"""Batch Analysis page for the Streamlit application."""


import streamlit as st

from ..config import ANALYSIS_TEMPLATES


def render_batch_analysis_page():
    """Render the Batch Analysis tutorial page."""
    st.header("Batch Analysis & Templates")

    st.markdown("""
    Perform comprehensive analyses across multiple locations using pre-configured templates 
    or custom configurations. Ideal for large-scale assessments and reporting.
    
    **What you'll learn:**
    - 🎯 Use analysis templates for common scenarios
    - 📍 Analyze multiple locations simultaneously
    - 📊 Generate comparative reports
    - 💾 Export results in multiple formats
    """)

    # Template selection
    st.subheader("Choose Analysis Template")

    template_name = st.selectbox(
        "Select Template",
        options=list(ANALYSIS_TEMPLATES.keys()),
        format_func=lambda x: f"{x} - {ANALYSIS_TEMPLATES[x]['description']}"
    )

    template = ANALYSIS_TEMPLATES[template_name]

    # Display template details
    with st.expander("📋 Template Details"):
        st.markdown(f"**Description:** {template['description']}")
        st.markdown(f"**POI Types:** {', '.join(template['poi_types'])}")
        st.markdown(f"**Census Variables:** {', '.join(template['census_vars'])}")
        st.markdown(f"**Travel Time:** {template['travel_time']} minutes")

    # Location input
    st.subheader("Configure Locations")

    input_method = st.radio(
        "How would you like to input locations?",
        options=["Text Input", "Upload CSV", "Select from Map"]
    )

    locations = []

    if input_method == "Text Input":
        location_text = st.text_area(
            "Enter locations (one per line)",
            value="Durham, North Carolina\nChapel Hill, North Carolina\nRaleigh, North Carolina",
            height=150
        )
        locations = [loc.strip() for loc in location_text.split('\n') if loc.strip()]

    elif input_method == "Upload CSV":
        uploaded_file = st.file_uploader(
            "Upload location CSV",
            type="csv",
            help="CSV should have 'location' or 'address' column"
        )
        if uploaded_file:
            st.info("CSV processing coming soon!")

    else:  # Select from Map
        st.info("Interactive map selection coming soon!")

    # Display location count
    if locations:
        st.info(f"📍 {len(locations)} locations selected")

    # Analysis options
    st.subheader("Analysis Options")

    col1, col2 = st.columns(2)

    with col1:
        travel_mode = st.selectbox(
            "Travel Mode",
            options=["walk", "bike", "drive"],
            index=0
        )

        parallel_processing = st.checkbox(
            "Enable parallel processing",
            value=True,
            help="Process multiple locations simultaneously"
        )

    with col2:
        output_format = st.selectbox(
            "Output Format",
            options=["CSV", "Excel", "GeoJSON", "HTML Report"],
            index=0
        )

        include_maps = st.checkbox(
            "Generate maps for each location",
            value=True
        )

    # Run analysis
    if st.button("🚀 Run Batch Analysis", type="primary", disabled=not locations):
        with st.spinner(f"Analyzing {len(locations)} locations..."):
            progress_bar = st.progress(0)
            status_text = st.empty()

            # Simulate batch processing
            for idx, location in enumerate(locations):
                status_text.text(f"Analyzing {location}...")
                progress_bar.progress((idx + 1) / len(locations))

            st.success("✅ Batch analysis complete!")

            # Results summary
            st.subheader("📊 Analysis Summary")

            col1, col2, col3, col4 = st.columns(4)

            with col1:
                st.metric("Locations Analyzed", len(locations))

            with col2:
                st.metric("Total POIs Found", "156")

            with col3:
                st.metric("Population Covered", "485,320")

            with col4:
                st.metric("Processing Time", "2m 34s")

            # Comparative results
            st.subheader("🔍 Comparative Results")

            st.markdown("""
            | Location | POIs Found | Population | Median Income | Access Score |
            |----------|------------|------------|---------------|--------------|
            | Durham, NC | 45 | 162,340 | $54,200 | 82% |
            | Chapel Hill, NC | 62 | 98,450 | $68,400 | 91% |
            | Raleigh, NC | 49 | 224,530 | $58,600 | 78% |
            """)

            # Download options
            st.subheader("📥 Download Results")

            col1, col2, col3 = st.columns(3)

            with col1:
                st.button("📄 Download Report", type="secondary")

            with col2:
                st.button("💾 Download Data", type="secondary")

            with col3:
                st.button("🗺️ Download Maps", type="secondary")
