weather_app.py

import streamlit as st
import requests
from datetime import datetime, timedelta
import pandas as pd
from dotenv import load_dotenv
import os
from PIL import Image
from io import BytesIO

# Load environment variables
load_dotenv()
API_KEY = os.getenv('WEATHER_API_KEY')
BASE_URL = "http://api.weatherapi.com/v1"

# Configure the app
st.set_page_config(
    page_title="Weather Dashboard",
    page_icon="🌤️",
    layout="wide"
)

# Custom CSS
st.markdown("""
    <style>
    .weather-icon {
        width: 64px;
        height: 64px;
        margin: 10px auto;
    }
    .stMetric {
        background-color: rgba(255, 255, 255, 0.1);
        padding: 10px;
        border-radius: 5px;
    }
    .main-header {
        text-align: center;
        color: #1E88E5;
        padding: 20px;
    }
    </style>
    """, unsafe_allow_html=True)

def load_weather_icon(icon_url):
    """Load and display weather icon from URL"""
    try:
        response = requests.get(icon_url)
        img = Image.open(BytesIO(response.content))
        return img
    except Exception as e:
        st.warning(f"Could not load weather icon: {e}")
        return None

def get_weather_data(location, is_historical=False, date=None):
    """Fetch weather data from the API"""
    try:
        if is_historical:
            endpoint = f"{BASE_URL}/history.json"
            params = {
                'key': API_KEY,
                'q': location,
                'dt': date.strftime('%Y-%m-%d')
            }
        else:
            endpoint = f"{BASE_URL}/forecast.json"
            params = {
                'key': API_KEY,
                'q': location,
                'days': 1,
                'aqi': 'no'
            }

        response = requests.get(endpoint, params=params)
        response.raise_for_status()
        return response.json()

    except requests.exceptions.RequestException as e:
        st.error(f"Error fetching weather data: {e}")
        return None

def display_weather_data(weather_data, selected_datetime, container):
    """Display weather data in the specified container"""
    if not weather_data:
        container.error("No weather data available")
        return

    container.subheader(f"Date: {selected_datetime.strftime('%Y-%m-%d %H:%M')}")
    
    # Handle both historical and forecast data structure
    if 'current' in weather_data:
        current_data = weather_data['current']
    else:
        historical_hour = min(
            weather_data['forecast']['forecastday'][0]['hour'],
            key=lambda x: abs(datetime.strptime(x['time'], '%Y-%m-%d %H:%M').time().hour - 
                           selected_datetime.time().hour)
        )
        current_data = historical_hour

    # Display current weather icon and condition
    icon_url = f"https:{current_data['condition']['icon']}"
    weather_icon = load_weather_icon(icon_url)
    if weather_icon:
        col1, col2, col3 = container.columns([1, 2, 1])
        with col2:
            st.image(weather_icon, caption=current_data['condition']['text'], use_container_width=True)
    
    # Create metrics in a grid
    metric_col1, metric_col2 = container.columns(2)
    
    with metric_col1:
        st.metric("Temperature", f"{current_data['temp_c']}°C",
                 f"Feels like {current_data['feelslike_c']}°C")
        st.metric("Wind", f"{current_data['wind_kph']} km/h",
                 f"Direction: {current_data['wind_dir']}")
    
    with metric_col2:
        st.metric("Humidity", f"{current_data['humidity']}%")
        st.metric("Pressure", f"{current_data['pressure_mb']} mb")
    
    # Display hourly forecast
    container.subheader("Hourly Forecast")
    hourly_data = weather_data['forecast']['forecastday'][0]['hour']
    
    # Create a more visual hourly forecast
    hours_to_show = 6
    current_hour = selected_datetime.hour
    relevant_hours = [h for h in hourly_data if datetime.strptime(h['time'], '%Y-%m-%d %H:%M').hour >= current_hour][:hours_to_show]
    
    hour_cols = container.columns(min(hours_to_show, len(relevant_hours)))
    
    for hour, col in zip(relevant_hours, hour_cols):
        with col:
            hour_time = datetime.strptime(hour['time'], '%Y-%m-%d %H:%M').strftime('%I %p')
            st.markdown(f"**{hour_time}**")
            
            hour_icon_url = f"https:{hour['condition']['icon']}"
            hour_icon = load_weather_icon(hour_icon_url)
            if hour_icon:
                st.image(hour_icon, use_container_width=True)
            
            st.markdown(f"🌡️ {hour['temp_c']}°C")
            st.markdown(f"💧 {hour['chance_of_rain']}%")
            st.markdown(f"💨 {hour['wind_kph']} km/h")
    
    # Display detailed hourly data
    with container.expander("Detailed Hourly Forecast"):
        hourly_df = pd.DataFrame([
            {
                'Time': datetime.strptime(hour['time'], '%Y-%m-%d %H:%M').strftime('%I:%M %p'),
                'Temperature': f"{hour['temp_c']}°C",
                'Condition': hour['condition']['text'],
                'Chance of Rain': f"{hour['chance_of_rain']}%",
                'Wind Speed': f"{hour['wind_kph']} km/h",
                'Humidity': f"{hour['humidity']}%"
            }
            for hour in hourly_data
        ])
        
        st.dataframe(
            hourly_df,
            hide_index=True,
            use_container_width=True
        )

def main():
    """Main function to run the Streamlit app"""
    st.markdown("<h1 class='main-header'>🌤️ Weather Forecast Dashboard</h1>", unsafe_allow_html=True)

    # Sidebar inputs
    with st.sidebar:
        st.header("Settings")
        location = st.text_input("Enter Location", "London")
        
        # Date selection
        view_type = st.radio("Select View", ["Current & Forecast", "Historical"])
        
        if view_type == "Historical":
            max_date = datetime.now() - timedelta(days=1)
            min_date = max_date - timedelta(days=7)
            selected_date = st.date_input(
                "Select Date",
                value=max_date,
                min_value=min_date,
                max_value=max_date
            )
            selected_time = st.time_input("Select Time", datetime.now().time())
            selected_datetime = datetime.combine(selected_date, selected_time)
            is_historical = True
        else:
            selected_datetime = datetime.now()
            is_historical = False

        if st.button("Get Weather Data"):
            with st.spinner("Fetching weather data..."):
                weather_data = get_weather_data(
                    location,
                    is_historical=is_historical,
                    date=selected_datetime if is_historical else None
                )
                
                if weather_data:
                    st.session_state.weather_data = weather_data
                    st.session_state.selected_datetime = selected_datetime

    # Main content area
    if 'weather_data' in st.session_state:
        display_weather_data(
            st.session_state.weather_data,
            st.session_state.selected_datetime,
            st
        )
    else:
        st.info("Enter a location and click 'Get Weather Data' to start")

if __name__ == "__main__":
    main()