Files
PolyWeather/src/utils/telegram_push.py
T
2569718930@qq.com fe9bf61ad6 接入香港天文台 HKO + 流浮山 LFS 1分钟实时温度
HKO 公共天气 API 免费无注册,提供 1 分钟温度 CSV。
两个站点加入高频推送,与首尔/釜山同级。

Station: HK Observatory (HKO) 27.0°C, Lau Fau Shan (LFS) 25.9°C
Interval: 60s

Tested: pytest 176 passed, HKO API 实测通过
2026-05-13 00:33:56 +08:00

960 lines
34 KiB
Python
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import hashlib
import json
import os
import re
import threading
import time
from datetime import datetime, timezone
from typing import Any, Dict, List, Optional, Tuple
from loguru import logger
from src.database.runtime_state import (
STATE_STORAGE_SQLITE,
TelegramAlertStateRepository,
get_state_storage_mode,
)
from src.data_collection.city_registry import CITY_REGISTRY
from src.utils.telegram_chat_ids import get_telegram_chat_ids_from_env
SEVERITY_RANK = {
"none": 0,
"low": 1,
"medium": 2,
"high": 3,
}
_telegram_state_repo = TelegramAlertStateRepository()
def _env_bool(name: str, default: bool) -> bool:
raw = os.getenv(name)
if raw is None:
return default
return raw.strip().lower() in {"1", "true", "yes", "on"}
def _env_int(name: str, default: int) -> int:
raw = os.getenv(name)
if raw is None:
return default
try:
return int(raw)
except Exception:
return default
def _env_float(name: str, default: float) -> float:
raw = os.getenv(name)
if raw is None:
return default
try:
return float(raw)
except Exception:
return default
def _norm_prob(v: Any) -> Optional[float]:
if v is None:
return None
try:
n = float(v)
except Exception:
return None
if n > 1.0:
n = n / 100.0
return max(0.0, min(1.0, n))
def _fmt_cents(value: Any) -> Optional[str]:
numeric = _norm_prob(value)
if numeric is None:
return None
cents = numeric * 100.0
rounded = round(cents, 1)
text = f"{rounded:.1f}".rstrip("0").rstrip(".")
return f"{text}c"
def _safe_float(v: Any) -> Optional[float]:
if v is None:
return None
try:
return float(v)
except Exception:
return None
def _bucket_value(row: Dict[str, Any]) -> Optional[float]:
if not isinstance(row, dict):
return None
for key in ("value", "temp"):
n = _safe_float(row.get(key))
if n is not None:
return n
label = str(row.get("label") or "").strip()
m = re.search(r"(-?\d+(?:\.\d+)?)", label)
if not m:
return None
return _safe_float(m.group(1))
def _bucket_bounds(row: Dict[str, Any]) -> Optional[Tuple[Optional[float], Optional[float]]]:
value = _bucket_value(row)
if value is None:
return None
label = str(row.get("label") or "").strip().lower()
is_upper_tail = any(key in label for key in ("+", "or higher", "or above", "and above"))
is_lower_tail = any(key in label for key in ("<=", "or lower", "or below", "and below"))
if is_upper_tail and not is_lower_tail:
return value, None
if is_lower_tail and not is_upper_tail:
return None, value
return value, value
def _observed_settlement_floor(alert_payload: Dict[str, Any]) -> Optional[float]:
evidence = alert_payload.get("evidence") or {}
if not isinstance(evidence, dict):
evidence = {}
inputs = evidence.get("inputs") or {}
if not isinstance(inputs, dict):
inputs = {}
suppression = alert_payload.get("suppression") or {}
if not isinstance(suppression, dict):
suppression = {}
rules = alert_payload.get("rules") or {}
if not isinstance(rules, dict):
rules = {}
breakthrough = rules.get("forecast_breakthrough") or {}
if not isinstance(breakthrough, dict):
breakthrough = {}
floor_candidates: List[float] = []
for raw in (
inputs.get("wu_settle"),
suppression.get("max_so_far"),
inputs.get("current_temp"),
suppression.get("current_temp"),
breakthrough.get("current_temp"),
):
n = _safe_float(raw)
if n is not None:
floor_candidates.append(n)
if not floor_candidates:
return None
return max(floor_candidates)
def _optional_bool(value: Any) -> Optional[bool]:
if value is None:
return None
if isinstance(value, bool):
return value
if isinstance(value, (int, float)):
return bool(value)
if isinstance(value, str):
