直接暴露出实体便于LLM读取天气预报信息
This commit is contained in:
@@ -1,4 +1,4 @@
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"""Sensor entities for Baidu Weather integration - Weather Alerts."""
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"""Sensor entities for Baidu Weather integration - Weather Alerts & Forecasts."""
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from __future__ import annotations
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@@ -6,11 +6,10 @@ import logging
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from typing import Any
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from homeassistant.components.sensor import (
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SensorDeviceClass,
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SensorEntity,
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)
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from homeassistant.config_entries import ConfigEntry
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from homeassistant.core import HomeAssistant, callback
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from homeassistant.core import HomeAssistant
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from homeassistant.helpers.device_registry import DeviceEntryType, DeviceInfo
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from homeassistant.helpers.entity_platform import AddEntitiesCallback
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from homeassistant.helpers.update_coordinator import CoordinatorEntity
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@@ -20,12 +19,18 @@ from .const import (
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CONF_LOCATION_NAME,
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DOMAIN,
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KEY_ALERTS,
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KEY_INDEXES,
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KEY_FORECASTS,
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KEY_NOW,
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)
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from .coordinator import BaiduWeatherCoordinator
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_LOGGER = logging.getLogger(__name__)
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# Day labels for forecast sensors (index 0 = today)
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_DAY_LABELS_CN = ["今天", "明天", "后天", "大后天", "第五天"]
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_DAY_LABELS_EN = ["Today", "Tomorrow", "Day After Tomorrow", "In 3 Days", "In 4 Days"]
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_DAY_KEYS = ["forecast_today", "forecast_tomorrow", "forecast_day2", "forecast_day3", "forecast_day4"]
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async def async_setup_entry(
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hass: HomeAssistant,
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@@ -41,6 +46,14 @@ async def async_setup_entry(
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BaiduWeatherAqiSensor(coordinator, entry, location_name),
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]
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# Create daily forecast sensors (today + next 4 days = 5 sensors)
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for day_index in range(5):
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entities.append(
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BaiduWeatherDailyForecastSensor(
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coordinator, entry, location_name, day_index
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)
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)
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async_add_entities(entities)
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@@ -187,3 +200,137 @@ class BaiduWeatherAqiSensor(
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attrs["aqi_level"] = "严重污染"
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return attrs
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class BaiduWeatherDailyForecastSensor(
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CoordinatorEntity[BaiduWeatherCoordinator], SensorEntity
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):
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"""Sensor entity for a single day's weather forecast.
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Each instance represents one day (today, tomorrow, day after tomorrow, etc.).
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The sensor state is a human-readable summary like "多云 12~20°C".
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Extra attributes contain detailed forecast fields so that voice assistants
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and LLM integrations can read the forecast directly from entity state.
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"""
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_attr_has_entity_name = True
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_attr_icon = "mdi:weather-partly-cloudy"
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_attr_attribution = ATTRIBUTION
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def __init__(
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self,
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coordinator: BaiduWeatherCoordinator,
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entry: ConfigEntry,
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location_name: str,
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day_index: int,
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) -> None:
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"""Initialize the daily forecast sensor.
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Args:
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day_index: 0 = today, 1 = tomorrow, 2 = day after tomorrow, etc.
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"""
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super().__init__(coordinator)
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self._entry = entry
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self._day_index = day_index
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self._attr_translation_key = _DAY_KEYS[day_index]
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self._attr_unique_id = f"{DOMAIN}_{entry.entry_id}_{_DAY_KEYS[day_index]}"
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self._attr_device_info = DeviceInfo(
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entry_type=DeviceEntryType.SERVICE,
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identifiers={(DOMAIN, entry.entry_id)},
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manufacturer="百度地图",
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name=f"百度天气 - {location_name}",
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configuration_url="https://lbsyun.baidu.com/",
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)
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def _get_forecast_data(self) -> dict[str, Any] | None:
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"""Get the forecast data for this day by index."""
