Finalize City Pulse animation with tested improvements (Closes #31)

GSSoC_2k25.code-workspace

@@ -0,0 +1,10 @@
+{
+	"folders": [
+		{
+			"path": ".."
+		}
+	],
+	"settings": {
+		"git.ignoreLimitWarning": true
+	}
+}

app.py

@@ -1,6 +1,7 @@
 import streamlit as st
 import pandas as pd
 import datetime
+import asyncio
 
 # Import your existing utility functions
 from utils.weather import get_current_weather, get_monthly_weather
@@ -9,10 +10,39 @@
 from utils.air_quality import get_air_quality
 from utils.crime import get_crime_news
 from utils.chatbot import search_google
-
+# Import the CityPulseAnimations class
+from utils.city_pulse_animation import CityPulseAnimations
+import random
 
 st.set_page_config(page_title="City Pulse", layout="wide")
 
+@st.cache_data(ttl=300)  # Cache for 5 minutes
+def get_city_pulse_data(city, lat, lon):
+    """Get city pulse data synchronously for Streamlit"""
+    try:
+        # Set up API keys (replace with your actual keys)
+        api_keys = {
+            'openweather': 'YOUR_OPENWEATHER_API_KEY_HERE',  # Get from https://openweathermap.org/api
+            # 'weatherapi': 'YOUR_WEATHERAPI_KEY_HERE',  # Optional
+            # 'aqicn': 'YOUR_AQICN_API_KEY_HERE'  # Optional
+        }
+
+        # Run the async function
+        async def fetch_data():
+            async with CityPulseAnimations(api_keys) as city_pulse:
+                return await city_pulse.update_city_data(city, lat, lon)
+
+        # Execute the async function
+        loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(loop)
+        city_data = loop.run_until_complete(fetch_data())
+        loop.close()
+
+        return city_data
+    except Exception as e:
+        st.error(f"Error fetching city pulse data: {e}")
+        return None
+
 st.title("City Pulse 🌆")
 city = st.selectbox("Select a City", list(CITY_COORDS.keys()))
 
@@ -23,11 +53,95 @@
     # --- Initialize chat history in session state ---
     if "messages" not in st.session_state:
         st.session_state.messages = []
+
+    # --- City Pulse Section ---
+    st.header(f"🎯 City Pulse for {city}")
+
+    city_pulse_data = get_city_pulse_data(city, lat, lon)
+
+    if city_pulse_data:
+        pulse_params = city_pulse_data.get('pulse_params', {})
+
+        col1, col2, col3, col4 = st.columns(4)
+
+        with col1:
+            st.metric("Pulse Color", pulse_params.get('color', '#00ff7f'))
+
+        with col2:
+            st.metric("Pulse Speed", f"{pulse_params.get('speed', 1.0):.1f}x")
+
+        with col3:
+            st.metric("Pulse Pattern", pulse_params.get('pattern', 'normal').title())
+
+        with col4:
+            st.metric("Pulse Intensity", f"{pulse_params.get('intensity', 0.7):.1f}")
+
+        # Show pulse visualization
+        pulse_color = pulse_params.get('color', '#00ff7f')
+        pulse_speed = pulse_params.get('speed', 1.0)
+        pulse_intensity = pulse_params.get('intensity', 0.7)
+        pulse_pattern = pulse_params.get('pattern', 'normal')
+
+        st.markdown(f"""
+        <div class="pulse-container" style="text-align: center; margin: 20px 0;">
+            <div class="city-pulse" style="
+                width: 120px; 
+                height: 120px; 
+                background: radial-gradient(circle, {pulse_color} 0%, rgba(0,255,127,0.3) 70%, transparent 100%);
+                border-radius: 50%; 
+                margin: 20px auto;
+                animation: cityPulse {2.0/pulse_speed:.1f}s ease-in-out infinite;
+                box-shadow: 0 0 30px {pulse_color};
+                position: relative;
+                display: flex;
+                align-items: center;
+                justify-content: center;
+                font-size: 2rem;
+            ">
+                ❤️
+            </div>
+            <p style="margin-top: 10px; font-style: italic; color: #666;">
+                Pattern: {pulse_pattern.title()} | Reflecting real-time city conditions
+            </p>
+        </div>
+
+        <style>
+        @keyframes cityPulse {{
+            0%, 100% {{ 
+                transform: scale(1);
+                box-shadow: 0 0 20px {pulse_color};
+            }}
+            50% {{ 
+                transform: scale({1 + pulse_intensity * 0.3});
+                box-shadow: 0 0 40px {pulse_color};
+            }}
+        }}
+        </style>
+        """, unsafe_allow_html=True)
+
+        # Show detailed pulse information
+        with st.expander("🔍 Pulse Details"):
+            weather_data = city_pulse_data.get('weather', {})
+            current_weather = weather_data.get('current', {})
+            air_quality = weather_data.get('air_quality', {})
+            crime_data = city_pulse_data.get('crime', {})
+            tourism_data = city_pulse_data.get('tourism', {})
+
+            st.write("**Pulse Factors:**")
+            st.write(f"🌡️ Temperature: {current_weather.get('temperature', 'N/A')}°C")
+            st.write(f"🏭 Air Quality Index: {air_quality.get('aqi', 'N/A')}")
+            st.write(f"🚨 Crime Risk Level: {crime_data.get('risk_level', 0.3):.1f}")
+            st.write(f"🎯 Tourist Activity: {tourism_data.get('activity_level', 0.6):.1f}")
+
+            st.info("💡 **How it works:** Color reflects air quality, speed varies with weather severity, intensity is influenced by crime data, and size changes with tourist activity levels.")
+
+    else:
+        st.warning("⚠️ City Pulse data unavailable. Please check your API keys or try again later.")
 
