kol-insight/backend/app/services/video_analysis.py

"""
视频分析服务 (T-024)

实现视频分析数据获取和成本指标计算。
"""

import logging
from datetime import datetime
from typing import Dict, Optional, Any

from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy import select

from sqlalchemy import update

from app.models.kol_video import KolVideo
from app.services.yuntu_api import (
    get_video_analysis as fetch_yuntu_analysis,
    parse_analysis_response,
    YuntuAPIError,
)

logger = logging.getLogger(__name__)


def calculate_cost_metrics(
    cost: float,
    natural_play_cnt: int,
    a3_increase_cnt: int,
    natural_a3_increase_cnt: int,
    after_view_search_uv: int,
    total_play_cnt: int,
) -> Dict[str, Optional[float]]:
    """
    计算成本指标。

    Args:
        cost: 总花费
        natural_play_cnt: 自然播放数
        a3_increase_cnt: 新增A3
        natural_a3_increase_cnt: 自然新增A3
        after_view_search_uv: 看后搜人数
        total_play_cnt: 总播放数

    Returns:
        Dict: 成本指标字典
    """
    metrics = {}

    # CPM = cost / total_play_cnt * 1000
    if total_play_cnt and total_play_cnt > 0:
        metrics["cpm"] = round(cost / total_play_cnt * 1000, 2)
    else:
        metrics["cpm"] = None

    # 自然CPM = cost / natural_play_cnt * 1000
    if natural_play_cnt and natural_play_cnt > 0:
        metrics["natural_cpm"] = round(cost / natural_play_cnt * 1000, 2)
    else:
        metrics["natural_cpm"] = None

    # CPA3 = cost / a3_increase_cnt
    if a3_increase_cnt and a3_increase_cnt > 0:
        metrics["cpa3"] = round(cost / a3_increase_cnt, 2)
    else:
        metrics["cpa3"] = None

    # 自然CPA3 = cost / natural_a3_increase_cnt
    if natural_a3_increase_cnt and natural_a3_increase_cnt > 0:
        metrics["natural_cpa3"] = round(cost / natural_a3_increase_cnt, 2)
    else:
        metrics["natural_cpa3"] = None

    # CPsearch = cost / after_view_search_uv
    if after_view_search_uv and after_view_search_uv > 0:
        metrics["cp_search"] = round(cost / after_view_search_uv, 2)
    else:
        metrics["cp_search"] = None

    # 预估自然看后搜人数 = natural_play_cnt / total_play_cnt * after_view_search_uv
    if total_play_cnt and total_play_cnt > 0 and after_view_search_uv:
        estimated_natural_search_uv = (
            natural_play_cnt / total_play_cnt * after_view_search_uv
        )
        metrics["estimated_natural_search_uv"] = round(estimated_natural_search_uv, 2)

        # 自然CPsearch = cost / estimated_natural_search_uv
        if estimated_natural_search_uv > 0:
            metrics["natural_cp_search"] = round(cost / estimated_natural_search_uv, 2)
        else:
            metrics["natural_cp_search"] = None
    else:
        metrics["estimated_natural_search_uv"] = None
        metrics["natural_cp_search"] = None

    return metrics


async def get_video_base_info(
    session: AsyncSession, item_id: str
) -> Optional[KolVideo]:
    """
    从数据库获取视频基础信息。

    Args:
        session: 数据库会话
        item_id: 视频ID

    Returns:
        KolVideo or None
    """
    stmt = select(KolVideo).where(KolVideo.item_id == item_id)
    result = await session.execute(stmt)
    return result.scalar_one_or_none()


async def get_video_analysis_data(
    session: AsyncSession, item_id: str
) -> Dict[str, Any]:
    """
    获取视频分析数据（T-024主接口）。

    包含：
    - 基础信息（从数据库）
    - 触达指标（从巨量云图API）
    - A3指标
    - 搜索指标
    - 费用指标
    - 成本指标（计算得出）

    Args:
        session: 数据库会话
        item_id: 视频ID

    Returns:
        Dict: 完整的视频分析数据

    Raises:
        ValueError: 视频不存在时抛出
        YuntuAPIError: API调用失败时抛出
    """
    # 1. 从数据库获取基础信息
    video = await get_video_base_info(session, item_id)
    if video is None:
        raise ValueError(f"Video not found: {item_id}")

    # 2. 构建基础信息
    base_info = {
        "item_id": video.item_id,
        "title": video.title,
        "video_url": video.video_url,
        "star_id": video.star_id,
        "star_unique_id": video.star_unique_id,
        "star_nickname": video.star_nickname,
        "publish_time": video.publish_time.isoformat() if video.publish_time else None,
        "industry_name": video.industry_name,
    }