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if self.coordinator.data is None:
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return None
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forecasts = self.coordinator.data.get(KEY_FORECASTS, [])
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if self._day_index < len(forecasts):
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return forecasts[self._day_index]
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return None
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@property
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def native_value(self) -> str | None:
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"""Return a human-readable weather summary for this day.
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Format: "多云 12~20°C" or "晴转多云 8~18°C"
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This makes it easy for voice assistants to read aloud.
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"""
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fc = self._get_forecast_data()
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if fc is None:
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return None
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text_day = fc.get("text_day", "")
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text_night = fc.get("text_night", "")
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high = fc.get("high")
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low = fc.get("low")
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# Build condition text
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if text_day and text_night and text_day != text_night:
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condition_text = f"{text_day}转{text_night}"
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elif text_day:
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condition_text = text_day
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elif text_night:
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condition_text = text_night
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else:
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condition_text = "未知"
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# Build temperature range
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if low is not None and high is not None:
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temp_text = f"{low}~{high}°C"
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elif high is not None:
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temp_text = f"最高{high}°C"
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elif low is not None:
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temp_text = f"最低{low}°C"
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else:
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temp_text = ""
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if temp_text:
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return f"{condition_text} {temp_text}"
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return condition_text
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@property
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def extra_state_attributes(self) -> dict[str, Any]:
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"""Return detailed forecast attributes for this day.
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These attributes are designed to be easily readable by LLM integrations.
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"""
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attrs: dict[str, Any] = {}
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fc = self._get_forecast_data()
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if fc is None:
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return attrs
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# Date
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if fc.get("date"):
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attrs["date"] = fc["date"]
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# Day label (今天/明天/后天...)
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attrs["day_label"] = _DAY_LABELS_CN[self._day_index]
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# Conditions
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if fc.get("text_day"):
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attrs["condition_day"] = fc["text_day"]
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if fc.get("text_night"):
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attrs["condition_night"] = fc["text_night"]
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# Temperatures
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if fc.get("high") is not None:
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attrs["temperature_high"] = fc["high"]
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if fc.get("low") is not None:
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attrs["temperature_low"] = fc["low"]
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# Wind - Day
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if fc.get("wc_day"):
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attrs["wind_class_day"] = fc["wc_day"]
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if fc.get("wd_day"):
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attrs["wind_direction_day"] = fc["wd_day"]
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# Wind - Night
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if fc.get("wc_night"):
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attrs["wind_class_night"] = fc["wc_night"]
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if fc.get("wd_night"):
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attrs["wind_direction_night"] = fc["wd_night"]
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return attrs
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@@ -69,6 +69,21 @@
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},
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"aqi": {
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"name": "空气质量指数"
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},
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"forecast_today": {
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"name": "今天天气预报"
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},
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"forecast_tomorrow": {
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"name": "明天天气预报"
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},
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"forecast_day2": {
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"name": "后天天气预报"
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},
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"forecast_day3": {
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"name": "大后天天气预报"
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},
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"forecast_day4": {
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"name": "第五天天气预报"
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}
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}
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}
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@@ -69,6 +69,21 @@
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},
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"aqi": {
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"name": "Air Quality Index"
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},
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"forecast_today": {
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"name": "Today's Weather Forecast"
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},
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"forecast_tomorrow": {
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"name": "Tomorrow's Weather Forecast"
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},
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"forecast_day2": {
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"name": "Day After Tomorrow Forecast"
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},
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"forecast_day3": {
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"name": "3-Day Forecast"
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},
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"forecast_day4": {
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"name": "4-Day Forecast"
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}
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}
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}
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@@ -69,6 +69,21 @@
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},
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"aqi": {
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"name": "空气质量指数"
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},
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"forecast_today": {
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"name": "今天天气预报"
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},
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"forecast_tomorrow": {
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"name": "明天天气预报"
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},
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"forecast_day2": {
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"name": "后天天气预报"
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},
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"forecast_day3": {
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"name": "大后天天气预报"
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},
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"forecast_day4": {
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"name": "第五天天气预报"
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}
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}
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}
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