     # Create tabs
     tabs = st.tabs(["Weather", "Air Quality", "Tourist Info", "Crime News", "Trends", "Find with City Pulse"]) 
 
-    # --- Existing Tabs (No changes needed for these sections) ---
+    # --- Weather Tab ---
     with tabs[0]:
         st.header(f"Current Weather in {city}")
         weather = get_current_weather(city, lat, lon)
@@ -53,6 +167,7 @@
             })
             st.dataframe(df_monthly)
 
+    # --- Air Quality Tab ---
     with tabs[1]:
         st.header(f"Air Quality in {city}")
         air_quality = get_air_quality(city)
@@ -66,6 +181,7 @@
                 comp_df["Pollutant"] = comp_df["Pollutant"].str.upper()
                 st.table(comp_df)
 
+    # --- Tourist Info Tab ---
     with tabs[2]:
         st.header(f"Tourist Recommendations in {city}")
         tourist_data = get_recommendations(city)
@@ -84,6 +200,7 @@
             else:
                 st.info("No tourist places data available or could not be fetched.")
 
+    # --- Crime News Tab ---
     with tabs[3]:
         st.header(f"Recent Crime News in {city}")
         crime_news = get_crime_news(city)
@@ -100,6 +217,7 @@
             else:
                 st.info("No crime news found.")
 
+    # --- Trends Tab ---
     with tabs[4]:
         st.header("How Popular is Your City? 📈")
         trends = tourist_data.get("trends", [])
@@ -115,29 +233,26 @@
             else:
                 st.info("No trends data available.")
 
-
     # --- Chatbot Tab ---
-
-with tabs[5]:
-    st.header("🤖 Search CityBot")
-
-    if "search_history" not in st.session_state:
-        st.session_state.search_history = []
+    with tabs[5]:
+        st.header("🤖 Search CityBot")
 
-    user_input = st.chat_input("Ask a question (e.g., top cafes, weekend events)")
+        if "search_history" not in st.session_state:
+            st.session_state.search_history = []
+
+        user_input = st.chat_input("Ask a question (e.g., top cafes, weekend events)")
 
-    if user_input:
-        st.session_state.search_history.append({"role": "user", "text": user_input})
+        if user_input:
+            st.session_state.search_history.append({"role": "user", "text": user_input})
 
-        with st.spinner("Searching Google..."):
-            answer = search_google(user_input)
+            with st.spinner("Searching Google..."):
+                answer = search_google(user_input)
 
-        st.session_state.search_history.append({"role": "bot", "text": answer})
-
-    # Display chat messages
-    for msg in st.session_state.search_history:
-        if msg["role"] == "user":
-            st.chat_message("user").markdown(msg["text"])
-        else:
-            st.chat_message("assistant").markdown(msg["text"])
+            st.session_state.search_history.append({"role": "bot", "text": answer})
 
+        # Display chat messages
+        for msg in st.session_state.search_history:
+            if msg["role"] == "user":
+                st.chat_message("user").markdown(msg["text"])
+            else:
+                st.chat_message("assistant").markdown(msg["text"])