final dashboard adjustments

2025-08-02 06:14:14 +02:00 · 2025-08-02 06:14:14 +02:00 · 770247a175
commit 770247a175
parent 81475b8080
14 changed files with 139 additions and 35 deletions
--- a/PlantDashboard/plant_meteo.py
+++ b/PlantDashboard/plant_meteo.py
@ -0,0 +1,83 @@
+import openmeteo_requests
+
+import pandas as pd
+import requests_cache
+from retry_requests import retry
+import geocoder
+
+
+class HappyMeteo:
+    def __init__(self):
+        # Setup the Open-Meteo API client with cache and retry on error
+        cache_session = requests_cache.CachedSession('.cache', expire_after = 3600)
+        retry_session = retry(cache_session, retries = 5, backoff_factor = 0.2)
+        self.openmeteo = openmeteo_requests.Client(session = retry_session)
+
+    def get_current_location(self):
+        """Get current location using IP geolocation"""
+        try:
+            g = geocoder.ip('me')
+            if g.ok:
+                latitude = g.latlng[0]
+                longitude = g.latlng[1]
+                print(f"Latitude: {latitude}")
+                print(f"Longitude: {longitude}")
+                print(f"Address: {g.address}")
+                return latitude, longitude
+            else:
+                print("Could not determine location")
+                return None, None
+        except Exception as e:
+            print(f"Error getting location: {e}")
+            return None, None
+        
+    def openMeteoCall(self, timeLapse):
+        lat, lon = self.get_current_location()
+        
+        # Make sure all required weather variables are listed here
+        # The order of variables in hourly or daily is important to assign them correctly below
+        url = "https://api.open-meteo.com/v1/forecast"
+        params = {
+            "latitude": lat,
+            "longitude": lon,
+            "daily": ["weather_code", "temperature_2m_mean", "rain_sum", "showers_sum", "precipitation_sum", "daylight_duration", "relative_humidity_2m_mean"],
+            "timezone": "auto",
+            "forecast_days": timeLapse
+        }
+        responses = self.openmeteo.weather_api(url, params=params)
+
+        # Process first location. Add a for-loop for multiple locations or weather models
+        response = responses[0]
+        print(f"Coordinates: {response.Latitude()}°N {response.Longitude()}°E")
+        print(f"Elevation: {response.Elevation()} m asl")
+        print(f"Timezone: {response.Timezone()}{response.TimezoneAbbreviation()}")
+        print(f"Timezone difference to GMT+0: {response.UtcOffsetSeconds()}s")
+
+        # Process daily data. The order of variables needs to be the same as requested.
+        daily = response.Daily()
+        daily_weather_code = daily.Variables(0).ValuesAsNumpy()
+        daily_temperature_2m_mean = daily.Variables(1).ValuesAsNumpy()
+        daily_rain_sum = daily.Variables(2).ValuesAsNumpy()
+        daily_showers_sum = daily.Variables(3).ValuesAsNumpy()
+        daily_precipitation_sum = daily.Variables(4).ValuesAsNumpy()
+        daily_daylight_duration = daily.Variables(5).ValuesAsNumpy()
+        daily_relative_humidity_2m_mean = daily.Variables(6).ValuesAsNumpy()
+
+        daily_data = {"date": pd.date_range(
+            start = pd.to_datetime(daily.Time(), unit = "s", utc = True),
+            end = pd.to_datetime(daily.TimeEnd(), unit = "s", utc = True),
+            freq = pd.Timedelta(seconds = daily.Interval()),
+            inclusive = "left"
+        )}
+
+        daily_data["weather_code"] = daily_weather_code
+        daily_data["temperature_2m_mean"] = daily_temperature_2m_mean
+        daily_data["rain_sum"] = daily_rain_sum
+        daily_data["showers_sum"] = daily_showers_sum
+        daily_data["precipitation_sum"] = daily_precipitation_sum
+        daily_data["daylight_duration"] = daily_daylight_duration
+        daily_data["relative_humidity_2m_mean"] = daily_relative_humidity_2m_mean
+
+        daily_dataframe = pd.DataFrame(data = daily_data)
+        print("\nDaily data\n", daily_dataframe)
+