normalized = value.strip().lower()
if normalized in {"1", "true", "yes", "on"}:
return True
if normalized in {"0", "false", "no", "off"}:
return False
return bool(value)
def _parse_iso_datetime_utc(value: Any) -> Optional[datetime]:
if not value:
return None
text = str(value).strip()
if not text:
return None
if "T" not in text:
return None
try:
dt = datetime.fromisoformat(text.replace("Z", "+00:00"))
except Exception:
return None
if dt.tzinfo is None:
return dt.replace(tzinfo=timezone.utc)
return dt.astimezone(timezone.utc)
def _parse_city_list(raw: Optional[str]) -> List[str]:
if not raw:
return list(CITY_REGISTRY.keys())
out: List[str] = []
for part in raw.split(","):
city = part.strip().lower()
if city and city in CITY_REGISTRY:
out.append(city)
return out or list(CITY_REGISTRY.keys())
def _state_file() -> str:
root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
return os.path.join(root, "data", "telegram_alert_state.json")
def _load_state(path: str) -> Dict[str, Any]:
mode = get_state_storage_mode()
if mode == STATE_STORAGE_SQLITE:
try:
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": {}}
try:
with open(path, "r", encoding="utf-8") as fh:
data = json.load(fh)
if isinstance(data, dict):
data.setdefault("last_by_city", {})
data.setdefault("by_signature", {})
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()
def build_trade_alert_for_city(
city: str,
config: Dict[str, Any],
force_refresh: bool = False,
target_date: Optional[str] = None,
) -> Dict[str, Any]:
from web.app import _analyze, _build_city_detail_payload
from src.analysis.market_alert_engine import build_trading_alerts
city_weather = _analyze(city, force_refresh=force_refresh)
try:
aggregate_detail = _build_city_detail_payload(
city_weather,
target_date=target_date,
)
market_scan = aggregate_detail.get("market_scan")
if isinstance(market_scan, dict):
city_weather = {**city_weather, "market_scan": market_scan}
except Exception as exc:
logger.debug(f"market scan attach skipped city={city}: {exc}")
resolved_target_date = target_date or city_weather.get("local_date")
if resolved_target_date:
datetime.strptime(resolved_target_date, "%Y-%m-%d")
map_url = os.getenv("POLYWEATHER_MAP_URL") or "https://polyweather-pro.vercel.app/"
alert_payload = build_trading_alerts(
city_weather=city_weather,
map_url=map_url,
)
alert_payload["target_date"] = resolved_target_date
return alert_payload
def _maybe_send_alert(
bot: Any,
chat_ids: List[str],
city: str,
alert_payload: Dict[str, Any],
state: Dict[str, Any],
cooldown_sec: int,
min_severity: str,
min_trigger_count: int,
) -> bool:
now_ts = int(time.time())
last_by_city = state.setdefault("last_by_city", {})
last_city = last_by_city.get(city) or {}
is_active = _severity_ok(alert_payload, min_severity, min_trigger_count)
if not _market_price_cap_ok(alert_payload):
is_active = False
message = ((alert_payload.get("telegram") or {}).get("zh") or "").strip()
if not is_active or not message:
if last_city.get("active"):
last_by_city[city] = {
**last_city,
"active": False,
"cleared_ts": now_ts,
}
logger.info(f"market monitor disarmed city={city}")
return True
return False
if not chat_ids:
return False
signature = _alert_signature(alert_payload)
trigger_key = _trigger_type_key(alert_payload)
last_city_sig = last_city.get("signature")
last_city_key = str(last_city.get("trigger_key") or "")
last_city_ts = int(last_city.get("ts") or 0)
last_sig_ts = int((state.get("by_signature") or {}).get(signature) or 0)
last_city_active = bool(last_city.get("active"))
if last_city_active and last_city_key == trigger_key and last_city_sig == signature:
return False
if last_city_ts and now_ts - last_city_ts < cooldown_sec:
return False
if last_sig_ts and now_ts - last_sig_ts < cooldown_sec:
return False
sent_count = 0
for chat_id in chat_ids:
try:
bot.send_message(chat_id, message)
sent_count += 1
except Exception as exc:
