app/components/news.py

"""News display components for the financial dashboard."""

import streamlit as st
import pandas as pd
from datetime import datetime
import html as html_module


def display_news_card(news_item: dict):
    """Display a single news card with professional styling using Streamlit components."""

    # Calculate time ago
    time_diff = datetime.now() - news_item['timestamp']
    if time_diff.seconds < 60:
        time_ago = f"{time_diff.seconds}s ago"
    elif time_diff.seconds < 3600:
        time_ago = f"{time_diff.seconds // 60}m ago"
    else:
        time_ago = f"{time_diff.seconds // 3600}h ago"

    # Create container with custom styling
    with st.container():
        # Add custom CSS for this card
        st.markdown("""
        <style>
        .news-card {
            background: linear-gradient(135deg, #1f2937 0%, #111827 100%);
            border: 1px solid #374151;
            border-radius: 12px;
            padding: 20px;
            margin-bottom: 16px;
        }
        </style>
        """, unsafe_allow_html=True)

        # Header row with source and badges
        col1, col2 = st.columns([3, 1])

        with col1:
            # Source and badges in one line
            badge_cols = st.columns([2, 1, 1, 1])
            with badge_cols[0]:
                st.markdown(f"**:blue[{news_item['source']}]**")
            with badge_cols[1]:
                if news_item['impact'] == 'high':
                    st.markdown("🔴 **HIGH**")
                elif news_item['impact'] == 'medium':
                    st.markdown("🟡 **MED**")
                else:
                    st.markdown("🟢 **LOW**")
            with badge_cols[2]:
                sentiment_emoji = {'positive': '📈', 'negative': '📉', 'neutral': '➡️'}
                st.markdown(f"{sentiment_emoji.get(news_item['sentiment'], '➡️')} {news_item['sentiment'].title()}")
            with badge_cols[3]:
                st.markdown(f"**#{news_item['category']}**")

        with col2:
            st.markdown(f"[**Read More →**]({news_item['url']})")

        # Title/Summary
        st.markdown(f"### {news_item.get('summary', '').strip()}")

        # Meta information
        st.caption(f"🕐 {time_ago}")

        st.markdown("---")


def display_news_feed(df: pd.DataFrame, max_items: int = 20):
    """Display a feed of news items."""

    if df.empty:
        st.info("📭 No news available. Adjust your filters or refresh the feed.")
        return

    # Add custom CSS for animations
    st.markdown("""
    <style>
    @keyframes pulse {
        0%, 100% { opacity: 1; }
        50% { opacity: 0.6; }
    }
    </style>
    """, unsafe_allow_html=True)

    # Display news items
    for idx, row in df.head(max_items).iterrows():
        display_news_card(row.to_dict())


def display_news_statistics(stats: dict):
    """Display news feed statistics in metric cards."""

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

    with col1:
        st.metric(
            "Total Stories",
            f"{stats['total']}",
            help="Total news items in feed"
        )

    with col2:
        st.metric(
            "High Impact",
            f"{stats['high_impact']}",
            delta=f"{(stats['high_impact']/max(stats['total'], 1)*100):.0f}%",
            help="High-impact market-moving news"
        )

    with col3:
        st.metric(
            "Breaking News",
            f"{stats['breaking']}",
            delta="LIVE" if stats['breaking'] > 0 else None,
            help="Breaking news alerts"
        )

    with col4:
        st.metric(
            "Last Update",
            stats['last_update'],
            help="Time of last news fetch"
        )


def display_category_breakdown(stats: dict):
    """Display news breakdown by category using Streamlit components."""

    if 'by_category' not in stats:
        return

    st.markdown("### 📊 News by Category")

    categories = stats['by_category']
    total = sum(categories.values())

    if total == 0:
        st.info("No categorized news available")
        return

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

    with col1:
        macro_count = categories.get('macro', 0)
        macro_pct = (macro_count / total) * 100
        with st.container():
            st.markdown("**:blue[📈 MACRO]**")
            st.markdown(f"# {macro_count}")
            st.caption(f"{macro_pct:.1f}% of total")

    with col2:
        geo_count = categories.get('geopolitical', 0)
        geo_pct = (geo_count / total) * 100
        with st.container():
            st.markdown("**:orange[🌍 GEOPOLITICAL]**")
            st.markdown(f"# {geo_count}")
            st.caption(f"{geo_pct:.1f}% of total")

    with col3:
        markets_count = categories.get('markets', 0)
        markets_pct = (markets_count / total) * 100
        with st.container():
            st.markdown("**:green[💹 MARKETS]**")
            st.markdown(f"# {markets_count}")
            st.caption(f"{markets_pct:.1f}% of total")


def display_breaking_news_banner(df: pd.DataFrame):
    """Display breaking news banner at the top using Streamlit components."""

    breaking = df[df['is_breaking'] == True] if not df.empty and 'is_breaking' in df.columns else pd.DataFrame()

    if not breaking.empty:
        latest = breaking.iloc[0]

        # Create container with red background styling
        with st.container():
            st.markdown("""
            <style>
            .breaking-news-container {
                background: linear-gradient(135deg, #dc2626 0%, #991b1b 100%);
                border-radius: 12px;
                padding: 20px;
                margin-bottom: 24px;
                border: 2px solid #fca5a5;
            }
            </style>
            """, unsafe_allow_html=True)

            # Layout with emoji and content
            col1, col2, col3 = st.columns([1, 8, 2])

            with col1:
                st.markdown("# 🚨")

            with col2:
                st.markdown(f"**:red[BREAKING NEWS • {latest['source'].upper()}]**")
                st.markdown(f"## {latest.get('summary', '').strip()}")

            with col3:
                st.markdown(f"[**READ NOW →**]({latest['url']})")