Merge pull request #84 from roshnaeem/open-meteo

Accessing open-meteo dataset from AWS s3 using docker

.env

@@ -0,0 +1,5 @@
+OPEN_METEO_MODELS=ncep_gfs013
+OPEN_METEO_VARIABLES=temperature_2m,precipitation,cloud_cover
+OPEN_METEO_MAX_AGE_DAYS=3
+OPEN_METEO_REPEAT_INTERVAL=5
+OPEN_METEO_CONCURRENT=4

.gitignore

@@ -1,4 +1,3 @@
-.env
 scripts/datapipes/test.nc
 scripts/datapipes/UK_PV_metadata.csv
 scripts/datapipes/nwp_data

docker-compose.yaml

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+version: '3.8'
+
+x-shared_environment: &shared_environment
+  LOG_LEVEL: ${LOG_LEVEL:-info}
+
+services:
+  open-meteo-api:
+    image: ghcr.io/open-meteo/open-meteo
+    container_name: open-meteo-api
+    ports:
+      - "8080:8080"
+    command: serve
+    volumes:
+      - data:/app/data
+    restart: always
+    environment:
+      <<: *shared_environment
+  open-meteo-sync:
+    image: ghcr.io/open-meteo/open-meteo
+    container_name: open-meteo-sync
+    command: sync ${OPEN_METEO_MODELS} ${OPEN_METEO_VARIABLES} --past-days ${OPEN_METEO_MAX_AGE_DAYS} --repeat-interval ${OPEN_METEO_REPEAT_INTERVAL} --concurrent ${OPEN_METEO_CONCURRENT}
+    volumes:
+      - data:/app/data
+    restart: always
+    environment:
+      <<: *shared_environment
+
+volumes:
+  data:

quartz_solar_forecast/open-meteo/open_meteo.py

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+import requests
+import pandas as pd
+from datetime import datetime, timedelta
+import xarray as xr
+
+from quartz_solar_forecast.pydantic_models import PVSite
+
+def fetch_open_meteo_temperature(site: PVSite, ts: datetime):
+    """
+    Fetch hourly temperature data from the local Open-Meteo API for a specific site.
+
+    :param site: The PV site object containing latitude and longitude.
+    :param ts: Timestamp for when the forecast is desired.
+    :return: A Dataset with the requested weather data.
+    """
+
+    variables = ['temperature_2m', 'precipitation', 'cloud_cover']
+
+    # Format the timestamp to a suitable string format for the API
+    start_date = ts.strftime('%Y-%m-%d')
+    end_date = (ts + timedelta(days=2)).strftime('%Y-%m-%d')
+
+    # Construct the API URL
+    api_url = (
+        f"http://127.0.0.1:8080/v1/forecast?latitude={site.latitude}&longitude={site.longitude}"
+        f"&hourly={','.join(variables)}"
+        f"&start_date={start_date}&end_date={end_date}"
+    )
+
+    try:
+        response = requests.get(api_url)
+        response.raise_for_status()
+        data = response.json()
+
+        df = pd.DataFrame({
+            'time': pd.to_datetime(data['hourly']['time']),
+            'temperature_2m': data['hourly'].get('temperature_2m', [None] * len(data['hourly']['time'])),
+            'precipitation': data['hourly'].get('precipitation', [None] * len(data['hourly']['time'])),
+            'cloud_cover': data['hourly'].get('cloud_cover', [None] * len(data['hourly']['time']))
+        }).set_index('time')
+
+        # Convert the DataFrame to an xarray Dataset
+        data_xr = xr.Dataset.from_dataframe(df)
+
+        return df
+
+    except requests.RequestException as e:
+        print(f"Request failed: {e}")
+        return None
+
+
+# Example usage
+site = PVSite(latitude=47.1, longitude=8.4, capacity_kwp=1)
+ts = datetime.now()
+data = fetch_open_meteo_temperature(site, ts)
+print(data)