2569718930@qq.com
1595 lines
62 KiB
Python
1595 lines
62 KiB
Python
import hashlib
|
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import json
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import os
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import re
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import threading
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import time
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from datetime import datetime, timezone
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from typing import Any, Dict, List, Optional, Set, Tuple
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import requests as requests_lib
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from loguru import logger
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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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STATE_STORAGE_SQLITE,
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TelegramAlertStateRepository,
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get_state_storage_mode,
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)
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from src.data_collection.city_registry import CITY_REGISTRY
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from src.utils.telegram_chat_ids import get_telegram_chat_ids_from_env
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from src.utils.telegram_i18n import (
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copy_text as _copy,
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is_bilingual as _is_bilingual,
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is_zh as _is_zh,
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normalize_push_language as _normalize_push_language,
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telegram_push_language as _resolve_telegram_push_language,
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)
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# Forum topic routing: maps city_key -> message_thread_id for the push forum group.
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# Created by scripts/create_forum_topics.py, stored in the runtime data dir.
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_CITY_THREAD_IDS_PATH = os.path.join(
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os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
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"data", "city_thread_ids.json",
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)
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_FORUM_CHAT_ID = "-1003927451869"
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_city_thread_ids: dict = {}
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# Shared HTTP session for AROME and auxiliary queries (connection reuse)
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_HTTP_SESSION: Optional[requests_lib.Session] = None
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_HTTP_SESSION_LOCK = threading.Lock()
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# Bot send_message rate limiter: max N messages per second across all threads
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_SEND_MSG_LOCK = threading.Lock()
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_SEND_MSG_LAST_TS: float = 0.0
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_SEND_MSG_MIN_INTERVAL_SEC = float(os.getenv("TELEGRAM_SEND_RATE_LIMIT_SEC", "0.05"))
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def _get_http_session() -> requests_lib.Session:
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global _HTTP_SESSION
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if _HTTP_SESSION is None:
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with _HTTP_SESSION_LOCK:
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if _HTTP_SESSION is None:
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_HTTP_SESSION = requests_lib.Session()
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return _HTTP_SESSION
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# Reusable executor for airport push cycles (avoids thread pool churn)
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_AIRPORT_EXECUTOR: Optional[ThreadPoolExecutor] = None
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_AIRPORT_EXECUTOR_LOCK = threading.Lock()
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_AIRPORT_EXECUTOR_MAX_WORKERS: int = 0
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def _get_airport_executor(max_workers: int) -> ThreadPoolExecutor:
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global _AIRPORT_EXECUTOR, _AIRPORT_EXECUTOR_MAX_WORKERS
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if _AIRPORT_EXECUTOR is None or _AIRPORT_EXECUTOR_MAX_WORKERS != max_workers:
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with _AIRPORT_EXECUTOR_LOCK:
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if _AIRPORT_EXECUTOR is None or _AIRPORT_EXECUTOR_MAX_WORKERS != max_workers:
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if _AIRPORT_EXECUTOR is not None:
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_AIRPORT_EXECUTOR.shutdown(wait=False)
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_AIRPORT_EXECUTOR = ThreadPoolExecutor(max_workers=max_workers)
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_AIRPORT_EXECUTOR_MAX_WORKERS = max_workers
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return _AIRPORT_EXECUTOR
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def _rate_limited_send(bot: Any, chat_id: str, message: str, **kwargs: Any) -> None:
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"""Throttle bot.send_message calls to avoid hitting Telegram rate limits."""
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global _SEND_MSG_LAST_TS
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with _SEND_MSG_LOCK:
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now = time.time()
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wait = _SEND_MSG_MIN_INTERVAL_SEC - (now - _SEND_MSG_LAST_TS)
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if wait > 0:
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time.sleep(wait)
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_SEND_MSG_LAST_TS = time.time()
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bot.send_message(chat_id, message, **kwargs)
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def _load_city_thread_ids() -> dict:
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global _city_thread_ids
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if _city_thread_ids:
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return _city_thread_ids
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paths = [
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_CITY_THREAD_IDS_PATH,
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"/var/lib/polyweather/city_thread_ids.json",
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"/app/data/city_thread_ids.json",
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]
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for path in paths:
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if os.path.isfile(path):
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try:
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with open(path, "r", encoding="utf-8") as f:
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_city_thread_ids = json.load(f)
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logger.info("loaded city_thread_ids from {}: {} cities", path, len(_city_thread_ids))
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return _city_thread_ids
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except Exception as exc:
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logger.warning("failed to load city_thread_ids from {}: {}", path, exc)
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return {}
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def _resolve_thread_id(chat_id: str, city: str) -> int:
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"""Return message_thread_id for a given chat and city, or 0 if not a forum topic."""
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if str(chat_id) != _FORUM_CHAT_ID:
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return 0
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mapping = _load_city_thread_ids()
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city_key = str(city or "").strip().lower()
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return int(mapping.get(city_key) or 0)
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SEVERITY_RANK = {
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"none": 0,
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"low": 1,
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"medium": 2,
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"high": 3,
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}
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_telegram_state_repo = TelegramAlertStateRepository()
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def _env_bool(name: str, default: bool) -> bool:
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raw = os.getenv(name)
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if raw is None:
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return default
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return raw.strip().lower() in {"1", "true", "yes", "on"}
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def _env_int(name: str, default: int) -> int:
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raw = os.getenv(name)
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if raw is None:
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return default
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try:
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return int(raw)
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except Exception:
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return default
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def _env_float(name: str, default: float) -> float:
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raw = os.getenv(name)
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if raw is None:
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return default
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try:
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return float(raw)
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except Exception:
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return default
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def _telegram_push_language() -> str:
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return _resolve_telegram_push_language(
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"TELEGRAM_AIRPORT_PUSH_LANGUAGE",
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"TELEGRAM_PUSH_LANGUAGE",
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"POLYWEATHER_TELEGRAM_PUSH_LANGUAGE",
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)
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def _norm_prob(v: Any) -> Optional[float]:
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if v is None:
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return None
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try:
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n = float(v)
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except Exception:
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return None
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if n > 1.0:
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n = n / 100.0
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return max(0.0, min(1.0, n))
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def _fmt_cents(value: Any) -> Optional[str]:
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numeric = _norm_prob(value)
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if numeric is None:
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return None
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cents = numeric * 100.0
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rounded = round(cents, 1)
