_settlement
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from src.data_collection.country_networks import get_country_network_provider # noqa: F401 - compatibility export for transitional routers
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from src.data_collection.city_registry import ALIASES
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from src.data_collection.city_time import get_city_utc_offset_seconds # noqa: F401 - compatibility export for transitional routers
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from src.utils.refresh_policy import OBSERVATION_REFRESH_SEC, SCAN_ROWS_REFRESH_SEC
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from web.analysis_service import (
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_build_city_chart_detail_payload, # noqa: F401 - compatibility export for chart detail batches
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_build_city_detail_payload, # noqa: F401 - compatibility export for tests and transitional routers
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_build_city_market_scan_payload,
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)
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from web.services.canonical_temperature import (
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build_city_weather_from_canonical,
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)
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from web.services.latest_observation_overlay import overlay_latest_amsc_observation
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from web.scan_terminal_service import build_scan_terminal_payload # noqa: F401 - compatibility export for tests and transitional routers
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from web.core import (
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CITIES,
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CITY_REGISTRY, # noqa: F401 - compatibility export for tests and transitional routers
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CITY_RISK_PROFILES, # noqa: F401 - compatibility export for tests and transitional routers
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PAYMENT_CHECKOUT, # noqa: F401 - compatibility export for tests and transitional routers
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PaymentCheckoutError, # noqa: F401 - compatibility export for tests and transitional routers
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SETTLEMENT_SOURCE_LABELS, # noqa: F401 - compatibility export for city list payloads
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SUPABASE_ENTITLEMENT, # noqa: F401 - compatibility export for tests and transitional routers
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ConfirmPaymentTxRequest, # noqa: F401 - compatibility export for tests and transitional routers
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CreatePaymentIntentRequest, # noqa: F401 - compatibility export for tests and transitional routers
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GrantPointsRequest, # noqa: F401 - compatibility export for tests and transitional routers
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SubmitPaymentTxRequest, # noqa: F401 - compatibility export for tests and transitional routers
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WalletChallengeRequest, # noqa: F401 - compatibility export for tests and transitional routers
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WalletUnbindRequest, # noqa: F401 - compatibility export for tests and transitional routers
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WalletVerifyRequest, # noqa: F401 - compatibility export for tests and transitional routers
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_ENTITLEMENT_GUARD_ENABLED, # noqa: F401 - compatibility export for tests and transitional routers
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_SUPABASE_AUTH_REQUIRED, # noqa: F401 - compatibility export for tests and transitional routers
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_assert_entitlement, # noqa: F401 - compatibility export for tests and transitional routers
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_bind_optional_supabase_identity, # noqa: F401 - compatibility export for tests and transitional routers
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_require_ops_admin, # noqa: F401 - compatibility export for tests and transitional routers
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_require_supabase_identity, # noqa: F401 - compatibility export for tests and transitional routers
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_resolve_auth_points, # noqa: F401 - compatibility export for tests and transitional routers
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_resolve_weekly_profile, # noqa: F401 - compatibility export for tests and transitional routers
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_sf,
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_weather, # noqa: F401 - compatibility export for tests and transitional routers
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)
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router = APIRouter()
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_CACHE_DB = DBManager()
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_DEB_RECENT_LOOKBACK = 7
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_DEB_RECENT_MIN_SAMPLES = 3
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_daily_record_repo = DailyRecordRepository()
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TRACKABLE_ANALYTICS_EVENTS = {
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"landing_view",
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"enter_terminal",
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"login_start",
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"signup_success",
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"trial_created",
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"payment_start",
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"payment_success",
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"degraded_auth_profile",
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"signup_completed",
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"dashboard_active",
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"paywall_feature_clicked",
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"paywall_viewed",
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"checkout_started",
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"checkout_succeeded",
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}
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DEFAULT_STATUS_CITIES = [
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"ankara",
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"istanbul",
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"shanghai",
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"beijing",
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"shenzhen",
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"guangzhou",
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"qingdao",
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"wuhan",
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"chengdu",
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"chongqing",
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"hong kong",
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"taipei",
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"singapore",
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"tokyo",
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"seoul",
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"busan",
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"london",