logger.warning("market monitor push failed city={} chat_id={} error={}", city, chat_id, exc)
if sent_count <= 0:
return False
last_by_city[city] = {
"signature": signature,
"trigger_key": trigger_key,
"severity": alert_payload.get("severity"),
"ts": now_ts,
"active": True,
"evidence": alert_payload.get("evidence"),
}
state.setdefault("by_signature", {})[signature] = now_ts
logger.info(
f"market monitor pushed city={city} severity={alert_payload.get('severity')} "
f"trigger_count={alert_payload.get('trigger_count')} trigger_key={trigger_key} "
f"evidence={_evidence_brief(alert_payload)} chat_targets={sent_count}"
)
return True
def _run_market_monitor_cycle(
bot: Any,
config: Dict[str, Any],
*,
chat_ids: List[str],
cities: List[str],
state: Dict[str, Any],
alert_cooldown_sec: int,
min_severity: str,
min_trigger_count: int,
sleep_between_cities_sec: float = 1.0,
) -> bool:
state_dirty = False
for city in cities:
try:
alert_payload = build_trade_alert_for_city(city, config)
if _maybe_send_alert(
bot=bot,
chat_ids=chat_ids,
city=city,
alert_payload=alert_payload,
state=state,
cooldown_sec=alert_cooldown_sec,
min_severity=min_severity,
min_trigger_count=min_trigger_count,
):
state_dirty = True
except Exception:
logger.exception(f"telegram market monitor loop failed for city={city}")
if sleep_between_cities_sec > 0:
time.sleep(sleep_between_cities_sec)
return state_dirty
def start_trade_alert_push_loop(bot: Any, config: Dict[str, Any]) -> Optional[threading.Thread]:
enabled = _env_bool("TELEGRAM_ALERT_PUSH_ENABLED", True)
chat_ids = get_telegram_chat_ids_from_env()
if not enabled:
logger.info("telegram market monitor loop disabled")
return None
if not chat_ids:
logger.warning("telegram market monitor loop skipped: TELEGRAM_CHAT_IDS is not set")
return None
interval_sec = max(60, _env_int("TELEGRAM_ALERT_PUSH_INTERVAL_SEC", 1800))
cities = _parse_city_list(os.getenv("TELEGRAM_ALERT_CITIES"))
state_path = _state_file()
alert_cooldown_sec = max(60, _env_int("TELEGRAM_ALERT_PUSH_COOLDOWN_SEC", 21600))
min_trigger_count = max(1, _env_int("TELEGRAM_ALERT_MIN_TRIGGER_COUNT", 3))
min_severity = str(os.getenv("TELEGRAM_ALERT_MIN_SEVERITY") or "high").strip().lower()
if min_severity not in SEVERITY_RANK:
min_severity = "high"
def _runner() -> None:
try:
_save_state(state_path, _load_state(state_path))
except Exception:
logger.exception(f"failed to initialize market monitor state path={state_path}")
logger.info(
f"telegram market monitor loop started mode=critical-alerts "
f"cities={len(cities)} interval={interval_sec}s chat_targets={len(chat_ids)} "
f"alert_cooldown={alert_cooldown_sec}s "
f"min_severity={min_severity} min_trigger_count={min_trigger_count} "
f"state_path={state_path}"
)
while True:
cycle_started = time.time()
state = _load_state(state_path)
_cleanup_state(state, int(cycle_started))
if _run_market_monitor_cycle(
bot=bot,
config=config,
chat_ids=chat_ids,
cities=cities,
state=state,
alert_cooldown_sec=alert_cooldown_sec,
min_severity=min_severity,
min_trigger_count=min_trigger_count,
):
_save_state(state_path, state)
elapsed = time.time() - cycle_started
sleep_sec = max(5, interval_sec - int(elapsed))
time.sleep(sleep_sec)
thread = threading.Thread(
target=_runner,
name="telegram-market-monitor-pusher",
daemon=True,
)
thread.start()
return thread
# ── high-freq airport push loop ──
HIGH_FREQ_AIRPORT_CITIES = {"seoul", "busan", "tokyo", "ankara", "helsinki", "amsterdam", "istanbul", "paris", "hong kong", "lau fau shan"}
HIGH_FREQ_AIRPORT_ICAO = {"seoul": "RKSI", "busan": "RKPK", "tokyo": "RJTT", "ankara": "17128", "helsinki": "EFHK", "amsterdam": "EHAM", "istanbul": "17058", "paris": "LFPB", "hong kong": "HKO", "lau fau shan": "LFS"}
_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)
def _fetch_arome_temp() -> Optional[float]:
"""Fetch latest AROME France HD 15-min temperature for LFPB from Open-Meteo."""