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text = f"{rounded:.1f}".rstrip("0").rstrip(".")
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return f"{text}c"
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def _safe_float(v: Any) -> Optional[float]:
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if v is None:
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return None
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try:
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return float(v)
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except Exception:
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return None
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def _bucket_value(row: Dict[str, Any]) -> Optional[float]:
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if not isinstance(row, dict):
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return None
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for key in ("value", "temp"):
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n = _safe_float(row.get(key))
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if n is not None:
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return n
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label = str(row.get("label") or "").strip()
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m = re.search(r"(-?\d+(?:\.\d+)?)", label)
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if not m:
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return None
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return _safe_float(m.group(1))
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def _bucket_bounds(row: Dict[str, Any]) -> Optional[Tuple[Optional[float], Optional[float]]]:
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value = _bucket_value(row)
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if value is None:
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return None
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label = str(row.get("label") or "").strip().lower()
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is_upper_tail = any(key in label for key in ("+", "or higher", "or above", "and above"))
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is_lower_tail = any(key in label for key in ("<=", "or lower", "or below", "and below"))
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if is_upper_tail and not is_lower_tail:
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return value, None
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if is_lower_tail and not is_upper_tail:
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return None, value
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return value, value
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def _observed_settlement_floor(alert_payload: Dict[str, Any]) -> Optional[float]:
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evidence = alert_payload.get("evidence") or {}
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if not isinstance(evidence, dict):
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evidence = {}
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inputs = evidence.get("inputs") or {}
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if not isinstance(inputs, dict):
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inputs = {}
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suppression = alert_payload.get("suppression") or {}
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if not isinstance(suppression, dict):
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suppression = {}
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rules = alert_payload.get("rules") or {}
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if not isinstance(rules, dict):
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rules = {}
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breakthrough = rules.get("forecast_breakthrough") or {}
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if not isinstance(breakthrough, dict):
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breakthrough = {}
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floor_candidates: List[float] = []
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for raw in (
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inputs.get("wu_settle"),
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suppression.get("max_so_far"),
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inputs.get("current_temp"),
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suppression.get("current_temp"),
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breakthrough.get("current_temp"),
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):
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n = _safe_float(raw)
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if n is not None:
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floor_candidates.append(n)
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if not floor_candidates:
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return None
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return max(floor_candidates)
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def _optional_bool(value: Any) -> Optional[bool]:
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if value is None:
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return None
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if isinstance(value, bool):
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return value
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if isinstance(value, (int, float)):
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return bool(value)
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if isinstance(value, str):
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normalized = value.strip().lower()
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if normalized in {"1", "true", "yes", "on"}:
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return True
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if normalized in {"0", "false", "no", "off"}:
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return False
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return bool(value)
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def _parse_iso_datetime_utc(value: Any) -> Optional[datetime]:
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if not value:
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return None
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text = str(value).strip()
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if not text:
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return None
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if "T" not in text:
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return None
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try:
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dt = datetime.fromisoformat(text.replace("Z", "+00:00"))
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except Exception:
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return None
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if dt.tzinfo is None:
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return dt.replace(tzinfo=timezone.utc)
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return dt.astimezone(timezone.utc)
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def _parse_city_list(raw: Optional[str]) -> List[str]:
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if not raw:
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return list(CITY_REGISTRY.keys())
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out: List[str] = []
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for part in raw.split(","):
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city = part.strip().lower()
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if city and city in CITY_REGISTRY:
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out.append(city)
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return out or list(CITY_REGISTRY.keys())
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def _state_file() -> str:
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root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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return os.path.join(root, "data", "telegram_alert_state.json")
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def _load_state(path: str) -> Dict[str, Any]:
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mode = get_state_storage_mode()
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if mode == STATE_STORAGE_SQLITE:
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||
try:
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return _telegram_state_repo.load_state()
|
||
except Exception as exc:
|
||
logger.error(f"failed to load telegram push state from sqlite: {exc}")
|
||
if not os.path.exists(path):
|
||
return {"last_by_city": {}, "by_signature": {}}
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try:
|
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with open(path, "r", encoding="utf-8") as fh:
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data = json.load(fh)
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||
if isinstance(data, dict):
|
||
data.setdefault("last_by_city", {})
|
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data.setdefault("by_signature", {})
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||
return data
|
||
except Exception as exc:
|
||
logger.warning(f"failed to load telegram push state: {exc}")
|
||
return {"last_by_city": {}, "by_signature": {}}
|
||
|
||
|
||
def _save_state(path: str, state: Dict[str, Any]) -> None:
|
||
mode = get_state_storage_mode()
|
||
if mode == STATE_STORAGE_SQLITE:
|
||
_telegram_state_repo.save_state(state)
|
||
if mode == STATE_STORAGE_SQLITE:
|
||
return
|
||
os.makedirs(os.path.dirname(path), exist_ok=True)
|
||
tmp_path = f"{path}.tmp"
|
||
with open(tmp_path, "w", encoding="utf-8") as fh:
|
||
json.dump(state, fh, ensure_ascii=False, indent=2)
|
||
os.replace(tmp_path, path)
|
||
|
||
|
||
def _cleanup_state(state: Dict[str, Any], now_ts: int, keep_sec: int = 7 * 86400) -> None:
|
||
for bucket_name in ("by_signature",):
|
||
bucket = state.get(bucket_name, {})
|
||
if not isinstance(bucket, dict):
|
||
state[bucket_name] = {}
|
||
continue
|
||
stale = [key for key, value in bucket.items() if now_ts - int(value or 0) > keep_sec]
|
||
for key in stale:
|
||
bucket.pop(key, None)
|
||
|
||
last_by_city = state.get("last_by_city", {})
|
||
if not isinstance(last_by_city, dict):
|
||
state["last_by_city"] = {}
|
||
return
|
||
stale_city = []
|
||
for city, row in last_by_city.items():
|
||
ts = int((row or {}).get("ts") or 0)
|
||
if now_ts - ts > keep_sec:
|
||
stale_city.append(city)
|
||
for city in stale_city:
|
||
last_by_city.pop(city, None)
|
||
|
||
|
||
def _severity_ok(alert_payload: Dict[str, Any], min_severity: str, min_trigger_count: int) -> bool:
|
||
triggered_alerts = alert_payload.get("triggered_alerts") or []
|
||
if any(alert.get("force_push") for alert in triggered_alerts):
|
||
return True
|
||
|
||
trigger_count = int(alert_payload.get("trigger_count") or 0)
|
||
if trigger_count < min_trigger_count:
|
||
return False
|
||
severity = str(alert_payload.get("severity") or "none").lower()
|
||
return SEVERITY_RANK.get(severity, 0) >= SEVERITY_RANK.get(min_severity, 0)
|
||
|
||
|
||
def _market_price_cap_ok(
|
||
alert_payload: Dict[str, Any],
|
||
) -> bool:
|
||
market = alert_payload.get("market_snapshot") or {}
|
||
if not isinstance(market, dict) or not market.get("available"):
|
||
return True
|
||
|
||
primary_market = market.get("primary_market") or {}
|
||
if not isinstance(primary_market, dict):
|
||
primary_market = {}
|
||
market_slug = (
|
||
str(market.get("selected_slug") or "").strip()
|
||
or str(primary_market.get("slug") or "").strip()
|
||
or "--"
|
||
)
|
||
active = market.get("market_active")
|
||
if active is None:
|
||
active = primary_market.get("active")
|
||
active = _optional_bool(active)
|
||
closed = market.get("market_closed")
|
||
if closed is None:
|
||
closed = primary_market.get("closed")
|
||
closed = _optional_bool(closed)
|
||
