app.py

import dash
from dash import dcc, html, Input, Output
import plotly.graph_objs as go
import requests
import os
from datetime import datetime

# Assuming weather_model.py exists; if not, we'll inline it
try:
    from weather_model import get_weather_data
except ImportError:
    def get_weather_data(city, days, api_key):
        try:
            geo_url = f"http://api.openweathermap.org/geo/1.0/direct?q={city}&limit=1&appid={api_key}"
            geo_response = requests.get(geo_url).json()
            if not geo_response:
                return None
            lat, lon = geo_response[0]['lat'], geo_response[0]['lon']

            url = f"http://api.openweathermap.org/data/2.5/onecall?lat={lat}&lon={lon}&exclude=minutely,hourly&units=metric&appid={api_key}"
            response = requests.get(url).json()

            current = {
                'temp': response['current']['temp'],
                'weather': response['current']['weather'][0]['description'],
                'humidity': response['current']['humidity'],
                'wind_speed': response['current']['wind_speed']
            }

            forecast = []
            for i in range(min(days, len(response['daily']))):
                day = response['daily'][i]
                forecast.append({
                    'date': datetime.fromtimestamp(day['dt']).strftime('%Y-%m-%d'),
                    'temp': day['temp']['day'],
                    'precipitation': day.get('rain', 0) + day.get('snow', 0),
                    'wind_speed': day['wind_speed'],
                    'weather': day['weather'][0]['main']
                })

            return {'current': current, 'forecast': forecast}
        except Exception as e:
            print(f"Error fetching weather data: {e}")
            return None

# Initialize Dash app
app = dash.Dash(__name__)
app.title = "Weather Forecast Dashboard"

# Use environment variable for API key
API_KEY = os.getenv("OPENWEATHERMAP_API_KEY", "53d50455f91b6bc3c920959e2954576d")

# Fixed locations
LOCATIONS = ["Hyderabad", "Jogulamba Gadwal", "Bangalore"]
DAYS = 5  # Fixed 5-day forecast

# Layout
app.layout = html.Div([
    html.Div([
        html.H1("Weather Forecast Dashboard", style={'textAlign': 'center', 'color': '#FFFFFF'}),
        html.P("Current weather for Hyderabad, Gadwal, and Karnataka (Bangalore).", 
               style={'textAlign': 'center', 'color': '#D3D9D4'})
    ], style={'backgroundColor': '#212A31', 'padding': '20px'}),

    html.Div([
        html.H2("Weather Overview", style={'color': '#FFFFFF', 'padding': '10px'}),
        html.Div(id='weather-display', style={'display': 'flex', 'flexWrap': 'wrap', 'justifyContent': 'space-around'})
    ], style={'backgroundColor': '#2E3944', 'padding': '20px', 'borderRadius': '10px'}),
], style={'backgroundColor': '#1A2329', 'fontFamily': 'Arial', 'minHeight': '100vh'})

# Callback to update dashboard
@app.callback(
    Output('weather-display', 'children'),
    Input('weather-display', 'id')  # Dummy input to trigger on load
)
def update_dashboard(_):
    weather_components = []
    
    for city in LOCATIONS:
        weather_data = get_weather_data(city, DAYS, API_KEY)
        if not weather_data:
            weather_components.append(
                html.Div(f"Error: Could not fetch data for {city}", style={'color': '#FF5555', 'padding': '10px'})
            )
            continue

        current = weather_data['current']
        forecast = weather_data['forecast']

        # Text Summary
        summary = html.Div([
            html.H3(f"{city}", style={'color': '#FFFFFF'}),
            html.P(f"Current Temp: {current['temp']}°C", style={'color': '#D3D9D4'}),
            html.P(f"Condition: {current['weather']}", style={'color': '#D3D9D4'}),
            html.P(f"Humidity: {current['humidity']}%", style={'color': '#D3D9D4'}),
            html.P(f"Wind Speed: {current['wind_speed']} km/h", style={'color': '#D3D9D4'}),
        ], style={'width': '30%', 'padding': '10px'})

        # Donut Charts
        temp_values = [f['temp'] for f in forecast]
        temp_fig = go.Figure(data=[go.Pie(labels=[f['date'] for f in forecast], values=temp_values, hole=.3)])
        temp_fig.update_layout(title=f"{city} - Temperature (°C)", template='plotly_dark')

        precip_values = [f['precipitation'] for f in forecast]
        precip_fig = go.Figure(data=[go.Pie(labels=[f['date'] for f in forecast], values=precip_values, hole=.3)])
        precip_fig.update_layout(title=f"{city} - Precipitation (mm)", template='plotly_dark')

        wind_values = [f['wind_speed'] for f in forecast]
        wind_fig = go.Figure(data=[go.Pie(labels=[f['date'] for f in forecast], values=wind_values, hole=.3)])
        wind_fig.update_layout(title=f"{city} - Wind Speed (km/h)", template='plotly_dark')

        # Combine into a city section
        city_section = html.Div([
            summary,
            dcc.Graph(figure=temp_fig, style={'width': '20%', 'display': 'inline-block'}),
            dcc.Graph(figure=precip_fig, style={'width': '20%', 'display': 'inline-block'}),
            dcc.Graph(figure=wind_fig, style={'width': '20%', 'display': 'inline-block'}),
        ], style={'margin': '20px', 'backgroundColor': '#2E3944', 'borderRadius': '10px', 'padding': '10px'})

        weather_components.append(city_section)

    return weather_components

# Run server on port 7860 for Hugging Face Spaces
if __name__ == '__main__':
    app.run_server(debug=True, host='0.0.0.0', port=7860)