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"paris",
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"madrid",
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]
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ASIA_CORE_CITIES = [
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"hong kong",
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"taipei",
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"tokyo",
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"seoul",
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"busan",
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"shanghai",
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"beijing",
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"guangzhou",
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"qingdao",
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"shenzhen",
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"chongqing",
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"chengdu",
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"singapore",
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"kuala lumpur",
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"jakarta",
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]
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EUROPE_CORE_CITIES = [
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"istanbul",
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"ankara",
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"moscow",
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"tel aviv",
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"london",
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"paris",
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"madrid",
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"milan",
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"warsaw",
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"amsterdam",
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"helsinki",
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]
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US_CORE_CITIES = [
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"new york",
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"los angeles",
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"san francisco",
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"austin",
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"houston",
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"chicago",
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"dallas",
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"miami",
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"atlanta",
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"seattle",
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]
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CITY_SUMMARY_CACHE_TTL_SEC = min(SCAN_ROWS_REFRESH_SEC, max(30, int(os.getenv("POLYWEATHER_CITY_SUMMARY_CACHE_TTL_SEC", str(SCAN_ROWS_REFRESH_SEC)))))
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CITY_PANEL_CACHE_TTL_SEC = min(SCAN_ROWS_REFRESH_SEC, max(30, int(os.getenv("POLYWEATHER_CITY_PANEL_CACHE_TTL_SEC", str(SCAN_ROWS_REFRESH_SEC)))))
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CITY_NEARBY_CACHE_TTL_SEC = min(SCAN_ROWS_REFRESH_SEC, max(30, int(os.getenv("POLYWEATHER_CITY_NEARBY_CACHE_TTL_SEC", str(SCAN_ROWS_REFRESH_SEC)))))
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CITY_MARKET_CACHE_TTL_SEC = min(SCAN_ROWS_REFRESH_SEC, max(30, int(os.getenv("POLYWEATHER_CITY_MARKET_CACHE_TTL_SEC", str(SCAN_ROWS_REFRESH_SEC)))))
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CITY_FULL_CACHE_TTL_SEC = min(OBSERVATION_REFRESH_SEC, max(30, int(os.getenv("POLYWEATHER_CITY_FULL_CACHE_TTL_SEC", str(OBSERVATION_REFRESH_SEC)))))
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MARKET_SCAN_PAYLOAD_TTL_SEC = max(
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5,
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int(os.getenv("POLYWEATHER_MARKET_SCAN_PAYLOAD_TTL_SEC", "30")),
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)
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def _city_cache_is_fresh(entry: Optional[dict], ttl_sec: int) -> bool:
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if not isinstance(entry, dict):
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return False
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updated_at_ts = float(entry.get("updated_at_ts") or 0.0)
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if updated_at_ts <= 0:
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return False
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return (time.time() - updated_at_ts) < float(ttl_sec)
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def _market_analysis_cache_is_fresh(entry: Optional[dict]) -> bool:
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if not isinstance(entry, dict):
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return False
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payload = entry.get("payload") or {}
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if isinstance(payload, dict):
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cached_at_ts = float(payload.get("market_analysis_cached_at_ts") or 0.0)
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if cached_at_ts > 0:
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return (time.time() - cached_at_ts) < float(CITY_MARKET_CACHE_TTL_SEC)
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return _city_cache_is_fresh(entry, CITY_MARKET_CACHE_TTL_SEC)
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def _market_scan_cache_key(
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data: dict,
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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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) -> str:
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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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multi_model_daily = data.get("multi_model_daily") or {}
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if requested_date and isinstance(multi_model_daily, dict) and requested_date not in multi_model_daily:
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selected_date = local_date
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normalized_slug = str(market_slug or "").strip().lower()
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return f"{selected_date}|{normalized_slug}|lite={1 if lite else 0}"
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def _attach_market_scan_payload(
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payload: dict,
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*,
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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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) -> dict:
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if not isinstance(payload, dict):
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return payload
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scan_payload = _build_city_market_scan_payload(
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payload,
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market_slug=market_slug,
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target_date=target_date,
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lite=lite,
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)
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now_ts = time.time()
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payload["market_scan_payload"] = scan_payload