accepting_orders = market.get("market_accepting_orders")
|
||
if accepting_orders is None:
|
||
accepting_orders = primary_market.get(
|
||
"accepting_orders",
|
||
primary_market.get("acceptingOrders"),
|
||
)
|
||
accepting_orders = _optional_bool(accepting_orders)
|
||
market_tradable = _optional_bool(market.get("market_tradable"))
|
||
tradable_reason = str(
|
||
market.get("market_tradable_reason")
|
||
or primary_market.get("tradable_reason")
|
||
or ""
|
||
).strip()
|
||
ended_at = str(
|
||
market.get("market_ended_at_utc")
|
||
or primary_market.get("ended_at_utc")
|
||
or ""
|
||
).strip()
|
||
ended_dt = _parse_iso_datetime_utc(ended_at)
|
||
is_past_end = ended_dt is not None and ended_dt <= datetime.now(timezone.utc)
|
||
if (
|
||
market_tradable is False
|
||
or closed is True
|
||
or active is False
|
||
or accepting_orders is False
|
||
or is_past_end
|
||
):
|
||
reason = tradable_reason or ("past_end_time" if is_past_end else "market_not_tradable")
|
||
logger.info(
|
||
"trade alert skipped: market not tradable city={} slug={} reason={} active={} closed={} accepting_orders={} ended_at={}".format(
|
||
alert_payload.get("city"),
|
||
market_slug,
|
||
reason,
|
||
active,
|
||
closed,
|
||
accepting_orders,
|
||
ended_at or "--",
|
||
)
|
||
)
|
||
return False
|
||
|
||
# Strict rule: use the bucket mapped from multi-model anchor settlement.
|
||
forecast_bucket = market.get("forecast_bucket") or {}
|
||
settle_ref = market.get("anchor_settlement")
|
||
if settle_ref is None:
|
||
settle_ref = market.get("open_meteo_settlement")
|
||
anchor_model = str(market.get("anchor_model") or "").strip() or "--"
|
||
yes_buy = None
|
||
bucket_label = None
|
||
if isinstance(forecast_bucket, dict):
|
||
yes_buy = _norm_prob(forecast_bucket.get("yes_buy"))
|
||
bucket_label = str(forecast_bucket.get("label") or "").strip() or None
|
||
|
||
observed_floor = _observed_settlement_floor(alert_payload)
|
||
bucket_bounds = _bucket_bounds(forecast_bucket) if isinstance(forecast_bucket, dict) else None
|
||
if observed_floor is not None and bucket_bounds is not None:
|
||
_lower, upper = bucket_bounds
|
||
if upper is not None and observed_floor > upper + 1e-9:
|
||
logger.info(
|
||
"trade alert skipped: mapped bucket invalidated by observed high city={} bucket={} observed_floor={} upper_bound={} anchor_model={} anchor_settle={}".format(
|
||
alert_payload.get("city"),
|
||
bucket_label or "--",
|
||
round(observed_floor, 2),
|
||
round(upper, 2),
|
||
anchor_model,
|
||
settle_ref,
|
||
)
|
||
)
|
||
return False
|
||
|
||
if yes_buy is None or yes_buy <= 0.0:
|
||
logger.info(
|
||
"trade alert skipped: no actionable mapped bucket quote city={} bucket={} anchor_model={} anchor_settle={}".format(
|
||
alert_payload.get("city"),
|
||
bucket_label or "--",
|
||
anchor_model,
|
||
settle_ref,
|
||
)
|
||
)
|
||
return False
|
||
|
||
return True
|
||
|
||
|
||
def _trigger_type_key(alert_payload: Dict[str, Any]) -> str:
|
||
trigger_types = sorted(
|
||
str(alert.get("type") or "").strip()
|
||
for alert in (alert_payload.get("triggered_alerts") or [])
|
||
if alert.get("type")
|
||
)
|
||
market = alert_payload.get("market_snapshot") or {}
|
||
if isinstance(market, dict) and market.get("available"):
|
||
signal = str(market.get("signal_label") or "").strip()
|
||
bucket = str(market.get("selected_bucket") or "").strip()
|
||
if signal:
|
||
trigger_types.append(f"mkt:{signal}:{bucket}")
|
||
return "|".join(trigger_types)
|
||
|
||
|
||
def _evidence_brief(alert_payload: Dict[str, Any]) -> str:
|
||
evidence = alert_payload.get("evidence") or {}
|
||
if not isinstance(evidence, dict):
|
||
return "--"
|
||
|
||
trigger_summary = evidence.get("trigger_summary") or {}
|
||
rules = evidence.get("rules") or {}
|
||
market = evidence.get("market") or {}
|
||
momentum = rules.get("momentum_spike") or {}
|
||
advection = rules.get("advection") or {}
|
||
breakthrough = rules.get("forecast_breakthrough") or {}
|
||
|
||
parts: List[str] = []
|
||
trigger_types = trigger_summary.get("trigger_types")
|
||
if isinstance(trigger_types, list) and trigger_types:
|
||
parts.append(f"triggers={','.join(str(t) for t in trigger_types)}")
|
||
|
||
slope = momentum.get("slope_30m")
|
||
if slope is not None:
|
||
parts.append(f"slope_30m={slope}")
|
||
|
||
lead_delta = advection.get("lead_delta")
|
||
if lead_delta is not None:
|
||
parts.append(f"lead_delta={lead_delta}")
|
||
|
||
margin = breakthrough.get("margin")
|
||
if margin is not None:
|
||
parts.append(f"break_margin={margin}")
|
||
|
||
edge = market.get("edge_percent")
|
||
if edge is not None:
|
||
parts.append(f"edge_pct={edge}")
|
||
|
||
forecast_bucket = market.get("forecast_bucket") or {}
|
||
if isinstance(forecast_bucket, dict):
|
||
label = str(forecast_bucket.get("label") or "").strip()
|
||
yes_buy = forecast_bucket.get("yes_buy")
|
||
if label:
|
||
parts.append(f"bucket={label}")
|
||
if yes_buy is not None:
|
||
parts.append(f"yes_buy={yes_buy}")
|
||
|
||
if not parts:
|
||
return "--"
|
||
return "; ".join(parts)
|
||
|
||
|
||
def _alert_signature(alert_payload: Dict[str, Any]) -> str:
|
||
rules = alert_payload.get("rules") or {}
|
||
center_deb = rules.get("ankara_center_deb_hit") or {}
|
||
momentum = rules.get("momentum_spike") or {}
|
||
breakthrough = rules.get("forecast_breakthrough") or {}
|
||
advection = rules.get("advection") or {}
|
||
suppression = alert_payload.get("suppression") or {}
|
||
market = alert_payload.get("market_snapshot") or {}
|
||
|
||
signature_payload = {
|
||
"city": alert_payload.get("city"),
|
||
"target_date": alert_payload.get("target_date"),
|
||
"severity": alert_payload.get("severity"),
|
||
"trigger_types": sorted(
|
||
alert.get("type")
|
||
for alert in (alert_payload.get("triggered_alerts") or [])
|
||
if alert.get("type")
|
||
),
|
||
"center_temp": round(float(((center_deb.get("center_station") or {}).get("temp")) or 0.0), 1),
|
||
"center_deb_prediction": round(float(center_deb.get("deb_prediction") or 0.0), 1),
|
||
"center_airport_gap": round(float(center_deb.get("center_lead_vs_airport") or 0.0), 1),
|
||
"momentum_direction": momentum.get("direction"),
|
||
"momentum_slope_30m": round(float(momentum.get("slope_30m") or 0.0), 1),
|
||
"breakthrough_margin": round(float(breakthrough.get("margin") or 0.0), 1),
|
||
"lead_station": (advection.get("lead_station") or {}).get("name"),
|
||
"lead_delta": round(float(advection.get("lead_delta") or 0.0), 1),
|
||
"suppressed": bool(suppression.get("suppressed")),
|
||
"suppression_reason": suppression.get("reason"),
|
||
"suppression_peak_time": suppression.get("max_temp_time"),
|
||
"suppression_rollback": round(float(suppression.get("rollback") or 0.0), 1),
|
||
"market_available": bool(market.get("available")),
|
||
"market_bucket": market.get("selected_bucket"),
|
||
"market_top_bucket": market.get("top_bucket"),
|
||
"market_top_bucket_prob": round(float(market.get("top_bucket_prob") or 0.0), 3),
|
||
"market_prob": round(float(market.get("market_prob") or 0.0), 3),
|
||
"model_prob": round(float(market.get("model_prob") or 0.0), 3),
|
||
"market_yes_buy": round(float(market.get("yes_buy") or 0.0), 3),
|
||
"market_yes_sell": round(float(market.get("yes_sell") or 0.0), 3),
|
||
"market_spread": round(float(market.get("spread") or 0.0), 3),
|
||
"market_edge_percent": round(float(market.get("edge_percent") or 0.0), 2),
|
||
"market_signal": market.get("signal_label"),
|
||
"market_confidence": market.get("confidence"),
|
||
}
|
||
raw = json.dumps(signature_payload, sort_keys=True, ensure_ascii=True)
|
||
return hashlib.sha1(raw.encode("utf-8")).hexdigest()
|
||
|
||
# ── high-freq airport push loop ──
|
||
|
||
HIGH_FREQ_AIRPORT_CITIES = {
|
||
"seoul", "singapore", "busan", "tokyo", "ankara", "helsinki", "amsterdam",
|
||
"istanbul", "paris", "hong kong", "shenzhen", "taipei",
|
||
"beijing", "shanghai", "guangzhou", "qingdao", "chengdu", "chongqing", "wuhan",
|
||
"new york", "los angeles", "chicago", "denver", "atlanta",
|
||
"miami", "san francisco", "houston", "dallas", "austin", "seattle",
|
||
"tel aviv",
|
||
}
|
||
HIGH_FREQ_AIRPORT_ICAO = {
|
||
"seoul": "RKSI", "singapore": "WSSS", "busan": "RKPK", "tokyo": "44166",
|
||
"ankara": "17128", "helsinki": "EFHK", "amsterdam": "EHAM", "istanbul": "17058",
|
||
"paris": "LFPB", "hong kong": "HKO", "shenzhen": "LFS", "taipei": "466920",
|
||
"beijing": "ZBAA", "shanghai": "ZSPD", "guangzhou": "ZGGG", "qingdao": "ZSQD",
|
||
"chengdu": "ZUUU", "chongqing": "ZUCK", "wuhan": "ZHHH",
|
||
"new york": "KLGA", "los angeles": "KLAX", "chicago": "KORD",
|
||
"denver": "KBKF", "atlanta": "KATL", "miami": "KMIA",
|
||
"san francisco": "KSFO", "houston": "KHOU", "dallas": "KDAL",
|
||
"austin": "KAUS", "seattle": "KSEA",
|
||
"tel aviv": "LLBG",
|
||
}
|
||
# Settlement runway mapping — matches settlement anchor stations.
|
||
# Format: (low_number, high_number) order-independent; stored sorted for lookup.
|
||
SETTLEMENT_RUNWAY_PAIRS: Dict[str, Set[Tuple[str, str]]] = {
|
||
"shanghai": {("17L", "35R")},
|
||
"beijing": {("01", "19")},
|
||
"guangzhou": {("02L", "20R")},
|
||
"chengdu": {("02L", "20R")},
|
||
"chongqing": {("02L", "20R")},
|
||
"wuhan": {("04", "22")},
|
||
"seoul": {("15R", "33L")},
|
||
}
|
||
|
||
# All cities with active runway observation data (AMSC AWOS / AMOS).
|
||
RUNWAY_OBSERVATION_CITIES = {
|
||
"shanghai", "beijing", "guangzhou",
|
||
"chengdu", "chongqing", "wuhan", "qingdao",
|
||
"seoul", "busan",
|
||
}
|
||
|
||
# Wind regime sectors per airport (approximate, based on runway orientation + coastline).
|
||
# Values: {sea_breeze: (from_deg, to_deg), warm_advection: (from_deg, to_deg)}
|
||
WIND_REGIME: Dict[str, Dict[str, Tuple[int, int]]] = {
|
||
"shanghai": {"sea_breeze": (45, 140), "warm_advection": (180, 260)},
|
||
"seoul": {"sea_breeze": (270, 350), "warm_advection": (150, 230)},
|
||
"busan": {"sea_breeze": (120, 200), "warm_advection": (250, 340)},
|
||
"qingdao": {"sea_breeze": (90, 180), "warm_advection": (200, 300)},
|
||
"beijing": {"sea_breeze": (120, 200), "warm_advection": (220, 320)},
|
||
"guangzhou": {"sea_breeze": (120, 200), "warm_advection": (200, 300)},
|
||
"chengdu": {"sea_breeze": (0, 0), "warm_advection": (0, 0)},
|
||
"chongqing": {"sea_breeze": (0, 0), "warm_advection": (0, 0)},
|
||
"wuhan": {"sea_breeze": (0, 0), "warm_advection": (0, 0)},
|
||
}
|
||
|
||
# Legacy alias for backward compat with existing _select_focus_runway_obs / _focus_runway_pairs_for_city
|
||
FOCUS_RUNWAY_PAIRS = SETTLEMENT_RUNWAY_PAIRS
|
||
|
||
_FUNCTION_HASHTAGS_ZH = {
|
||
"runway": "#跑道观测",
|
||
"airport": "#机场观测",
|
||
"trade": "#交易机会",
|
||
}
|
||
_FUNCTION_HASHTAGS_EN = {
|
||
"runway": "#RunwayObs",
|
||
"airport": "#AirportObs",
|
||
"trade": "#TradeAlert",
|
||
}
|
||
|
||
|
||
def _city_hashtag(city: Optional[str]) -> Optional[str]:
|
||
text = str(city or "").strip()
|
||
if not text:
|
||
return None
|
||
parts = [part for part in re.split(r"[^A-Za-z0-9]+", text.title()) if part]
|
||
if not parts:
|
||
return None
|
||
return "#" + "".join(parts)
|
||
|
||
|
||
def _station_hashtag(station: Optional[str]) -> Optional[str]:
|
||
text = re.sub(r"[^A-Za-z0-9]+", "", str(station or "").upper())
|
||
return f"#{text}" if text else None
|
||
|
||
|
||
def _build_telegram_hashtag_line(
|
||
kind: str,
|
||
*,
|
||
city: Optional[str] = None,
|
||
station: Optional[str] = None,
|
||
extra: Optional[List[str]] = None,
|
||
language: Optional[str] = None,
|
||
) -> str:
|
||
tags: List[str] = []
|
||
tag_maps = (
|
||
(_FUNCTION_HASHTAGS_EN, _FUNCTION_HASHTAGS_ZH)
|
||
if _is_bilingual(language)
|
||
else ((_FUNCTION_HASHTAGS_ZH,) if _is_zh(language) else (_FUNCTION_HASHTAGS_EN,))
|
||
)
|
||
for tag_map in tag_maps:
|
||
primary = tag_map.get(kind)
|
||
if primary and primary not in tags:
|
||
tags.append(primary)
|
||
for item in extra or []:
|
||
added = False
|
||
for tag_map in tag_maps:
|
||
tag = tag_map.get(item)
|
||
if tag and tag not in tags:
|
||
tags.append(tag)
|
||
added = True
|
||
if not added and item and item not in tags:
|
||
tags.append(item)
|
||
city_tag = _city_hashtag(city)
|
||
if city_tag and city_tag not in tags:
|
||
tags.append(city_tag)
|
||
station_tag = _station_hashtag(station)
|
||
if station_tag and station_tag not in tags:
|
||
tags.append(station_tag)
|
||
return " ".join(tags)
|
||
|
||
|
||
def _fmt(value: Any) -> str:
|
||
"""Format a single temperature reading; returns '--' for missing values."""