try:
import requests
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 = requests.get(url, timeout=8)
data = resp.json()
temps = (data.get("minutely_15") or {}).get("temperature_2m") or []
return float(temps[-1]) if temps else None
except Exception:
return None
def _build_airport_status_message(
city: str,
city_weather: Dict[str, Any],
deb_pred: Optional[float],
local_time: str = "",
) -> str:
_AIRPORT_EN = {"seoul": "Incheon", "busan": "Gimhae", "tokyo": "Haneda",
"ankara": "Esenboğa", "helsinki": "Vantaa", "amsterdam": "Schiphol",
"istanbul": "Airport", "paris": "Le Bourget",
"hong kong": "Observatory", "lau fau shan": "Lau Fau Shan"}
en_name = city.title()
ap_name = _AIRPORT_EN.get(city, "")
time_suffix = f" {local_time}" if local_time else ""
header = f"{en_name} / {ap_name}{time_suffix}" if ap_name else f"{en_name}{time_suffix}"
amos = city_weather.get("amos") or {}
runway_data = (amos.get("runway_obs") or {}) if amos else {}
runway_pairs = runway_data.get("runway_pairs") or []
runway_temps = runway_data.get("temperatures") 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_row = mgm_nearby[0] if mgm_nearby else {}
station_temp = airport_row.get("temp") if airport_row else None
current = city_weather.get("current") or {}
if station_temp is None:
station_temp = current.get("temp")
lines = [header, ""]
runway_shown = False
if runway_pairs and runway_temps and len(runway_pairs) == len(runway_temps):
for (r1, r2), (t, _d) in zip(runway_pairs, runway_temps):
if t is not None:
lines.append(f"{r1}/{r2} {t:.1f}°C")
runway_shown = True
if not runway_shown and station_temp is not None:
label = "AROME预报" if city == "paris" else "当前实测"
lines.append(f"{label}{station_temp:.1f}°C")
if deb_pred is not None:
lines.append(f"今日DEB预报最高:{deb_pred:.1f}°C")
max_so_far, max_temp_time = _get_airport_daily_high(city_weather)
if max_so_far is not None:
time_str = f"{max_temp_time}" if max_temp_time else ""
lines.append(f"今日实测最高:{max_so_far:.1f}°C{time_str}")
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 matching native data refresh rate (seconds)
_AIRPORT_PUSH_INTERVAL = {
"seoul": 60, # AMOS 1-min
"busan": 60, # AMOS 1-min
"tokyo": 600, # JMA 10-min
"ankara": 600, # MGM ~10-min
"helsinki": 600, # FMI 10-min
"amsterdam": 600, # KNMI 10-min
"istanbul": 600, # MGM ~10-min
"paris": 900, # AROME HD 15-min model
"hong kong": 60, # HKO 1-min
"lau fau shan": 60, # HKO 1-min
}
_DEB_PROXIMITY_THRESHOLD_C = 3.0
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", {})
for city in sorted(HIGH_FREQ_AIRPORT_CITIES):
try:
last_city = last_by_city.get(city) or {}
last_city_ts = int(last_city.get("ts") or 0)
city_interval = _AIRPORT_PUSH_INTERVAL.get(city, 600)
if now_ts - last_city_ts < city_interval:
continue
city_weather: Dict[str, Any] = {}
deb_pred: Optional[float] = None
try:
from web.app import _analyze
city_weather = _analyze(city)
deb_raw = (city_weather.get("deb") or {}).get("prediction")
if deb_raw is not None:
deb_pred = float(deb_raw)
except Exception:
pass
current = city_weather.get("current") or {}
current_temp = current.get("temp")
# Paris: use AROME 15-min model temp instead of METAR
if city == "paris":
arome_temp = _fetch_arome_temp()
if arome_temp is not None:
current_temp = arome_temp
city_weather.setdefault("current", {})["temp"] = arome_temp
if current_temp is None or deb_pred is None:
continue
# Push only when approaching DEB predicted high
proximity = deb_pred - current_temp
in_window = proximity <= _DEB_PROXIMITY_THRESHOLD_C
# Stop if past peak (skip for Paris: no obs_log for AROME model data)
if in_window and city != "paris":
try:
from src.database.db_manager import DBManager
icao = HIGH_FREQ_AIRPORT_ICAO.get(city, "")
db = DBManager()
obs = db.get_airport_obs_recent(icao, minutes=60)
if obs:
temps = [r.get("temp_c") for r in obs if r.get("temp_c") is not None]
if len(temps) >= 6:
peak = max(temps)
peak_idx = temps.index(peak)
if peak_idx < len(temps) - 2:
post = temps[peak_idx:]
if all(post[i] <= post[i - 1] + 0.1 for i in range(1, len(post))):
if current_temp < peak - 0.5:
in_window = False
except Exception:
pass
if not in_window:
if last_city.get("active"):
last_by_city[city] = {"ts": now_ts, "active": False}
state_dirty = True
continue
local_time = city_weather.get("local_time") or ""
message = _build_airport_status_message(city, city_weather, deb_pred, local_time)
sent = False
for chat_id in chat_ids:
try:
bot.send_message(chat_id, message)
sent = True
except Exception as exc:
logger.warning("airport push failed city={} chat_id={}: {}", city, chat_id, exc)
if sent:
last_by_city[city] = {"ts": now_ts, "active": True}
state_dirty = True
logger.info("airport status pushed city={} temp={} proximity={:.1f}", city, current_temp, proximity)
except Exception:
logger.exception("airport cycle failed for city={}", city)
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()
state = _load_airport_state()
if _run_high_freq_airport_cycle(
bot=bot,
config=config,
chat_ids=chat_ids,
state=state,
):
_save_airport_state(state)
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