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payload["market_scan_updated_at"] = datetime.now().isoformat()
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payload["market_scan_updated_at_ts"] = now_ts
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payload["market_scan_cache_key"] = _market_scan_cache_key(
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payload,
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market_slug=market_slug,
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target_date=target_date,
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lite=lite,
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)
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return payload
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def _get_cached_market_scan_payload(
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payload: dict,
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*,
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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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) -> Optional[dict]:
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if not isinstance(payload, dict):
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return None
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scan_payload = payload.get("market_scan_payload")
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if not isinstance(scan_payload, dict):
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return None
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expected_key = _market_scan_cache_key(
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payload,
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market_slug=market_slug,
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target_date=target_date,
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lite=lite,
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)
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cached_key = str(payload.get("market_scan_cache_key") or "")
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if cached_key != expected_key:
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return None
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updated_at_ts = float(payload.get("market_scan_updated_at_ts") or 0.0)
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if updated_at_ts <= 0:
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return None
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if (time.time() - updated_at_ts) >= float(MARKET_SCAN_PAYLOAD_TTL_SEC):
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return None
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return scan_payload
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def _refresh_market_scan_payload_from_cached_analysis(
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city: str,
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payload: dict,
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*,
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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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) -> dict:
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_attach_market_scan_payload(
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payload,
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market_slug=market_slug,
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target_date=target_date,
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lite=lite,
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)
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_CACHE_DB.set_city_cache(
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"market",
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city,
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payload,
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version="v1",
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source_fingerprint=f"{city}:market",
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)
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return payload.get("market_scan_payload") or {}
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def _enqueue_city_observation_refresh(city: str, kind: str, *, reason: str) -> bool:
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try:
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enqueue = getattr(_CACHE_DB, "enqueue_observation_refresh_request", None)
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if not callable(enqueue):
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return False
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return bool(
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enqueue(
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city=str(city or "").strip().lower(),
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kind=kind,
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priority="high",
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reason=reason,
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)
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)
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except Exception as exc:
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logger.debug("city cache collector enqueue skipped city={} kind={}: {}", city, kind, exc)
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return False
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def _cached_city_payload(kind: str, city: str) -> dict:
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try:
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entry = _CACHE_DB.get_city_cache(kind, city)
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except Exception as exc:
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logger.debug("city cache read skipped city={} kind={}: {}", city, kind, exc)
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return {}
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if not isinstance(entry, dict):
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return {}
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payload = entry.get("payload")
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if not isinstance(payload, dict):
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return {}
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payload = overlay_latest_amsc_observation(_CACHE_DB, city, payload)
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return _strip_wunderground_current(payload)
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def _canonical_city_payload(city: str, *, detail_depth: str) -> dict:
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try:
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row = _CACHE_DB.get_canonical_temperature(city)
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except Exception as exc:
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logger.debug("canonical city cache read skipped city={}: {}", city, exc)
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return {}
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if not isinstance(row, dict):
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return {}
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canonical = row.get("payload") or row
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if not isinstance(canonical, dict):
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return {}
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payload = build_city_weather_from_canonical(city, canonical)
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if not isinstance(payload, dict) or not payload:
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return {}
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city_meta = CITY_REGISTRY.get(city, {}) or {}