|
||
if value is None:
|
||
return "--"
|
||
try:
|
||
f = float(value)
|
||
if not -80.0 < f < 80.0:
|
||
return "--"
|
||
return f"{f:.1f}"
|
||
except (TypeError, ValueError):
|
||
return "--"
|
||
|
||
|
||
def _normalize_runway_label(value: Any) -> str:
|
||
return re.sub(r"[^0-9A-Z]+", "", str(value or "").strip().upper())
|
||
|
||
|
||
def _runway_pair_key(r1: Any, r2: Any) -> Tuple[str, str]:
|
||
a = _normalize_runway_label(r1)
|
||
b = _normalize_runway_label(r2)
|
||
return tuple(sorted((a, b))) # type: ignore[return-value]
|
||
|
||
|
||
def _focus_runway_pairs_for_city(city: str) -> Set[Tuple[str, str]]:
|
||
return {_runway_pair_key(a, b) for a, b in FOCUS_RUNWAY_PAIRS.get(city, set())}
|
||
|
||
|
||
def _select_focus_runway_obs(
|
||
city: str,
|
||
runway_pairs: List[Any],
|
||
runway_temps: List[Any],
|
||
point_temps: Optional[List[Any]] = None,
|
||
) -> Tuple[List[Any], List[Any], List[Any]]:
|
||
"""Return only market-relevant runway pairs when configured for the city.
|
||
|
||
If a configured focus pair is not present in the upstream payload, fall back
|
||
to the original lists so the push still carries useful airport evidence.
|
||
"""
|
||
focus_pairs = _focus_runway_pairs_for_city(city)
|
||
if not focus_pairs or not runway_pairs or not runway_temps:
|
||
return runway_pairs, runway_temps, point_temps or []
|
||
|
||
selected_pairs: List[Any] = []
|
||
selected_temps: List[Any] = []
|
||
selected_points: List[Any] = []
|
||
points = point_temps or []
|
||
for i, (pair, temp) in enumerate(zip(runway_pairs, runway_temps)):
|
||
try:
|
||
r1, r2 = pair
|
||
except Exception:
|
||
continue
|
||
if _runway_pair_key(r1, r2) not in focus_pairs:
|
||
continue
|
||
selected_pairs.append(pair)
|
||
selected_temps.append(temp)
|
||
if i < len(points):
|
||
selected_points.append(points[i])
|
||
|
||
if selected_pairs:
|
||
return selected_pairs, selected_temps, selected_points
|
||
return runway_pairs, runway_temps, points
|
||
|
||
|
||
def _settlement_runway_for_city(city: str) -> Optional[Tuple[str, str]]:
|
||
"""Return the settlement runway pair for a city, if configured."""
|
||
pairs = SETTLEMENT_RUNWAY_PAIRS.get(str(city or "").strip().lower(), set())
|
||
return next(iter(pairs)) if pairs else None
|
||
|
||
|
||
def _is_settlement_runway(city: str, r1: str, r2: str) -> bool:
|
||
"""Check if a runway pair is the settlement anchor for this city."""
|
||
pair_set = SETTLEMENT_RUNWAY_PAIRS.get(str(city or "").strip().lower(), set())
|
||
return _runway_pair_key(r1, r2) in pair_set
|
||
|
||
|
||
def _wind_regime_label(city: str, wind_dir: Optional[int], language: Optional[str] = None) -> Optional[str]:
|
||
"""Classify wind direction into a thermal regime label."""
|
||
if wind_dir is None:
|
||
return None
|
||
regimes = WIND_REGIME.get(str(city or "").strip().lower(), {})
|
||
sea = regimes.get("sea_breeze")
|
||
warm = regimes.get("warm_advection")
|
||
if sea and sea[0] != sea[1] and sea[0] <= wind_dir <= sea[1]:
|
||
return _copy(language, "sea-breeze cooling", "海风降温")
|
||
if warm and warm[0] != warm[1] and warm[0] <= wind_dir <= warm[1]:
|
||
return _copy(language, "warm advection", "暖平流增强")
|
||
return None
|
||
|
||
|
||
def _compute_slope_15m(icao: str, current_temp: float) -> Optional[float]:
|
||
"""Estimate 15-minute temperature trend from runway_obs_log."""
|
||
try:
|
||
db = DBManager()
|
||
rows = db.get_runway_obs_recent(icao, minutes=20)
|
||
temps = []
|
||
for r in rows:
|
||
t = r.get("target_runway_max") or r.get("tdz_temp")
|
||
if t is not None:
|
||
temps.append(float(t))
|
||
if len(temps) >= 2:
|
||
# Compare latest vs earliest in ~15 min window
|
||
return round(current_temp - temps[0], 1)
|
||
except Exception:
|
||
pass
|
||
return None
|
||
|
||
|
||
def _runway_heat_signal(
|
||
current_temp: float,
|
||
slope_15m: Optional[float],
|
||
wind_dir: Optional[int],
|
||
city: str,
|
||
language: Optional[str] = None,
|
||
) -> str:
|
||
"""Compute a simple runway heat signal label."""
|
||
if slope_15m is None:
|
||
return ""
|
||
regime = _wind_regime_label(city, wind_dir, language)
|
||
warm_regime = _copy(language, "warm advection", "暖平流增强")
|
||
sea_regime = _copy(language, "sea-breeze cooling", "海风降温")
|
||
if slope_15m >= 1.0:
|
||
return _copy(language, "🚀 Peak push strengthening", "🚀 冲顶增强") if regime == warm_regime else _copy(language, "🔥 Warming", "🔥 升温中")
|
||
if slope_15m >= 0.5:
|
||
return _copy(language, "🔥 Warming", "🔥 升温中")
|
||
if slope_15m >= -0.2:
|
||
return _copy(language, "⚠️ Watch sea-breeze cooling", "⚠️ 高位观察") if regime == sea_regime else _copy(language, "⏸️ Holding near high", "⏸️ 高位横盘")
|
||
return _copy(language, "🧊 Peak-risk cooling", "🧊 过峰风险")
|
||
|
||
|
||
def _focused_runway_max(city: str, city_weather: Dict[str, Any]) -> Optional[float]:
|
||
amos = city_weather.get("amos") or {}
|
||
runway_obs = (amos.get("runway_obs") or {}) if isinstance(amos, dict) else {}
|
||
runway_pairs = runway_obs.get("runway_pairs") or []
|
||
runway_temps = runway_obs.get("temperatures") or []
|
||
runway_pairs, runway_temps, _points = _select_focus_runway_obs(
|
||
city,
|
||
runway_pairs,
|
||
runway_temps,
|
||
runway_obs.get("point_temperatures") or [],
|
||
)
|
||
del runway_pairs
|
||
valid = [float(t) for (t, _d) in runway_temps if t is not None]
|
||
return max(valid) if valid else None
|
||
|
||
|
||
_AIRPORT_PUSH_STATE_PATH = os.path.join(
|
||
os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
|
||
"data", "airport_push_state.json",
|
||
)
|
||
|
||
|
||
def _load_airport_state() -> Dict[str, Any]:
|
||
path = _AIRPORT_PUSH_STATE_PATH
|
||
if not os.path.exists(path):
|
||
return {"last_by_city": {}}
|
||
try:
|
||
with open(path, "r", encoding="utf-8") as fh:
|
||
data = json.load(fh)
|
||
if isinstance(data, dict):
|
||
data.setdefault("last_by_city", {})
|
||
return data
|
||
except Exception:
|
||
pass
|
||
return {"last_by_city": {}}
|
||
|
||
|
||
def _save_airport_state(state: Dict[str, Any]) -> None:
|
||
path = _AIRPORT_PUSH_STATE_PATH
|
||
os.makedirs(os.path.dirname(path), exist_ok=True)
|
||
tmp = f"{path}.tmp"
|
||
with open(tmp, "w", encoding="utf-8") as fh:
|
||
json.dump(state, fh, ensure_ascii=False, indent=2)
|
||
os.replace(tmp, path)
|
||
|
||
|
||
_AROME_CACHE: Dict[str, Any] = {}
|
||
_AROME_CACHE_TTL_SEC = 600 # AROME HD updates every 15 min; cache 10 min
|
||
|
||
def _fetch_arome_temp() -> Optional[float]:
|
||
"""Fetch latest AROME France HD 15-min temperature for LFPB from Open-Meteo.
