Update src/streamlit_app.py
Browse files- src/streamlit_app.py +163 -38
src/streamlit_app.py
CHANGED
@@ -1,40 +1,165 @@
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import altair as alt
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import numpy as np
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import pandas as pd
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import streamlit as st
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st.altair_chart(alt.Chart(df, height=700, width=700)
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.mark_point(filled=True)
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.encode(
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x=alt.X("x", axis=None),
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y=alt.Y("y", axis=None),
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color=alt.Color("idx", legend=None, scale=alt.Scale()),
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size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
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))
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import streamlit as st
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import pandas as pd
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import requests
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import plotly.express as px
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from datetime import date, timedelta
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# --- Page Configuration ---
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st.set_page_config(
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page_title="Earthquake Activity Explorer",
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page_icon="πΊοΈ",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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# --- API Data Fetching Function ---
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@st.cache_data(ttl=600) # Cache data for 10 minutes
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def fetch_earthquakes(start_date, end_date, min_magnitude):
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"""
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Fetches earthquake data from the specified API endpoint.
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Returns a pandas DataFrame or None if an error occurs.
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"""
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API_URL = "https://cwadayi-python-app.hf.space/earthquakes"
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params = {
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"start_date": start_date,
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"end_date": end_date,
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"min_magnitude": min_magnitude
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}
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try:
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response = requests.get(API_URL, params=params, timeout=20)
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response.raise_for_status() # Raises an HTTPError for bad responses (4xx or 5xx)
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data = response.json()
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if not data:
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return pd.DataFrame() # Return empty dataframe if no data
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return pd.DataFrame(data)
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except requests.exceptions.RequestException as e:
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st.error(f"API Request Failed: {e}")
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return None
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except ValueError: # Catches JSON decoding errors
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st.error("Failed to decode API response. The API might be temporarily down.")
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return None
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# --- UI Design ---
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# 1. Title
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st.title("πΊοΈ Global Earthquake Activity Explorer")
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st.markdown("Analyze and visualize recent earthquake events around the world.")
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# 2. Sidebar for User Inputs
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with st.sidebar:
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st.header("π Search Parameters")
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# Use a date range of the last 90 days as a default
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today = date.today()
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default_start_date = today - timedelta(days=90)
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start_date = st.date_input(
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"Start Date",
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value=default_start_date,
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min_value=date(1900, 1, 1),
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max_value=today,
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help="Select the beginning of the date range."
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)
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end_date = st.date_input(
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"End Date",
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value=today,
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min_value=start_date,
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max_value=today,
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help="Select the end of the date range."
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)
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min_magnitude = st.slider(
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"Minimum Magnitude",
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min_value=0.0,
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max_value=10.0,
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value=5.5, # A sensible default to avoid clutter
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step=0.1,
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help="Drag the slider to set the minimum magnitude for queried earthquakes."
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)
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# Action button to trigger the search
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search_button = st.button("Search Earthquakes", type="primary", use_container_width=True)
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# --- Main Content Area ---
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if search_button:
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with st.spinner('Fetching earthquake data from the server... Please wait.'):
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# 3. Fetch data using the function
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df = fetch_earthquakes(start_date, end_date, min_magnitude)
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if df is not None and not df.empty:
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st.success(f"Found {len(df)} earthquakes matching your criteria.")
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# Reformat DataFrame for better display
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df['time'] = pd.to_datetime(df['time'])
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df['magnitude'] = df['mag'].astype(float)
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df['depth'] = df['depth'].astype(float)
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# --- Display Summary Metrics ---
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st.subheader("π Summary Statistics")
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col1, col2, col3 = st.columns(3)
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col1.metric("Total Earthquakes", f"{len(df):,}")
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col2.metric("Largest Magnitude", f"{df['magnitude'].max():.2f}")
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col3.metric("Deepest Event (km)", f"{df['depth'].max():.2f}")
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st.markdown("---")
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# --- 4. Draw Earthquake Distribution Map ---
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st.subheader("π Interactive Earthquake Map")
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st.markdown("Hover over points for details. Circle size represents magnitude.")
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fig = px.scatter_geo(
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df,
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lat='latitude',
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lon='longitude',
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size='magnitude',
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color='depth',
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hover_name='place',
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hover_data={
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'latitude': ':.2f',
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'longitude': ':.2f',
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'time': True,
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'magnitude': ':.2f',
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'depth': ':.2f km'
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},
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projection="natural earth",
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title=f"Earthquakes from {start_date} to {end_date} (Magnitude > {min_magnitude})",
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color_continuous_scale=px.colors.sequential.Plasma_r # Reverse Plasma for depth
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)
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fig.update_layout(
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margin={"r":0,"t":40,"l":0,"b":0},
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coloraxis_colorbar_title_text='Depth (km)'
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)
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st.plotly_chart(fig, use_container_width=True)
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st.markdown("---")
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# --- 5. Show Earthquakes in a Table ---
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st.subheader("π Detailed Earthquake Data")
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# Select and rename columns for a cleaner table display
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display_df = df[['time', 'place', 'magnitude', 'depth', 'url']].copy()
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display_df.rename(columns={
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'time': 'Time (UTC)',
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'place': 'Location',
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'magnitude': 'Magnitude',
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'depth': 'Depth (km)',
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'url': 'More Info'
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}, inplace=True)
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st.dataframe(
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display_df,
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use_container_width=True,
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height=400,
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column_config={
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"More Info": st.column_config.LinkColumn("USGS Event Page")
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}
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)
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elif df is not None and df.empty:
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st.warning(f"No earthquakes with magnitude {min_magnitude} or higher were found in the selected date range.")
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else:
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st.error("Could not retrieve data. Please try again later.")
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else:
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st.info("Please set your desired parameters in the sidebar and click 'Search Earthquakes' to begin.")
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