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city_info = CITIES.get(city, {}) or {}
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risk = CITY_RISK_PROFILES.get(city, {}) or {}
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payload.update(
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{
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"city": city,
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"detail_depth": detail_depth,
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"display_name": str(city_meta.get("display_name") or city_meta.get("name") or city.title()),
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"lat": city_info.get("lat"),
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"lon": city_info.get("lon"),
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"temp_symbol": canonical.get("temp_symbol") or payload.get("temp_symbol") or ("\u00b0F" if city_info.get("f") else "\u00b0C"),
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"risk": {
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"level": risk.get("risk_level", "low"),
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"emoji": risk.get("risk_emoji", ""),
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"airport": risk.get("airport_name", ""),
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"icao": risk.get("icao", ""),
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"distance_km": risk.get("distance_km", 0),
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"warning": risk.get("warning", ""),
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},
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"probabilities": payload.get("probabilities") or {"mu": None, "distribution": []},
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}
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)
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return overlay_latest_amsc_observation(_CACHE_DB, city, payload)
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def _initializing_city_payload(city: str, *, detail_depth: str) -> dict:
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city_meta = CITY_REGISTRY.get(city, {}) or {}
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city_info = CITIES.get(city, {}) or {}
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risk = CITY_RISK_PROFILES.get(city, {}) or {}
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return {
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"city": city,
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"name": city,
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"display_name": str(city_meta.get("display_name") or city_meta.get("name") or city.title()),
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"detail_depth": detail_depth,
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"status": "initializing",
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"stale": True,
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"stale_reason": "collector_refresh_queued",
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"lat": city_info.get("lat"),
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"lon": city_info.get("lon"),
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"temp_symbol": "\u00b0F" if city_info.get("f") else "\u00b0C",
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"risk": {
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"level": risk.get("risk_level", "low"),
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"emoji": risk.get("risk_emoji", ""),
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"airport": risk.get("airport_name", ""),
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"icao": risk.get("icao", ""),
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"distance_km": risk.get("distance_km", 0),
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"warning": risk.get("warning", ""),
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},
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"current": {
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"temp": None,
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"source_code": None,
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"settlement_source": None,
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"settlement_source_label": None,
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"obs_time": None,
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"freshness": {
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"freshness_status": "missing",
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"freshness_reason": "collector_refresh_queued",
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},
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"observation_status": "initializing",
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},
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"airport_current": {},
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"airport_primary": {},
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"canonical_temperature": None,
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"deb": {"prediction": None},
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"probabilities": {"mu": None, "distribution": []},
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"hourly": {"times": [], "temps": []},
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"multi_model_daily": {},
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}
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def _queued_city_cache_payload(city: str, kind: str, *, force_refresh: bool = False) -> dict:
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normalized = str(city or "").strip().lower()
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cached = _cached_city_payload(kind, normalized)
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if cached:
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if force_refresh:
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_enqueue_city_observation_refresh(normalized, kind, reason="force_refresh")
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return cached
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canonical_payload = _canonical_city_payload(normalized, detail_depth=kind)
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if canonical_payload:
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_enqueue_city_observation_refresh(
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normalized,
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kind,
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reason="force_refresh" if force_refresh else "canonical_fallback",
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)
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return canonical_payload
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_enqueue_city_observation_refresh(
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normalized,
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kind,
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reason="force_refresh" if force_refresh else "cold_start",
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)
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return _initializing_city_payload(normalized, detail_depth=kind)
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def _refresh_city_summary_cache(city: str, force_refresh: bool = False) -> dict:
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return _queued_city_cache_payload(city, "summary", force_refresh=force_refresh)
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def _refresh_city_panel_cache(city: str, force_refresh: bool = False) -> dict:
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return _queued_city_cache_payload(city, "panel", force_refresh=force_refresh)
