"""키워드 분석 오버뷰 — 요약 카드, 테이블, 차트."""
import html

import pandas as pd
import plotly.graph_objects as go
import streamlit as st

from core.charts import POLARITY_COLORS


def render_keyword_overview(keywords_list: list[dict]):
    """키워드 분석 오버뷰 카드."""
    total_keywords = len(keywords_list)
    total_sentences = sum(kw.get("total_sentences", 0) for kw in keywords_list)
    total_brand_mentions = sum(kw.get("brand_mentioned_count", 0) for kw in keywords_list)
    total_no_brand = total_sentences - total_brand_mentions
    brand_mention_rate = (total_brand_mentions / total_sentences * 100) if total_sentences > 0 else 0

    # Brand sentiment aggregation
    brand_pos = sum((kw.get("brand_sentiment") or {}).get("positive", 0) for kw in keywords_list)
    brand_neu = sum((kw.get("brand_sentiment") or {}).get("neutral", 0) for kw in keywords_list)
    brand_neg = sum((kw.get("brand_sentiment") or {}).get("negative", 0) for kw in keywords_list)
    brand_total = brand_pos + brand_neu + brand_neg
    brand_pos_pct = (brand_pos / brand_total * 100) if brand_total > 0 else 0
    brand_neg_pct = (brand_neg / brand_total * 100) if brand_total > 0 else 0

    # Top keyword-brand associations
    top_associations = []
    for kw in sorted(keywords_list, key=lambda x: x.get("brand_mentioned_count", 0), reverse=True)[:3]:
        keyword = kw.get("keyword", "")
        total = kw.get("total_sentences", 0)
        brand_count = kw.get("brand_mentioned_count", 0)
        if total > 0 and brand_count > 0:
            rate = brand_count / total * 100
            top_associations.append(f'"{keyword}" {brand_count:,}건 ({rate:.0f}%)')

    assoc_text = " | ".join(top_associations) if top_associations else "데이터 없음"

    # Brand sentiment bar
    brand_sent_bar = ""
    if brand_total > 0:
        bp = brand_pos / brand_total * 100
        bn = brand_neg / brand_total * 100
        bne = 100 - bp - bn
        brand_sent_bar = f"""
    <div style="display:flex;height:6px;border-radius:3px;overflow:hidden;margin-top:4px;max-width:300px;">
        <div style="width:{bp}%;background:#10B981;"></div>
        <div style="width:{bne}%;background:#D1D5DB;"></div>
        <div style="width:{bn}%;background:#EF4444;"></div>
    </div>"""

    st.markdown(f"""
<div style="background: linear-gradient(135deg, #F8FAFC 0%, #ECFDF5 100%); border: 1px solid #A7F3D0;
            border-radius: 12px; padding: 16px; margin-bottom: 16px;">
    <div style="display: flex; gap: 24px; flex-wrap: wrap; font-size: 13px; color: #374151;">
        <span>분석 키워드: <strong>{total_keywords}개</strong></span>
        <span>전체 문장: <strong>{total_sentences:,}건</strong></span>
    </div>
    <div style="display:flex;gap:20px;flex-wrap:wrap;font-size:12px;color:#374151;margin-top:8px;">
        <span>🏠 브랜드 언급: <strong>{total_brand_mentions:,}건</strong> ({brand_mention_rate:.1f}%)
            &mdash; <span style="color:#10B981;">긍정 {brand_pos_pct:.0f}%</span>
            / <span style="color:#EF4444;">부정 {brand_neg_pct:.0f}%</span>
        </span>
        <span style="color:#6B7280;">비브랜드: <strong>{total_no_brand:,}건</strong> ({100 - brand_mention_rate:.1f}%)</span>
    </div>{brand_sent_bar}
    <div style="font-size: 11px; color: #9CA3AF; margin-top: 6px;">
        키워드-브랜드 연관 상위: {html.escape(assoc_text)}
    </div>
</div>
""", unsafe_allow_html=True)


def render_summary_table(keywords_list: list[dict]):
    """키워드별 감성 요약 테이블."""
    st.markdown("**키워드별 감성 요약**")

    rows = []
    for kw in keywords_list:
        keyword = kw.get("keyword", "")
        total = kw.get("total_sentences", 0)
        ks = kw.get("keyword_sentiment", {})
        pos = ks.get("positive", 0)
        neu = ks.get("neutral", 0)
        neg = ks.get("negative", 0)
        brand_count = kw.get("brand_mentioned_count", 0)

        neg_rate = (neg / total * 100) if total > 0 else 0
        pos_rate = (pos / total * 100) if total > 0 else 0

        # Brand sentiment breakdown
        brand_sent = kw.get("brand_sentiment") or {}
        brand_pos = brand_sent.get("positive", 0)
        brand_neg = brand_sent.get("negative", 0)
        brand_neg_rate = (brand_neg / brand_count * 100) if brand_count > 0 else 0

        rows.append({
            "키워드": keyword,
            "총 문장": total,
            "긍정": pos,
            "중립": neu,
            "부정": neg,
            "부정률": f"{neg_rate:.1f}%",
            "긍정률": f"{pos_rate:.1f}%",
            "브랜드 멘션": brand_count,
            "브랜드 긍정": brand_pos if brand_count > 0 else "-",
            "브랜드 부정": brand_neg if brand_count > 0 else "-",
            "브랜드 부정률": f"{brand_neg_rate:.1f}%" if brand_count > 0 else "-",
        })

    if rows:
        df = pd.DataFrame(rows)
        df = df.sort_values("부정", ascending=False)
        st.dataframe(df, use_container_width=True, hide_index=True)
    else:
        st.info("데이터가 없습니다")


def render_sentiment_chart(keywords_list: list[dict]):
    """키워드 감성 비교 bar chart (부정 비율 순)."""
    st.markdown("**키워드 감성 비교 차트**")

    # Sort by negative count descending
    sorted_kws = sorted(
        keywords_list,
        key=lambda x: x.get("keyword_sentiment", {}).get("negative", 0),
        reverse=True,
    )[:20]  # Top 20

    keywords = [kw.get("keyword", "") for kw in sorted_kws]
    positives = [kw.get("keyword_sentiment", {}).get("positive", 0) for kw in sorted_kws]
    neutrals = [kw.get("keyword_sentiment", {}).get("neutral", 0) for kw in sorted_kws]
    negatives = [kw.get("keyword_sentiment", {}).get("negative", 0) for kw in sorted_kws]

    fig = go.Figure()
    fig.add_trace(go.Bar(
        name="부정", x=keywords, y=negatives,
        marker_color=POLARITY_COLORS["negative"],
    ))
    fig.add_trace(go.Bar(
        name="중립", x=keywords, y=neutrals,
        marker_color=POLARITY_COLORS["neutral"],
    ))
    fig.add_trace(go.Bar(
        name="긍정", x=keywords, y=positives,
        marker_color=POLARITY_COLORS["positive"],
    ))

    fig.update_layout(
        barmode="stack",
        height=400,
        margin=dict(l=20, r=20, t=30, b=80),
        legend=dict(orientation="h", yanchor="bottom", y=1.02),
        xaxis_tickangle=-45,
    )
    st.plotly_chart(fig, use_container_width=True, config={"displayModeBar": False})