|
||
|
||
Cached for 10 minutes since the model only updates every 15 minutes.
|
||
"""
|
||
now = time.time()
|
||
cached = _AROME_CACHE.get("value")
|
||
cached_at = _AROME_CACHE.get("ts", 0)
|
||
if cached is not None and (now - cached_at) < _AROME_CACHE_TTL_SEC:
|
||
return cached
|
||
try:
|
||
url = (
|
||
"https://api.open-meteo.com/v1/forecast?"
|
||
"latitude=48.9673&longitude=2.4277"
|
||
"&models=meteofrance_arome_france_hd"
|
||
"&minutely_15=temperature_2m"
|
||
"&timezone=Europe/Paris"
|
||
"&forecast_minutely_15=2"
|
||
)
|
||
resp = _get_http_session().get(url, timeout=8)
|
||
data = resp.json()
|
||
temps = (data.get("minutely_15") or {}).get("temperature_2m") or []
|
||
result = float(temps[-1]) if temps else None
|
||
_AROME_CACHE["value"] = result
|
||
_AROME_CACHE["ts"] = now
|
||
return result
|
||
except Exception:
|
||
return _AROME_CACHE.get("value")
|
||
|
||
|
||
_LAST_AEROWEB: Dict[str, Any] = {} # {"temp": 31.0, "max_so_far": 31.0, "max_time": "14:00", "ts": epoch}
|
||
|
||
|
||
def _build_narrative(
|
||
current_temp: Optional[float],
|
||
max_so_far: Optional[float],
|
||
deb_pred: Optional[float],
|
||
models: Dict[str, Any],
|
||
city_weather: Dict[str, Any],
|
||
) -> str:
|
||
"""Generate a market-structure interpretation based on current state."""
|
||
if current_temp is None:
|
||
return ""
|
||
vals = sorted([v for v in models.values() if isinstance(v, (int, float))])
|
||
model_lo = vals[0] if vals else None
|
||
model_hi = vals[-1] if vals else None
|
||
h = 12
|
||
try:
|
||
h = int(str(city_weather.get("local_time") or "12")[:2])
|
||
except ValueError:
|
||
pass
|
||
|
||
lines = []
|
||
# Delta vs daily high
|
||
if max_so_far is not None:
|
||
d = current_temp - max_so_far
|
||
if d >= 0.3:
|
||
lines.append(f"🔺 当前已创今日新高（+{d:.1f}°），持续冲高")
|
||
elif d >= -1.0:
|
||
lines.append(f"紧贴日高，距峰值仅 {abs(d):.1f}°")
|
||
else:
|
||
lines.append(f"低于日高 {abs(d):.1f}°")
|
||
|
||
# DEB relation
|
||
if deb_pred is not None:
|
||
if current_temp > deb_pred:
|
||
lines.append("DEB 已被突破，模型偏保守")
|
||
elif max_so_far is not None and max_so_far >= deb_pred:
|
||
pass # already covered by 日高已触及
|
||
elif current_temp > deb_pred - 2.0:
|
||
lines.append("DEB 仍在可达范围")
|
||
|
||
# Model position + time context
|
||
if model_lo is not None and model_hi is not None:
|
||
if current_temp < model_lo:
|
||
if h >= 17:
|
||
lines.append("低于所有模型，晚间升温窗口有限")
|
||
else:
|
||
lines.append("低于主流模型，日间仍有升温空间")
|
||
elif current_temp <= model_hi:
|
||
lines.append("位于模型区间内，市场在预期路径上")
|
||
else:
|
||
lines.append("已超出最热模型，市场进入超预期定价")
|
||
elif max_so_far is not None and current_temp < max_so_far - 2.0:
|
||
if h < 14:
|
||
lines.append("日间仍可能二次冲高")
|
||
else:
|
||
lines.append("已脱离日内峰值")
|
||
|
||
return "\n".join(lines)
|
||
|
||
|
||
def _build_airport_status_message(
|
||
city: str,
|
||
city_weather: Dict[str, Any],
|
||
deb_pred: Optional[float],
|
||
local_time: str = "",
|
||
state: str = "",
|
||
source_label: str = "",
|
||
arome_temp: Optional[float] = None,
|
||
aeroweb_available: bool = False,
|
||
language: Optional[str] = None,
|
||
) -> str:
|
||
language = _normalize_push_language(language or _telegram_push_language())
|
||
_AIRPORT_EN = {"seoul": "Incheon", "singapore": "Changi", "busan": "Gimhae", "tokyo": "Haneda",
|
||
"ankara": "Esenboğa", "helsinki": "Vantaa", "amsterdam": "Schiphol",
|
||
"istanbul": "Airport", "paris": "Le Bourget",
|
||
"hong kong": "Observatory", "shenzhen": "LFS Observatory",
|
||
"taipei": "Songshan", "beijing": "Capital", "shanghai": "Pudong",
|
||
"guangzhou": "Baiyun", "qingdao": "Jiaodong",
|
||
"chengdu": "Shuangliu", "chongqing": "Jiangbei", "wuhan": "Tianhe",
|
||
"new york": "LaGuardia", "los angeles": "LAX", "chicago": "O'Hare",
|
||
"denver": "Buckley", "atlanta": "Hartsfield", "miami": "Intl",
|
||
"san francisco": "SFO", "houston": "Hobby", "dallas": "Love Field",
|
||
"austin": "Bergstrom", "seattle": "Sea-Tac",
|
||
"tel aviv": "Ben Gurion"}
|
||
en_name = city.title()
|
||
ap_name = _AIRPORT_EN.get(city, "")
|
||
time_suffix = f" · {local_time}" if local_time else ""
|
||
|
||
amos = city_weather.get("amos") or {}
|
||
runway_data = amos.get("runway_obs") or {}
|
||
runway_pairs = runway_data.get("runway_pairs") or []
|
||
runway_temps = runway_data.get("temperatures") or []
|
||
point_temps = runway_data.get("point_temperatures") or []
|
||
is_amsc = amos.get("source") in ("amsc_awos", "amos")
|
||
has_runway = bool(runway_pairs and (runway_temps or point_temps))
|
||
amos_icao = amos.get("icao") or HIGH_FREQ_AIRPORT_ICAO.get(city, "")
|
||
settlement_pair = _settlement_runway_for_city(city)
|
||
|
||
# ── Display temp: settlement runway max first, then airport temp ──
|
||
settlement_temp: Optional[float] = None
|
||
display_temp: Optional[float] = None
|
||
if point_temps:
|
||
for pt in point_temps:
|
||
rw = str(pt.get("runway") or "")
|
||
rw_parts = [p.strip() for p in str(rw).split("/") if p.strip()]
|
||
if settlement_pair and len(rw_parts) >= 2 and _runway_pair_key(rw_parts[0], rw_parts[1]) == _runway_pair_key(*settlement_pair):
|
||
tmax = pt.get("target_runway_max")
|
||
if tmax is not None:
|
||
settlement_temp = float(tmax)
|
||
break
|
||
if settlement_temp is not None:
|
||
display_temp = settlement_temp
|
||
if display_temp is None:
|
||
if point_temps:
|
||
valid_tmax = [float(p.get("target_runway_max")) for p in point_temps if p.get("target_runway_max") is not None]
|
||
display_temp = max(valid_tmax) if valid_tmax else None
|
||
if display_temp is None:
|
||
station_temp = None
|
||
mgm_nearby = city_weather.get("mgm_nearby") or []
|
||
airport_icao = HIGH_FREQ_AIRPORT_ICAO.get(city, "")
|
||
for row in mgm_nearby:
|
||
if str(row.get("istNo") or "") == airport_icao or str(row.get("icao") or "") == airport_icao:
|
||
station_temp = row.get("temp")
|
||
break
|
||
if station_temp is None and mgm_nearby:
|
||
logger.warning(
|
||
"airport message fallback city={}: station {} not found in mgm_nearby, falling back to current.temp",
|
||
city, airport_icao,
|
||
)
|
||
if station_temp is None:
|
||
station_temp = (city_weather.get("current") or {}).get("temp")
|
||
display_temp = station_temp
|
||
|
||
# ── Heat model ──
|
||
wind_dir = amos.get("wind_dir") if is_amsc else None
|
||
slope_15m = _compute_slope_15m(amos_icao, display_temp) if is_amsc and display_temp is not None else None
|
||
heat_signal = _runway_heat_signal(display_temp or 0, slope_15m, wind_dir, city, language) if is_amsc else ""
|
||
wind_label = _wind_regime_label(city, wind_dir, language) if is_amsc and wind_dir is not None else None
|
||
|
||
max_so_far, max_temp_time = _get_airport_daily_high(city_weather)
|
||
# ── Build message ──
|
||
lines: List[str] = []
|
||
|
||
# Header
|
||
hashtag_line = _build_telegram_hashtag_line(
|
||
"runway" if has_runway else "airport",
|
||
city=city,
|
||
language=language,
|
||
)
|
||
icao_display = f"{amos_icao} · " if amos_icao else ""
|
||
settlement_str = f" · ★{settlement_pair[0]}/{settlement_pair[1]}" if settlement_pair else ""
|
||
header = f"{icao_display}{en_name} / {ap_name}{settlement_str}{time_suffix}" if ap_name else f"{icao_display}{en_name}{settlement_str}{time_suffix}"
|
||
lines.append(hashtag_line)
|
||
lines.append("")
|
||
lines.append(header)
|
||
|
||
# Heat signal
|
||
if heat_signal:
|
||
lines.append("")
|
||
lines.append(heat_signal)
|
||
if state:
|
||
lines.append(state)
|
||
|
||
# All runway detail block
|
||
if has_runway:
|
||
lines.append("")
|
||
for i, ((r1, r2), (t, _d)) in enumerate(zip(runway_pairs, runway_temps)):
|
||
if t is None:
|
||
continue
|
||
pts = point_temps[i] if i < len(point_temps) else {}