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def _refresh_city_nearby_cache(city: str, force_refresh: bool = False) -> dict:
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return _queued_city_cache_payload(city, "nearby", force_refresh=force_refresh)
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def _refresh_city_market_cache(city: str, force_refresh: bool = False) -> dict:
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return _queued_city_cache_payload(city, "market", force_refresh=force_refresh)
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def _refresh_city_full_cache(city: str, force_refresh: bool = False) -> dict:
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return _queued_city_cache_payload(city, "full", force_refresh=force_refresh)
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def _strip_wunderground_current(payload: dict) -> dict:
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if not isinstance(payload, dict):
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return payload
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next_payload = deepcopy(payload)
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next_payload.pop("wunderground_current", None)
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official = next_payload.get("official")
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if isinstance(official, dict):
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official.pop("wunderground_current", None)
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timeseries = next_payload.get("timeseries")
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if isinstance(timeseries, dict):
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timeseries.pop("wunderground_today_obs", None)
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return next_payload
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def _overlay_latest_wunderground_current(city: str, payload: dict) -> dict:
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if not isinstance(payload, dict):
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return payload
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return _strip_wunderground_current(payload)
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def _normalize_city_or_404(name: str) -> str:
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city = name.lower().strip().replace("-", " ")
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city = ALIASES.get(city, city)
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if city not in CITIES:
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raise HTTPException(404, detail=f"Unknown city: {city}")
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return city
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def _normalize_city_list(raw: Optional[str]) -> list[str]:
|
|
if not raw:
|
|
return list(DEFAULT_STATUS_CITIES)
|
|
out: list[str] = []
|
|
for part in str(raw).split(","):
|
|
city = str(part or "").strip().lower().replace("-", " ")
|
|
if not city:
|
|
continue
|
|
city = ALIASES.get(city, city)
|
|
if city in CITIES and city not in out:
|
|
out.append(city)
|
|
return out
|
|
|
|
|
|
def _select_priority_city_batches(client_timezone: Optional[str]) -> dict[str, object]:
|
|
tz = str(client_timezone or "").strip()
|
|
normalized = tz.lower()
|
|
if normalized.startswith("america/"):
|
|
primary = list(US_CORE_CITIES)
|
|
secondary = []
|
|
region = "america"
|
|
elif normalized.startswith("europe/"):
|
|
primary = list(EUROPE_CORE_CITIES)
|
|
secondary = list(ASIA_CORE_CITIES)
|
|
region = "europe"
|
|
elif normalized.startswith("asia/") or normalized.startswith("australia/") or normalized.startswith("pacific/"):
|
|
primary = list(ASIA_CORE_CITIES)
|
|
secondary = list(EUROPE_CORE_CITIES)
|
|
region = "asia"
|
|
else:
|
|
primary = list(ASIA_CORE_CITIES)
|
|
secondary = list(EUROPE_CORE_CITIES)
|
|
region = "default"
|
|
return {
|
|
"region": region,
|
|
"timezone": tz or None,
|
|
"primary": primary,
|
|
"secondary": secondary,
|
|
}
|
|
|
|
|
|
def _history_file_path() -> str:
|
|
project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
|
return os.path.join(project_root, "data", "daily_records.json")
|
|
|
|
|
|
def _build_recent_deb_performance_index(
|
|
history_data: Optional[dict] = None,
|
|
*,
|
|
lookback: int = _DEB_RECENT_LOOKBACK,
|
|
min_samples: int = _DEB_RECENT_MIN_SAMPLES,
|
|
) -> dict[str, dict[str, object]]:
|
|
index: dict[str, dict[str, object]] = {}
|
|
today = datetime.utcnow().strftime("%Y-%m-%d")
|
|
settled_by_city: dict[str, list[tuple[str, float, float]]] = {}
|
|
|
|
if isinstance(history_data, dict):
|
|
for city_name, rows in history_data.items():
|
|
if not isinstance(rows, dict):
|
|
continue
|
|
settled: list[tuple[str, float, float]] = []
|
|
for date_key in sorted(rows.keys(), reverse=True):
|
|
if date_key >= today:
|
|
continue
|
|
record = rows.get(date_key) or {}
|
|
if not isinstance(record, dict):
|
|
continue
|
|
actual = _sf(record.get("actual_high"))
|
|
deb_prediction = _sf(record.get("deb_prediction"))
|
|
if actual is None or deb_prediction is None:
|
|
continue
|
|
settled.append((date_key, actual, deb_prediction))
|
|
if len(settled) >= max(lookback, 1):
|
|
break
|
|
settled_by_city[str(city_name).strip().lower()] = settled
|
|
elif get_state_storage_mode() == STATE_STORAGE_SQLITE:
|
|
recent_rows = _daily_record_repo.load_recent_settled_rows(
|
|
before_date=today,
|
|
per_city_limit=max(lookback, 1),
|
|
)
|
|
for city_name, rows in recent_rows.items():
|
|
settled: list[tuple[str, float, float]] = []
|
|
for row in rows:
|
|
actual = _sf(row.get("actual_high"))
|
|
deb_prediction = _sf(row.get("deb_prediction"))
|
|
date_key = str(row.get("target_date") or "").strip()
|
|
if not date_key or actual is None or deb_prediction is None:
|
|
continue
|
|
settled.append((date_key, actual, deb_prediction))
|
|
settled_by_city[str(city_name).strip().lower()] = settled
|
|
else:
|
|
data = load_history(_history_file_path())
|
|
if not isinstance(data, dict):
|
|
return index
|
|
for city_name, rows in data.items():
|
|
if not isinstance(rows, dict):
|
|
continue
|
|
settled: list[tuple[str, float, float]] = []
|
|
for date_key in sorted(rows.keys(), reverse=True):
|
|
if date_key >= today:
|
|
continue
|
|
record = rows.get(date_key) or {}
|
|
if not isinstance(record, dict):
|
|
continue
|
|
actual = _sf(record.get("actual_high"))
|
|
deb_prediction = _sf(record.get("deb_prediction"))
|
|
if actual is None or deb_prediction is None:
|
|
continue
|
|
settled.append((date_key, actual, deb_prediction))
|
|
if len(settled) >= max(lookback, 1):
|
|
break
|
|
settled_by_city[str(city_name).strip().lower()] = settled
|
|
|
|
for city_name, settled in settled_by_city.items():
|
|
if not settled:
|
|
continue
|
|
|
|
hit_count = 0
|
|
abs_errors: list[float] = []
|
|
for _, actual, deb_prediction in settled:
|
|
abs_errors.append(abs(deb_prediction - actual))
|
|
if apply_city_settlement(city_name, actual) == apply_city_settlement(city_name, deb_prediction):
|
|
hit_count += 1
|
|
|
|
sample_count = len(settled)
|
|
hit_rate = (hit_count / sample_count) if sample_count > 0 else None
|
|
if sample_count < min_samples:
|
|
tier = "other"
|
|
elif hit_rate is not None and hit_rate >= 0.67:
|
|
tier = "high"
|
|
elif hit_rate is not None and hit_rate >= 0.34:
|
|
tier = "medium"
|
|
else:
|
|
tier = "low"
|
|
|
|
index[str(city_name).strip().lower()] = {
|
|
"tier": tier,
|
|
"sample_count": sample_count,
|
|
"hit_rate": round(hit_rate, 4) if hit_rate is not None else None,
|
|
"mae": round(sum(abs_errors) / sample_count, 3) if sample_count > 0 else None,
|
|
"last_date": settled[0][0] if settled else None,
|
|
}
|
|
return index
|
|
|
|
__all__ = [name for name in globals() if not (name.startswith('__') and name.endswith('__'))]
|
|
|