Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,143 +1,143 @@
 import streamlit as st
 import pandas as pd
-import requests
 import plotly.express as px
 from datetime import date, timedelta
 
+# Import ObsPy for live data fetching
+import obspy
+from obspy.clients.fdsn import Client
+from obspy import UTCDateTime
+
 # --- Page Configuration ---
 st.set_page_config(
-    page_title="Earthquake Activity Explorer",
-    page_icon="🗺️",
+    page_title="Live Earthquake Explorer (ObsPy)",
+    page_icon="🛰️",
     layout="wide",
     initial_sidebar_state="expanded"
 )
 
-# --- API Data Fetching Function ---
-@st.cache_data(ttl=600)
-def fetch_earthquakes(start_date, end_date, min_magnitude):
+# --- Live Data Fetching Function using ObsPy ---
+@st.cache_data(ttl=900)  # Cache the data for 15 minutes
+def fetch_live_data(start_date, end_date, min_mag):
     """
-    Fetches earthquake data from the specified API endpoint.
-    Returns a pandas DataFrame or None if an error occurs.
+    Fetches live earthquake data from the IRIS FDSN web service using ObsPy.
     """
-    API_URL = "https://cwadayi-python-app.hf.space/earthquakes"
-    params = {
-        "start_date": start_date,
-        "end_date": end_date,
-        "min_magnitude": min_magnitude
-    }
+    # Initialize the FDSN client
+    client = Client("IRIS")
+    
+    # Convert dates to ObsPy's UTCDateTime format
+    start_time = UTCDateTime(start_date)
+    # Add one day to the end date to ensure the entire day is included
+    end_time = UTCDateTime(end_date) + timedelta(days=1)
+
     try:
-        response = requests.get(API_URL, params=params, timeout=20)
-        response.raise_for_status()
-        data = response.json()
-        if not data:
-            return pd.DataFrame()
-        return pd.DataFrame(data)
-    except requests.exceptions.RequestException as e:
-        st.error(f"API Request Failed: {e}")
-        return None
-    except ValueError:
-        st.error("Failed to decode API response. The API might be temporarily down.")
-        return None
+        # Fetch the earthquake catalog
+        catalog = client.get_events(
+            starttime=start_time,
+            endtime=end_time,
+            minmagnitude=min_mag
+        )
+    except Exception as e:
+        st.error(f"Could not retrieve data from IRIS FDSN service: {e}")
+        return pd.DataFrame() # Return empty dataframe on error
+
+    # Process the catalog into a list of dictionaries
+    event_list = []
+    for event in catalog:
+        # Skip events that lack a preferred origin or magnitude to prevent errors
+        if not (event.preferred_origin() and event.preferred_magnitude()):
+            continue
+
+        origin = event.preferred_origin()
+        magnitude = event.preferred_magnitude()
+        
+        # Get location description
+        description = "N/A"
+        if event.descriptions and event.descriptions[0].text:
+            description = event.descriptions[0].text
+
+        event_list.append({
+            "latitude": origin.latitude,
+            "longitude": origin.longitude,
+            "depth": origin.depth / 1000,  # Convert depth from meters to km
+            "magnitude": magnitude.mag,
+            "time": origin.time.datetime,
+            "place": description,
+        })
+    
+    if not event_list:
+        return pd.DataFrame()
+
+    return pd.DataFrame(event_list)
 
 # --- UI Design ---
-st.title("🗺️ Global Earthquake Activity Explorer")
-st.markdown("Analyze and visualize recent earthquake events around the world.")
+st.title("🛰️ Live Earthquake Explorer with ObsPy")
+st.markdown("Data is fetched in real-time from the **IRIS FDSN** web service.")
 
 with st.sidebar:
     st.header("🔍 Search Parameters")
+
+    # Set default dates: today and 30 days prior
     today = date.today()
-    default_start_date = today - timedelta(days=90)
-    start_date = st.date_input("Start Date", value=default_start_date, min_value=date(1900, 1, 1), max_value=today, help="Select the beginning of the date range.")
-    end_date = st.date_input("End Date", value=today, min_value=start_date, max_value=today, help="Select the end of the date range.")
-    min_magnitude = st.slider("Minimum Magnitude", min_value=0.0, max_value=10.0, value=5.5, step=0.1, help="Drag the slider to set the minimum magnitude for queried earthquakes.")
+    thirty_days_ago = today - timedelta(days=30)
+
+    start_date = st.date_input("Start Date", value=thirty_days_ago)
+    end_date = st.date_input("End Date", value=today)
+
+    min_magnitude = st.slider("Minimum Magnitude", 0.0, 10.0, 5.0, 0.1)
+
     search_button = st.button("Search Earthquakes", type="primary", use_container_width=True)
 
