65 lines
2.5 KiB
Python
65 lines
2.5 KiB
Python
import requests
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import bz2
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import json
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from flask import Flask, render_template
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app = Flask(__name__)
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# DWD-Daten URL
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DWD_URL = "https://opendata.dwd.de/weather/weather_reports/synoptic/germany/json/Z__C_EDZW_latest_bda01%2Csynop_bufr_GER_999999_999999__MW_XXX.json.bz2"
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def load_weather_data():
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# Hole die komprimierten Daten von der DWD-URL
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response = requests.get(DWD_URL)
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# Dekomprimieren der bz2-Daten
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decompressed_data = bz2.decompress(response.content)
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# Parsen der JSON-Daten
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data = json.loads(decompressed_data.decode('utf-8'))
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# Extrahieren der relevanten Wetterdaten
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weather_data = []
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for message in data["messages"]:
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# Jede Nachricht kann mehrere Wetterstationen enthalten
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if isinstance(message, list):
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for station_data in message[1:]:
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station_info = {}
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# Überprüfe, ob station_data eine Liste ist
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if isinstance(station_data, list):
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for info in station_data:
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# Stelle sicher, dass info ein Dictionary ist
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if isinstance(info, dict) and "key" in info:
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if info["key"] == "stationNumber":
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station_info["stationNumber"] = info["value"]
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elif info["key"] == "stationOrSiteName":
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station_info["stationName"] = info["value"]
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elif info["key"] == "airTemperature":
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station_info["temperature"] = round(info["value"] - 273.15, 2) # Umwandlung von K in °C
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elif info["key"] == "windSpeed":
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station_info["windSpeed"] = info["value"]
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elif info["key"] == "pressureReducedToMeanSeaLevel":
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station_info["pressure"] = info["value"]
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# Füge nur Daten hinzu, wenn sie vollständig sind
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if "stationNumber" in station_info:
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weather_data.append(station_info)
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# Sortiere nach stationNumber
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weather_data.sort(key=lambda x: x["stationNumber"])
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return weather_data
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# Flask Route für die Hauptseite
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@app.route('/')
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def index():
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# Lade und verarbeite die Wetterdaten
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weather_data = load_weather_data()
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# Render die HTML-Seite mit den Wetterdaten
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return render_template('index.html', weather_data=weather_data)
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=5000)
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