"""Download elevation data for all 27 stations using Open Topo Data API."""
import requests
import pandas as pd
import time
from pathlib import Path

# Load stations
stations = pd.read_csv('datasets/station_list.csv')

print(f"Downloading elevation for {len(stations)} stations...")

elevations = []

for idx, row in stations.iterrows():
    station_code = row['station_code']
    lat = row['lat']
    lon = row['lon']

    # Query Open Topo Data API
    url = f"https://api.opentopodata.org/v1/eudem25m?locations={lat},{lon}"

    try:
        response = requests.get(url, timeout=10)
        if response.status_code == 200:
            data = response.json()
            elevation = data['results'][0]['elevation']
            elevations.append({
                'station_code': station_code,
                'station_name': row['station_name'],
                'latitude': lat,
                'longitude': lon,
                'elevation_m': elevation,
                'data_source': 'EU-DEM 25m (Open Topo Data)'
            })
            print(f"✓ {station_code}: {elevation:.1f} m")
        else:
            print(f"✗ {station_code}: API error {response.status_code}")
            elevations.append({
                'station_code': station_code,
                'station_name': row['station_name'],
                'latitude': lat,
                'longitude': lon,
                'elevation_m': None,
                'data_source': 'Failed'
            })
    except Exception as e:
        print(f"✗ {station_code}: {e}")
        elevations.append({
            'station_code': station_code,
            'station_name': row['station_name'],
            'latitude': lat,
            'longitude': lon,
            'elevation_m': None,
            'data_source': 'Failed'
        })

    # Rate limiting
    time.sleep(3)

# Save
df_elevation = pd.DataFrame(elevations)
output_file = Path('datasets/station_elevations.csv')
df_elevation.to_csv(output_file, index=False)

print(f"\n✓ Saved to: {output_file}")
print(f"✓ Success: {df_elevation['elevation_m'].notna().sum()}/{len(df_elevation)} stations")
print(f"\nElevation range: {df_elevation['elevation_m'].min():.1f} - {df_elevation['elevation_m'].max():.1f} m")