|
||
tdz = pts.get("tdz_temp")
|
||
mid = pts.get("mid_temp")
|
||
end = pts.get("end_temp")
|
||
is_settlement = _is_settlement_runway(city, r1, r2)
|
||
marker = _copy(language, " ★Settlement", " ★结算") if is_settlement else ""
|
||
tmax = pts.get("target_runway_max")
|
||
if tdz is not None or mid is not None or end is not None:
|
||
line = f"{r1}/{r2}{marker} TDZ:{_fmt(tdz)} MID:{_fmt(mid)} END:{_fmt(end)}"
|
||
if tmax is not None:
|
||
line += f" max:{tmax:.1f}"
|
||
lines.append(line)
|
||
else:
|
||
temp_symbol = str(city_weather.get("temp_symbol") or "°C").strip()
|
||
lines.append(f"{r1}/{r2}{marker} {t:.1f}{temp_symbol}")
|
||
|
||
# Summary stats
|
||
lines.append("")
|
||
temp_symbol = str(city_weather.get("temp_symbol") or "°C").strip()
|
||
cur_str = f"{display_temp:.1f}{temp_symbol}" if display_temp is not None else "--"
|
||
|
||
if city == "paris":
|
||
if aeroweb_available and display_temp is not None:
|
||
lines.append(f"{_copy(language, 'Current observation', '当前实况')}: {cur_str}")
|
||
else:
|
||
lines.append(_copy(language, "Current observation: unavailable", "当前实况：暂无"))
|
||
else:
|
||
if has_runway:
|
||
current_label = (
|
||
_copy(language, "Settlement runway now", "结算跑道当前")
|
||
if settlement_pair
|
||
else _copy(language, "Runway now", "跑道当前")
|
||
)
|
||
lines.append(f"{current_label}: {cur_str}")
|
||
else:
|
||
lines.append(f"{_copy(language, 'Current', '当前')}: {cur_str}")
|
||
|
||
if city == "paris":
|
||
if aeroweb_available and max_so_far is not None:
|
||
time_str = f" ({max_temp_time})" if max_temp_time and not _is_zh(language) else (f"（{max_temp_time}）" if max_temp_time else "")
|
||
lines.append(f"{_copy(language, 'Observed high', '日高实况')}: {max_so_far:.1f}{temp_symbol}{time_str}")
|
||
elif not aeroweb_available:
|
||
last_temp = _LAST_AEROWEB.get("temp")
|
||
if last_temp is not None:
|
||
last_time = _LAST_AEROWEB.get("max_time", "")
|
||
time_str = f" ({last_time})" if last_time and not _is_zh(language) else (f"（{last_time}）" if last_time else "")
|
||
lines.append(f"{_copy(language, 'Latest observation', '最近实况')}: {last_temp:.1f}{temp_symbol}{time_str}")
|
||
elif max_so_far is not None:
|
||
time_str = f" ({max_temp_time})" if max_temp_time and not _is_zh(language) else (f"（{max_temp_time}）" if max_temp_time else "")
|
||
if has_runway:
|
||
high_label = _copy(language, "Today's runway high", "今日跑道高点")
|
||
lines.append(f"{high_label}: {max_so_far:.1f}{temp_symbol}{time_str}")
|
||
else:
|
||
high_label = _copy(language, "Today's high", "日高")
|
||
lines.append(f"{high_label}: {max_so_far:.1f}{temp_symbol}{time_str}")
|
||
if slope_15m is not None:
|
||
sign = "+" if slope_15m >= 0 else ""
|
||
lines.append(f"{_copy(language, '15m trend', '15分钟趋势')}: {sign}{slope_15m:.1f}°")
|
||
if wind_dir is not None:
|
||
wind_str = f"{_copy(language, 'Wind dir', '风向')}: {wind_dir}°"
|
||
if wind_label:
|
||
wind_str += f" {wind_label}"
|
||
lines.append(wind_str)
|
||
# --- AMSC METAR temp + time for Chinese cities (Beijing time) ---
|
||
if is_amsc:
|
||
raw_metar = amos.get("raw_metar") or ""
|
||
if raw_metar:
|
||
parts = raw_metar.split()
|
||
# Extract temp/dew: "20/17" → 20
|
||
metar_temp = None
|
||
for p in parts:
|
||
m = re.match(r"^(M?\d{2})/(M?\d{2})$", p)
|
||
if m:
|
||
t = m.group(1)
|
||
metar_temp = str(int(t.replace("M", "-")))
|
||
break
|
||
# Extract time: "211930Z" → Beijing time (UTC+8)
|
||
metar_time = None
|
||
for p in parts:
|
||
m = re.match(r"^(\d{2})(\d{2})(\d{2})Z$", p)
|
||
if m:
|
||
_day, hh, mm = int(m.group(1)), int(m.group(2)), m.group(3)
|
||
bj_h = hh + 8
|
||
if bj_h >= 24:
|
||
bj_h -= 24
|
||
metar_time = f"{_copy(language, 'Beijing time', '北京时')} {bj_h:02d}:{mm}"
|
||
break
|
||
if metar_temp or metar_time:
|
||
bits = []
|
||
if metar_temp:
|
||
bits.append(f"{metar_temp}{temp_symbol}")
|
||
if metar_time:
|
||
bits.append(metar_time)
|
||
lines.append(f"{_copy(language, 'METAR', '报文')}: {' '.join(bits)}")
|
||
if deb_pred is not None:
|
||
if city == "paris":
|
||
if aeroweb_available and display_temp is not None:
|
||
diff = display_temp - deb_pred
|
||
sign = "+" if diff >= 0 else ""
|
||
suffix = _copy(language, f" (vs obs {sign}{diff:.1f}°)", f"（距实况 {sign}{diff:.1f}°）")
|
||
lines.append(f"DEB: {deb_pred:.1f}{temp_symbol}{suffix}" if not _is_zh(language) else f"DEB：{deb_pred:.1f}{temp_symbol}{suffix}")
|
||
elif not aeroweb_available:
|
||
last_temp = _LAST_AEROWEB.get("temp")
|
||
if last_temp is not None:
|
||
diff = last_temp - deb_pred
|
||
sign = "+" if diff >= 0 else ""
|
||
suffix = _copy(language, f" (vs latest obs {sign}{diff:.1f}°)", f"（距最近实况 {sign}{diff:.1f}°）")
|
||
lines.append(f"DEB: {deb_pred:.1f}{temp_symbol}{suffix}" if not _is_zh(language) else f"DEB：{deb_pred:.1f}{temp_symbol}{suffix}")
|
||
else:
|
||
lines.append(f"DEB: {deb_pred:.1f}{temp_symbol}" if not _is_zh(language) else f"DEB：{deb_pred:.1f}{temp_symbol}")
|
||
else:
|
||
lines.append(f"DEB: {deb_pred:.1f}{temp_symbol}" if not _is_zh(language) else f"DEB：{deb_pred:.1f}{temp_symbol}")
|
||
elif display_temp is not None and display_temp > deb_pred:
|
||
suffix = _copy(language, f" (already above +{display_temp - deb_pred:.1f}°)", f"（已突破 +{display_temp - deb_pred:.1f}°）")
|
||
lines.append(f"DEB: {deb_pred:.1f}{temp_symbol}{suffix}" if not _is_zh(language) else f"DEB：{deb_pred:.1f}{temp_symbol}{suffix}")
|
||
else:
|
||
lines.append(f"DEB: {deb_pred:.1f}{temp_symbol}" if not _is_zh(language) else f"DEB：{deb_pred:.1f}{temp_symbol}")
|
||
|
||
if city == "paris":
|
||
lines.append("")
|
||
if aeroweb_available and display_temp is not None:
|
||
label = _copy(language, "AEROWEB airport obs", "AEROWEB 机场实况")
|
||
lines.append(f"📡 {label}: {display_temp:.1f}{temp_symbol} · Météo-France")
|
||
else:
|
||
lines.append(_copy(language, "📡 AEROWEB airport obs: unavailable", "📡 AEROWEB 机场实况：暂不可用"))
|
||
if arome_temp is not None:
|
||
if aeroweb_available and display_temp is not None:
|
||
d = arome_temp - display_temp
|
||
sign = "+" if d >= 0 else ""
|
||
label = _copy(language, "AROME HD 15m nowcast", "AROME HD 15分钟临近预报")
|
||
suffix = _copy(language, f" (vs obs {sign}{d:.1f}°)", f"（较实况 {sign}{d:.1f}°）")
|
||
lines.append(f"🕐 {label}: {arome_temp:.1f}{temp_symbol}{suffix}")
|
||
else:
|
||
label = _copy(language, "AROME HD 15m nowcast", "AROME HD 15分钟临近预报")
|
||
lines.append(f"🕐 {label}: {arome_temp:.1f}{temp_symbol}")
|
||
else:
|
||
label = _copy(language, "AROME HD 15m nowcast", "AROME HD 15分钟临近预报")
|
||
lines.append(f"🕐 {label}: --")
|
||
if not aeroweb_available:
|
||
lines.append("")
|
||
lines.append(_copy(language, "Note: showing model reference only; observed high is not updating.", "提示：当前仅显示模型参考，不更新实况日高。"))
|
||
elif source_label:
|
||
lines.append("")
|
||
lines.append(f"📡 {source_label}")
|
||
|
||
# Model summary (compact)
|
||
models = city_weather.get("multi_model") or {}
|
||
if isinstance(models, dict) and len(models) >= 2:
|
||
vals = sorted([(v, k) for k, v in models.items() if isinstance(v, (int, float))])
|
||
if len(vals) >= 2:
|
||
lo, hi = vals[0][0], vals[-1][0]
|
||
spread = hi - lo
|
||
if spread <= 2.0:
|
||
spread_label = _copy(language, "low dispersion", "低分歧")
|
||
elif spread <= 4.0:
|
||
spread_label = _copy(language, "moderate dispersion", "中等分歧")
|
||
else:
|
||
spread_label = _copy(language, "high dispersion", "高分歧")
|
||
range_label = _copy(language, "Model range", "模型区间")
|
||
lines.append(f"{range_label}: {lo:.1f}~{hi:.1f}{temp_symbol} {spread_label}")
|
||
|
||
return "\n".join(lines)
|
||
|
||
|
||
def _get_airport_daily_high(city_weather: Dict[str, Any]):
|
||
"""Get today's observed high from METAR/AMOS airport history."""
