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The types necessary for weather information such as GeoLocation, DateTime, Temperature,Pressure, WindSpeed, RelativeHumidity, Compass (wind direction) and symbols for the weather have been implemented. There are unit conversions and translations for weather property labels. Signed-off-by: Markus Heiser <markus.heiser@darmarit.de>
151 lines
4.4 KiB
Python
151 lines
4.4 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-or-later
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"""Open Meteo (weather)"""
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from urllib.parse import urlencode
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from datetime import datetime
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from searx.result_types import EngineResults, WeatherAnswer
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from searx import weather
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about = {
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"website": "https://open-meteo.com",
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"wikidata_id": None,
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"official_api_documentation": "https://open-meteo.com/en/docs",
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"use_official_api": True,
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"require_api_key": False,
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"results": "JSON",
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}
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categories = ["weather"]
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geo_url = "https://geocoding-api.open-meteo.com"
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api_url = "https://api.open-meteo.com"
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data_of_interest = (
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"temperature_2m",
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"apparent_temperature",
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"relative_humidity_2m",
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"apparent_temperature",
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"cloud_cover",
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"pressure_msl",
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"wind_speed_10m",
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"wind_direction_10m",
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"weather_code",
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# "visibility",
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# "is_day",
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)
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def request(query, params):
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try:
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location = weather.GeoLocation.by_query(query)
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except ValueError:
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return
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args = {
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"latitude": location.latitude,
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"longitude": location.longitude,
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"timeformat": "unixtime",
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"timezone": "auto", # use timezone of the location
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"format": "json",
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"current": ",".join(data_of_interest),
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"forecast_days": 3,
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"hourly": ",".join(data_of_interest),
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}
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params["url"] = f"{api_url}/v1/forecast?{urlencode(args)}"
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# https://open-meteo.com/en/docs#weather_variable_documentation
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# https://nrkno.github.io/yr-weather-symbols/
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WMO_TO_CONDITION: dict[int, weather.WeatherConditionType] = {
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# 0 Clear sky
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0: "clear sky",
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# 1, 2, 3 Mainly clear, partly cloudy, and overcast
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1: "fair",
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2: "partly cloudy",
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3: "cloudy",
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# 45, 48 Fog and depositing rime fog
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45: "fog",
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48: "fog",
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# 51, 53, 55 Drizzle: Light, moderate, and dense intensity
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51: "light rain",
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53: "light rain",
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55: "light rain",
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# 56, 57 Freezing Drizzle: Light and dense intensity
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56: "light sleet showers",
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57: "light sleet",
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# 61, 63, 65 Rain: Slight, moderate and heavy intensity
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61: "light rain",
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63: "rain",
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65: "heavy rain",
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# 66, 67 Freezing Rain: Light and heavy intensity
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66: "light sleet showers",
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67: "light sleet",
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# 71, 73, 75 Snow fall: Slight, moderate, and heavy intensity
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71: "light sleet",
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73: "sleet",
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75: "heavy sleet",
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# 77 Snow grains
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77: "snow",
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# 80, 81, 82 Rain showers: Slight, moderate, and violent
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80: "light rain showers",
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81: "rain showers",
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82: "heavy rain showers",
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# 85, 86 Snow showers slight and heavy
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85: "snow showers",
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86: "heavy snow showers",
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# 95 Thunderstorm: Slight or moderate
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95: "rain and thunder",
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# 96, 99 Thunderstorm with slight and heavy hail
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96: "light snow and thunder",
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99: "heavy snow and thunder",
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}
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def _weather_data(location: weather.GeoLocation, data: dict):
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return WeatherAnswer.Item(
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location=location,
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temperature=weather.Temperature(unit="°C", value=data["temperature_2m"]),
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condition=WMO_TO_CONDITION[data["weather_code"]],
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feels_like=weather.Temperature(unit="°C", value=data["apparent_temperature"]),
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wind_from=weather.Compass(data["wind_direction_10m"]),
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wind_speed=weather.WindSpeed(data["wind_speed_10m"], unit="km/h"),
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pressure=weather.Pressure(data["pressure_msl"], unit="hPa"),
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humidity=weather.RelativeHumidity(data["relative_humidity_2m"]),
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cloud_cover=data["cloud_cover"],
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)
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def response(resp):
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location = weather.GeoLocation.by_query(resp.search_params["query"])
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res = EngineResults()
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json_data = resp.json()
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weather_answer = WeatherAnswer(
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current=_weather_data(location, json_data["current"]),
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service="Open-meteo",
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# url="https://open-meteo.com/en/docs",
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)
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for index, time in enumerate(json_data["hourly"]["time"]):
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if time < json_data["current"]["time"]:
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# Cut off the hours that are already in the past
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continue
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hourly_data = {}
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for key in data_of_interest:
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hourly_data[key] = json_data["hourly"][key][index]
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forecast_data = _weather_data(location, hourly_data)
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forecast_data.datetime = weather.DateTime(datetime.fromtimestamp(time))
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weather_answer.forecasts.append(forecast_data)
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res.add(weather_answer)
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return res
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