"""리포트 탭.

Feature별 미리보기, HTML/CSV 다운로드, 전체 리포트 생성.
"""
from datetime import datetime, timedelta

import streamlit as st

from core.api_client import ChainShiftClient
from core.supabase_client import get_campaign_date_range

from .utils import render_feature_section
from . import full_report


# Period presets: (label, days or None for "all")
PERIOD_PRESETS = [
    ("최근 1일", 1),
    ("최근 7일", 7),
    ("최근 30일", 30),
    ("최근 90일", 90),
    ("최근 180일", 180),
    ("전체 기간", None),
    ("직접 선택", -1),
]


def render(base_ctx: dict):
    """리포트 탭 렌더링."""
    st.markdown("##### 리포트")
    st.caption("기간별 AI 가시성 분석 리포트를 생성하고, HTML로 다운로드할 수 있습니다.")

    # Get campaign date range for presets
    campaign_date_range = get_campaign_date_range(base_ctx["campaign_id"])
    if campaign_date_range:
        first_date_str, last_date_str = campaign_date_range
        first_date = datetime.strptime(first_date_str, "%Y-%m-%d")
        last_date = datetime.strptime(last_date_str, "%Y-%m-%d")
        total_days = (last_date - first_date).days + 1
    else:
        first_date = datetime.now() - timedelta(days=30)
        last_date = datetime.now()
        first_date_str = first_date.strftime("%Y-%m-%d")
        last_date_str = last_date.strftime("%Y-%m-%d")
        total_days = 31

    # Period selection
    start_date_str, end_date_str = _render_period_selector(
        first_date, last_date, first_date_str, last_date_str, total_days
    )

    # Show selected period info
    selected_days = (datetime.strptime(end_date_str, "%Y-%m-%d") - datetime.strptime(start_date_str, "%Y-%m-%d")).days + 1
    st.caption(f"📅 선택된 기간: **{start_date_str} ~ {end_date_str}** ({selected_days}일)")

    st.markdown("---")

    # 4 Sub-tabs for Features + 1 for Full Report
    report_tab_summary, report_tab_visibility, report_tab_citation, report_tab_full = st.tabs([
        "📊 Executive Summary",
        "👁️ Visibility & Content",
        "🔗 Citation Analysis",
        "📄 전체 리포트",
    ])

    client = ChainShiftClient(api_key=base_ctx.get("api_key"), access_token=base_ctx.get("access_token"))

    # Tab 1: Executive Summary
    with report_tab_summary:
        render_feature_section(
            client=client,
            campaign_id=base_ctx["campaign_id"],
            feature_key="overview",
            title="가시성 개요",
            description="AI 플랫폼별 브랜드 노출 현황과 핵심 지표",
            start_date=start_date_str,
            end_date=end_date_str,
            api_key=base_ctx.get("api_key") or "",
            access_token=base_ctx.get("access_token") or "",
        )

    # Tab 2: Visibility & Content
    with report_tab_visibility:
        render_feature_section(
            client=client,
            campaign_id=base_ctx["campaign_id"],
            feature_key="visibility",
            title="플랫폼별 가시성",
            description="ChatGPT, Gemini 등 AI 플랫폼별 자사 vs 경쟁사 노출 비교",
            start_date=start_date_str,
            end_date=end_date_str,
            api_key=base_ctx.get("api_key") or "",
            access_token=base_ctx.get("access_token") or "",
        )

        render_feature_section(
            client=client,
            campaign_id=base_ctx["campaign_id"],
            feature_key="content-types",
            title="콘텐츠 유형 분포",
            description="AI가 인용하는 콘텐츠 유형 (블로그, 뉴스, 공식 사이트 등)",
            start_date=start_date_str,
            end_date=end_date_str,
            api_key=base_ctx.get("api_key") or "",
            access_token=base_ctx.get("access_token") or "",
        )

        render_feature_section(
            client=client,
            campaign_id=base_ctx["campaign_id"],
            feature_key="sentiment",
            title="브랜드 감정 분석",
            description="브랜드별 긍정/부정/중립 감정 분포",
            start_date=start_date_str,
            end_date=end_date_str,
            api_key=base_ctx.get("api_key") or "",
            access_token=base_ctx.get("access_token") or "",
        )

    # Tab 3: Citation Analysis
    with report_tab_citation:

        render_feature_section(
            client=client,
            campaign_id=base_ctx["campaign_id"],
            feature_key="citations",
            title="인용 출처 순위",
            description="AI 답변에서 가장 많이 인용되는 도메인과 출처",
            start_date=start_date_str,
            end_date=end_date_str,
            api_key=base_ctx.get("api_key") or "",
            access_token=base_ctx.get("access_token") or "",
        )

        render_feature_section(
            client=client,
            campaign_id=base_ctx["campaign_id"],
            feature_key="citation-trends",
            title="인용 추이",
            description="시간에 따른 인용 출처 변화 트렌드",
            start_date=start_date_str,
            end_date=end_date_str,
            api_key=base_ctx.get("api_key") or "",
            access_token=base_ctx.get("access_token") or "",
        )

        render_feature_section(
            client=client,
            campaign_id=base_ctx["campaign_id"],
            feature_key="homepage-citations",
            title="홈페이지 인용률",
            description="자사 홈페이지가 AI 답변에 직접 인용되는 비율",
            start_date=start_date_str,
            end_date=end_date_str,
            api_key=base_ctx.get("api_key") or "",
            access_token=base_ctx.get("access_token") or "",
        )

    # Tab 4: Full Report
    with report_tab_full:
        full_report.render(client, base_ctx, start_date_str, end_date_str)


def _render_period_selector(
    first_date: datetime,
    last_date: datetime,
    first_date_str: str,
    last_date_str: str,
    total_days: int,
) -> tuple[str, str]:
    """기간 선택 UI 렌더링. (start_date, end_date) 반환."""
    col_period, col_date1, col_date2 = st.columns([1.5, 1, 1])

    with col_period:
        period_options = [label for label, _ in PERIOD_PRESETS]
        selected_period = st.selectbox(
            "분석 기간",
            options=period_options,
            index=5,  # Default to "전체 기간"
            key="reports:period_select",
            help=f"캠페인 데이터: {first_date_str} ~ {last_date_str} (총 {total_days}일)",
        )

    period_idx = period_options.index(selected_period)
    _, period_days = PERIOD_PRESETS[period_idx]

    if period_days == -1:  # Custom selection
        with col_date1:
            report_start = st.date_input(
                "시작일",
                value=first_date,
                min_value=first_date,
                max_value=last_date,
                key="reports:start_date",
            )
        with col_date2:
            report_end = st.date_input(
                "종료일",
                value=last_date,
                min_value=first_date,
                max_value=last_date,
                key="reports:end_date",
            )
        return str(report_start), str(report_end)
    elif period_days is None:  # All data
        with col_date1:
            st.text_input("시작일", value=first_date_str, disabled=True, key="reports:start_display")
        with col_date2:
            st.text_input("종료일", value=last_date_str, disabled=True, key="reports:end_display")
        return first_date_str, last_date_str
    else:  # Preset days
        end_date = last_date
        start_date = max(first_date, end_date - timedelta(days=period_days - 1))
        start_date_str = start_date.strftime("%Y-%m-%d")
        end_date_str = end_date.strftime("%Y-%m-%d")
        with col_date1:
            st.text_input("시작일", value=start_date_str, disabled=True, key="reports:start_display")
        with col_date2:
            st.text_input("종료일", value=end_date_str, disabled=True, key="reports:end_display")
        return start_date_str, end_date_str