|
||
airport = city_weather.get("airport_current") or {}
|
||
max_so_far = airport.get("max_so_far")
|
||
max_time = airport.get("max_temp_time")
|
||
if max_so_far is not None:
|
||
try:
|
||
max_so_far = round(float(max_so_far), 1)
|
||
except Exception:
|
||
max_so_far = None
|
||
return max_so_far, max_time
|
||
|
||
|
||
# Per-city push interval — unified to 60s, obs_time dedup prevents spam
|
||
_AIRPORT_PUSH_INTERVAL = {
|
||
"seoul": 60, "busan": 60, "tokyo": 60, "ankara": 60,
|
||
"helsinki": 60, "amsterdam": 60, "istanbul": 60, "paris": 60,
|
||
"hong kong": 60, "shenzhen": 60, "singapore": 60, "taipei": 60,
|
||
"beijing": 60, "shanghai": 60, "guangzhou": 60, "qingdao": 60,
|
||
"chengdu": 60, "chongqing": 60, "wuhan": 60,
|
||
"new york": 60, "los angeles": 60, "chicago": 60, "denver": 60,
|
||
"atlanta": 60, "miami": 60, "san francisco": 60, "houston": 60,
|
||
"dallas": 60, "austin": 60, "seattle": 60,
|
||
"tel aviv": 60,
|
||
}
|
||
# Per-city temperature window threshold (°C below DEB predicted high)
|
||
# Continental airports: wider window (temp rises steadily over land)
|
||
# Maritime airports: narrower (sea breeze moderates temp)
|
||
# Strong sea breeze: tightest (marine air suppresses peak)
|
||
_AIRPORT_HEAT_THRESHOLD = {
|
||
"seoul": 3.0, "ankara": 3.0, "istanbul": 3.0, "paris": 3.0,
|
||
"busan": 2.0, "tokyo": 2.0, "amsterdam": 2.0, "helsinki": 2.0,
|
||
"hong kong": 1.5, "shenzhen": 1.5, "taipei": 1.5,
|
||
}
|
||
|
||
|
||
# 部分城市 Open-Meteo 算出的 peak 窗口偏窄，用 fallback 拓宽
|
||
# （例如沿海城市受海风影响，高温窗口被压缩）
|
||
_AIRPORT_PEAK_FALLBACK = {
|
||
"busan": (12, 16),
|
||
}
|
||
|
||
def _in_peak_time_window(city: str, city_weather: Dict[str, Any]) -> bool:
|
||
"""Check if current local time is within the expected peak temperature window."""
|
||
peak = city_weather.get("peak") or {}
|
||
first_h = peak.get("first_h")
|
||
last_h = peak.get("last_h")
|
||
fallback = _AIRPORT_PEAK_FALLBACK.get(city)
|
||
if fallback and ((first_h is None) or (last_h is not None and last_h - first_h < 3)):
|
||
first_h, last_h = fallback
|
||
local_time = city_weather.get("local_time") or ""
|
||
if first_h is None or not local_time:
|
||
return False
|
||
try:
|
||
current_h, current_m = int(local_time[:2]), int(local_time[3:5])
|
||
current_minutes = current_h * 60 + current_m
|
||
# Window: first_h - 4h to last_h + 2h
|
||
start_min = max(0, (first_h - 4) * 60)
|
||
end_min = min(24 * 60 - 1, (last_h + 2) * 60)
|
||
return start_min <= current_minutes <= end_min
|
||
except Exception:
|
||
return False
|
||
|
||
|
||
def _check_rising_trend(icao: str) -> bool:
|
||
"""Check if temperature has been rising over the last 30-60 minutes."""
|
||
try:
|
||
from src.database.db_manager import DBManager
|
||
db = DBManager()
|
||
obs = db.get_airport_obs_recent(icao, minutes=60)
|
||
if not obs:
|
||
return False
|
||
temps = [r.get("temp_c") for r in obs if r.get("temp_c") is not None]
|
||
if len(temps) < 4:
|
||
return False
|
||
# Check: last 3 readings are increasing
|
||
recent = temps[-3:]
|
||
if recent[2] > recent[1] > recent[0]:
|
||
return True
|
||
# Or: current > 30 min ago
|
||
if len(temps) >= 4:
|
||
mid = len(temps) // 2
|
||
if temps[-1] > temps[mid]:
|
||
return True
|
||
return False
|
||
except Exception:
|
||
return False
|
||
|
||
|
||
def _process_airport_city(
|
||
city: str,
|
||
now_ts: int,
|
||
last_city: dict,
|
||
chat_ids: List[str],
|
||
bot: Any,
|
||
) -> Optional[Tuple[str, dict]]:
|
||
"""Process one airport city and return (city, new_state_entry) or None.
|
||
|
||
This is the per-city unit used by the concurrent thread pool in
|
||
``_run_high_freq_airport_cycle``.