 # --- Main Content Area ---
 if search_button:
-    with st.spinner('Fetching earthquake data from the server... Please wait.'):
-        df = fetch_earthquakes(start_date, end_date, min_magnitude)
-
-    if df is not None and not df.empty:
-        # --- DIAGNOSTIC FIX IS HERE ---
-        # This logic now includes a debugging message to reveal the available columns.
-        time_col = None
-        if 'event_time' in df.columns:
-            time_col = 'event_time'
-        elif 'time' in df.columns:
-            time_col = 'time'
-        
-        if time_col:
-            df['time'] = pd.to_datetime(df[time_col])
-        else:
-            # If no time column is found, print the available columns for debugging.
-            st.error("Data format error: Could not find a valid time column in the API response.")
-            st.warning("The API returned data, but the column names were not as expected.")
-            st.write("**Available columns found in the data:**", df.columns.tolist())
-            st.stop()
-        
-        # --- The rest of the script continues as before ---
-        st.success(f"Found {len(df)} earthquakes matching your criteria.")
-        df['magnitude'] = df['mag'].astype(float)
-        df['depth'] = df['depth'].astype(float)
-
-        st.subheader("📊 Summary Statistics")
-        col1, col2, col3 = st.columns(3)
-        col1.metric("Total Earthquakes", f"{len(df):,}")
-        col2.metric("Largest Magnitude", f"{df['magnitude'].max():.2f}")
-        col3.metric("Deepest Event (km)", f"{df['depth'].max():.2f}")
-        
-        st.markdown("---")
-        st.subheader("🌍 Interactive Earthquake Map")
-        st.markdown("Hover over points for details. Circle size represents magnitude.")
-
-        fig = px.scatter_geo(
-            df,
-            lat='latitude',
-            lon='longitude',
-            size='magnitude',
-            color='depth',
-            hover_name='place',
-            hover_data={
-                'latitude': ':.2f',
-                'longitude': ':.2f',
-                'time': True,
-                'magnitude': ':.2f',
-                'depth': ':.2f km'
-            },
-            projection="natural earth",
-            title=f"Earthquakes from {start_date} to {end_date} (Magnitude > {min_magnitude})",
-            color_continuous_scale=px.colors.sequential.Plasma_r
-        )
-        
-        fig.update_layout(
-            margin={"r":0,"t":40,"l":0,"b":0},
-            coloraxis_colorbar_title_text='Depth (km)'
-        )
-        st.plotly_chart(fig, use_container_width=True)
-
-        st.markdown("---")
-        st.subheader("📋 Detailed Earthquake Data")
-        
-        display_df = df[['time', 'place', 'magnitude', 'depth', 'url']].copy()
-        display_df.rename(columns={
-            'time': 'Time (UTC)',
-            'place': 'Location',
-            'magnitude': 'Magnitude',
-            'depth': 'Depth (km)',
-            'url': 'More Info'
-        }, inplace=True)
-        
-        st.dataframe(
-            display_df,
-            use_container_width=True,
-            height=400,
-            column_config={
-                "More Info": st.column_config.LinkColumn("USGS Event Page")
-            }
-        )
-    elif df is not None and df.empty:
-        st.warning(f"No earthquakes with magnitude {min_magnitude} or higher were found in the selected date range.")
+    # Validate date range
+    if start_date > end_date:
+        st.error("Error: Start date cannot be after end date.")
     else:
-        st.error("Could not retrieve data. Please try again later.")
+        with st.spinner(f"Fetching earthquakes from {start_date} to {end_date}..."):
+            df = fetch_live_data(start_date, end_date, min_magnitude)
+
+        if not df.empty:
+            st.success(f"Found {len(df)} earthquakes matching your criteria.")
+
+            # --- Display Summary Metrics ---
+            st.subheader("📊 Summary Statistics")
+            col1, col2, col3 = st.columns(3)
+            col1.metric("Total Earthquakes", f"{len(df):,}")
+            col2.metric("Largest Magnitude", f"{df['magnitude'].max():.1f}")
+            col3.metric("Deepest Event (km)", f"{df['depth'].max():.1f}")
+            
+            st.markdown("---")
+
+            # --- Draw Earthquake Distribution Map ---
+            st.subheader("🌍 Interactive Earthquake Map")
+            st.markdown("Hover over points for details. Circle size represents magnitude.")
+
+            fig = px.scatter_geo(
+                df,
+                lat='latitude',
+                lon='longitude',
+                size='magnitude',
+                color='depth',
+                hover_name='place',
+                hover_data={'latitude': ':.2f', 'longitude': ':.2f', 'time': '|%Y-%m-%d %H:%M', 'magnitude': ':.1f', 'depth': ':.1f km'},
+                projection="natural earth",
+                title=f"Live Earthquakes from {start_date} to {end_date} (Magnitude > {min_magnitude})",
+                color_continuous_scale=px.colors.sequential.Plasma_r
+            )
+            fig.update_layout(margin={"r":0,"t":40,"l":0,"b":0}, coloraxis_colorbar_title_text='Depth (km)')
+            st.plotly_chart(fig, use_container_width=True)
+
+            # --- Show Earthquakes in a Table ---
+            st.subheader("📋 Detailed Earthquake Data")
+            display_df = df[['time', 'place', 'magnitude', 'depth']].copy()
+            st.dataframe(
+                display_df.sort_values(by='time', ascending=False),
+                use_container_width=True,
+                height=400,
+                column_config={"time": st.column_config.DatetimeColumn("Time (UTC)", format="YYYY-MM-DD HH:mm")}
+            )
+        else:
+            st.warning("No earthquakes were found for the specified criteria. Try expanding the date range or lowering the magnitude.")
 else:
-    st.info("Please set your desired parameters in the sidebar and click 'Search Earthquakes' to begin.")
+    st.info("Set your desired parameters in the sidebar and click 'Search Earthquakes' to begin.")