|
||
"""
|
||
last_city_ts = int(last_city.get("ts") or 0)
|
||
last_obs_time = str(last_city.get("obs_time") or "")
|
||
city_interval = _AIRPORT_PUSH_INTERVAL.get(city, 600)
|
||
if now_ts - last_city_ts < city_interval:
|
||
return None
|
||
|
||
from web.app import _analyze # lazy import — only the bot process needs it
|
||
|
||
city_weather: Dict[str, Any] = {}
|
||
deb_pred: Optional[float] = None
|
||
try:
|
||
city_weather = _analyze(city, force_refresh_observations_only=True)
|
||
deb_raw = (city_weather.get("deb") or {}).get("prediction")
|
||
if deb_raw is not None:
|
||
deb_pred = float(deb_raw)
|
||
except Exception:
|
||
logger.exception("airport analyze failed for city={}", city)
|
||
return None
|
||
|
||
# Extract airport-level temperature
|
||
amos = city_weather.get("amos") or {}
|
||
mgm_nearby = city_weather.get("mgm_nearby") or []
|
||
airport_icao = HIGH_FREQ_AIRPORT_ICAO.get(city, "")
|
||
airport_row = None
|
||
for row in mgm_nearby:
|
||
if str(row.get("istNo") or "") == airport_icao or str(row.get("icao") or "") == airport_icao:
|
||
airport_row = row
|
||
break
|
||
if not airport_row:
|
||
airport_primary = city_weather.get("airport_primary") or {}
|
||
if airport_primary.get("temp") is not None:
|
||
airport_row = airport_primary
|
||
else:
|
||
current_fallback = city_weather.get("current") or {}
|
||
if current_fallback.get("temp") is not None:
|
||
airport_row = current_fallback
|
||
else:
|
||
logger.warning(
|
||
"airport push skipped city={}: station {} not found in mgm_nearby, "
|
||
"airport_primary, or current (mgm={} rows)",
|
||
city, airport_icao, len(mgm_nearby),
|
||
)
|
||
return None
|
||
station_temp = airport_row.get("temp") if airport_row else None
|
||
current_obs_time = str(airport_row.get("obs_time") or "")
|
||
|
||
runway_obs = (amos.get("runway_obs") or {})
|
||
runway_pairs = runway_obs.get("runway_pairs") or []
|
||
runway_temps = runway_obs.get("temperatures") or []
|
||
runway_pairs, runway_temps, _point_temps = _select_focus_runway_obs(
|
||
city, runway_pairs, runway_temps,
|
||
runway_obs.get("point_temperatures") or [],
|
||
)
|
||
if runway_temps:
|
||
valid_temps = [t for (t, _d) in runway_temps if t is not None]
|
||
if valid_temps:
|
||
station_temp = max(valid_temps)
|
||
amos_obs_time = amos.get("observation_time") or ""
|
||
if amos_obs_time:
|
||
current_obs_time = amos_obs_time
|
||
|
||
current_temp = station_temp
|
||
if current_temp is None:
|
||
airport_primary = city_weather.get("airport_primary") or {}
|
||
current_temp = airport_primary.get("temp") or (city_weather.get("current") or {}).get("temp")
|
||
if not current_obs_time:
|
||
current_obs_time = str(airport_primary.get("obs_time") or "")
|
||
source_label = "" # human-readable data source for Paris messages
|
||
arome_temp_val = None # AROME HD temperature for display (always fetched for comparison)
|
||
aeroweb_available = False
|
||
if city == "paris":
|
||
arome_temp_val = _fetch_arome_temp()
|
||
airport_primary = city_weather.get("airport_primary") or {}
|
||
# Detect AEROWEB availability
|
||
if airport_primary.get("source_code") == "aeroweb" and airport_primary.get("temp") is not None:
|
||
aeroweb_available = True
|
||
source_label = "AEROWEB 机场实况 · Météo-France"
|
||
# Update last known AEROWEB cache
|
||
_LAST_AEROWEB["temp"] = float(airport_primary["temp"])
|
||
_LAST_AEROWEB["ts"] = time.time()
|
||
# Get daily high from airport data
|
||
aero_max = (city_weather.get("airport_current") or {}).get("max_so_far")
|
||
aero_max_time = (city_weather.get("airport_current") or {}).get("max_temp_time")
|
||
if aero_max is not None:
|
||
_LAST_AEROWEB["max_so_far"] = float(aero_max)
|
||
_LAST_AEROWEB["max_time"] = str(aero_max_time or "")[11:16] if aero_max_time else ""
|
||
# Allow Paris pushes even when AEROWEB is down (show cached/last-known data)
|
||
if city == "paris" and not aeroweb_available and deb_pred is not None:
|
||
pass
|
||
elif current_temp is None or deb_pred is None:
|
||
return None
|
||
|
||
# Dedup: same observation → skip (with delayed retry for HK / LFS)
|
||
_CITIES_WITH_DELAYED_API = {"hong kong", "shenzhen"}
|
||
if (current_obs_time and last_obs_time and current_obs_time == last_obs_time
|
||
and city in _CITIES_WITH_DELAYED_API
|
||
and now_ts - last_city_ts > 540):
|
||
time.sleep(4)
|
||
try:
|
||
city_weather = _analyze(city, force_refresh_observations_only=True)
|
||
deb_raw2 = (city_weather.get("deb") or {}).get("prediction")
|
||
if deb_raw2 is not None:
|
||
deb_pred = float(deb_raw2)
|
||
mgm_nearby2 = city_weather.get("mgm_nearby") or []
|
||
row2 = None
|
||
for r in mgm_nearby2:
|
||
if str(r.get("istNo") or "") == airport_icao or str(r.get("icao") or "") == airport_icao:
|
||
row2 = r
|
||
break
|
||
if not row2 and mgm_nearby2:
|
||
row2 = mgm_nearby2[0]
|
||
retry_obs = str(row2.get("obs_time") or "") if row2 else ""
|
||
if retry_obs and retry_obs != last_obs_time:
|
||
current_obs_time = retry_obs
|
||
station_temp = row2.get("temp") if row2 else None
|
||
current_temp = station_temp or (city_weather.get("current") or {}).get("temp")
|
||
if current_temp is None or deb_pred is None:
|
||
return None
|
||
else:
|
||
return None
|
||
except Exception:
|
||
return None
|
||
elif current_obs_time and last_obs_time and current_obs_time == last_obs_time:
|
||
return None
|
||
|
||
obs_local = (
|
||
((city_weather.get("amos") or {}).get("observation_time_local") or "")[11:16]
|
||
if len(str((city_weather.get("amos") or {}).get("observation_time_local") or "")) >= 16
|
||
else (city_weather.get("airport_current") or {}).get("obs_time")
|
||
or city_weather.get("local_time")
|
||
or ""
|
||
)
|
||
message = _build_airport_status_message(city, city_weather, deb_pred, obs_local, state="", source_label=source_label, arome_temp=arome_temp_val, aeroweb_available=aeroweb_available)
|
||
|
||
# Send to all target chats
|
||
sent = False
|
||
for chat_id in chat_ids:
|
||
try:
|
||
kwargs = {}
|
||
thread_id = _resolve_thread_id(chat_id, city)
|
||
if thread_id:
|
||
kwargs["message_thread_id"] = thread_id
|
||
_rate_limited_send(bot, chat_id, message, **kwargs)
|
||
sent = True
|
||
except Exception as exc:
|
||
logger.warning("airport push failed city={} chat_id={}: {}", city, chat_id, exc)
|
||
|
||
if sent:
|
||
logger.info("airport status pushed city={} temp={} deb={} obs_time={}",
|
||
city, current_temp, deb_pred, current_obs_time)
|
||
return (city, {"ts": now_ts, "active": True, "obs_time": current_obs_time})
|
||
|
||
return None
|
||
|
||
|
||
def _run_high_freq_airport_cycle(
|
||
bot: Any,
|
||
config: Dict[str, Any],
|
||
chat_ids: List[str],
|
||
state: Dict[str, Any],
|
||
) -> bool:
|
||
state_dirty = False
|
||
now_ts = int(time.time())
|
||
last_by_city = state.setdefault("last_by_city", {})
|
||
max_workers = max(1, min(4, _env_int("TELEGRAM_AIRPORT_PUSH_MAX_WORKERS", 1)))
|
||
logger.info("airport cycle tick cities={} max_workers={}", len(HIGH_FREQ_AIRPORT_CITIES), max_workers)
|
||
|
||
cities = sorted(HIGH_FREQ_AIRPORT_CITIES)
|
||
pool = _get_airport_executor(max_workers)
|
||
futures = {
|
||
pool.submit(
|
||
_process_airport_city,
|
||
city,
|
||
now_ts,
|
||
last_by_city.get(city) or {},
|
||
chat_ids,
|
||
bot,
|
||
): city
|
||
for city in cities
|
||
}
|
||
for future in as_completed(futures):
|
||
try:
|
||
result = future.result()
|
||
except Exception:
|
||
logger.exception("airport city task crashed city={}", futures[future])
|
||
continue
|
||
if result is None:
|
||
continue
|
||
city, entry = result
|
||
last_by_city[city] = entry
|
||
state_dirty = True
|
||
|
||
return state_dirty
|
||
|
||
|
||
def start_high_freq_airport_push_loop(bot: Any, config: Dict[str, Any]) -> Optional[threading.Thread]:
|
||
enabled = _env_bool("TELEGRAM_AIRPORT_PUSH_ENABLED", True)
|
||
chat_ids = get_telegram_chat_ids_from_env()
|
||
if not enabled:
|
||
logger.info("airport high-freq push loop disabled")
|
||
return None
|
||
if not chat_ids:
|
||
logger.warning("airport high-freq push loop skipped: TELEGRAM_CHAT_IDS is not set")
|
||
return None
|
||
|
||
interval_sec = max(30, _env_int("TELEGRAM_AIRPORT_PUSH_INTERVAL_SEC", 60))
|
||
|
||
def _runner() -> None:
|
||
state = _load_airport_state()
|
||
logger.info(
|
||
"airport high-freq push loop started cities={} interval={}s chat_targets={}",
|
||
len(HIGH_FREQ_AIRPORT_CITIES), interval_sec, len(chat_ids),
|
||
)
|
||
while True:
|
||
cycle_started = time.time()
|
||
try:
|
||
state = _load_airport_state()
|
||
if _run_high_freq_airport_cycle(
|
||
bot=bot,
|
||
config=config,
|
||
chat_ids=chat_ids,
|
||
state=state,
|
||
):
|
||
_save_airport_state(state)
|
||
except Exception:
|
||
logger.exception("airport push cycle crashed")
|
||
|
||
elapsed = time.time() - cycle_started
|
||
sleep_sec = max(5, interval_sec - int(elapsed))
|
||
time.sleep(sleep_sec)
|
||
|
||
thread = threading.Thread(
|
||
target=_runner,
|
||
name="airport-high-freq-pusher",
|
||
daemon=True,
|
||
)
|
||
thread.start()
|
||
logger.info("airport high-freq push loop thread started")
|
||
return thread
|