    # 3. 调用巨量云图API获取实时数据
    try:
        publish_time = video.publish_time or datetime.now()
        industry_id = video.industry_id or ""

        api_response = await fetch_yuntu_analysis(
            item_id=item_id,
            publish_time=publish_time,
            industry_id=industry_id,
        )

        # 4. 解析API响应
        analysis_data = parse_analysis_response(api_response)

    except YuntuAPIError as e:
        logger.error(f"Failed to get yuntu analysis for {item_id}: {e.message}")
        # API失败时，使用数据库中的数据
        analysis_data = {
            "total_show_cnt": video.total_play_cnt or 0,
            "natural_show_cnt": video.natural_play_cnt or 0,
            "ad_show_cnt": video.heated_play_cnt or 0,
            "total_play_cnt": video.total_play_cnt or 0,
            "natural_play_cnt": video.natural_play_cnt or 0,
            "ad_play_cnt": video.heated_play_cnt or 0,
            "effective_play_cnt": 0,
            "a3_increase_cnt": 0,
            "ad_a3_increase_cnt": 0,
            "natural_a3_increase_cnt": 0,
            "after_view_search_uv": video.after_view_search_uv or 0,
            "after_view_search_pv": 0,
            "brand_search_uv": 0,
            "product_search_uv": 0,
            "return_search_cnt": video.return_search_cnt or 0,
            "cost": video.estimated_video_cost or 0,
            "natural_cost": 0,
            "ad_cost": 0,
        }

    # 5. 计算成本指标
    cost = analysis_data.get("cost", 0) or (video.estimated_video_cost or 0)
    cost_metrics = calculate_cost_metrics(
        cost=cost,
        natural_play_cnt=analysis_data.get("natural_play_cnt", 0),
        a3_increase_cnt=analysis_data.get("a3_increase_cnt", 0),
        natural_a3_increase_cnt=analysis_data.get("natural_a3_increase_cnt", 0),
        after_view_search_uv=analysis_data.get("after_view_search_uv", 0),
        total_play_cnt=analysis_data.get("total_play_cnt", 0),
    )

    # 6. 组装返回数据
    return {
        "base_info": base_info,
        "reach_metrics": {
            "total_show_cnt": analysis_data.get("total_show_cnt", 0),
            "natural_show_cnt": analysis_data.get("natural_show_cnt", 0),
            "ad_show_cnt": analysis_data.get("ad_show_cnt", 0),
            "total_play_cnt": analysis_data.get("total_play_cnt", 0),
            "natural_play_cnt": analysis_data.get("natural_play_cnt", 0),
            "ad_play_cnt": analysis_data.get("ad_play_cnt", 0),
            "effective_play_cnt": analysis_data.get("effective_play_cnt", 0),
        },
        "a3_metrics": {
            "a3_increase_cnt": analysis_data.get("a3_increase_cnt", 0),
            "ad_a3_increase_cnt": analysis_data.get("ad_a3_increase_cnt", 0),
            "natural_a3_increase_cnt": analysis_data.get("natural_a3_increase_cnt", 0),
        },
        "search_metrics": {
            "after_view_search_uv": analysis_data.get("after_view_search_uv", 0),
            "after_view_search_pv": analysis_data.get("after_view_search_pv", 0),
            "brand_search_uv": analysis_data.get("brand_search_uv", 0),
            "product_search_uv": analysis_data.get("product_search_uv", 0),
            "return_search_cnt": analysis_data.get("return_search_cnt", 0),
        },
        "cost_metrics_raw": {
            "cost": analysis_data.get("cost", 0),
            "natural_cost": analysis_data.get("natural_cost", 0),
            "ad_cost": analysis_data.get("ad_cost", 0),
        },
        "cost_metrics_calculated": cost_metrics,
    }


async def update_video_a3_metrics(
    session: AsyncSession,
    item_id: str,
    total_new_a3_cnt: int,
    heated_new_a3_cnt: int,
    natural_new_a3_cnt: int,
    total_cost: float,
) -> bool:
    """
    更新数据库中的A3指标 (T-025)。

    Args:
        session: 数据库会话
        item_id: 视频ID
        total_new_a3_cnt: 总新增A3
        heated_new_a3_cnt: 加热新增A3
        natural_new_a3_cnt: 自然新增A3
        total_cost: 总花费

    Returns:
        bool: 更新是否成功
    """
    try:
        stmt = (
            update(KolVideo)
            .where(KolVideo.item_id == item_id)
            .values(
                total_new_a3_cnt=total_new_a3_cnt,
                heated_new_a3_cnt=heated_new_a3_cnt,
                natural_new_a3_cnt=natural_new_a3_cnt,
                total_cost=total_cost,
            )
        )
        result = await session.execute(stmt)
        await session.commit()

        if result.rowcount > 0:
            logger.info(f"Updated A3 metrics for video {item_id}")
            return True
        else:
            logger.warning(f"No video found to update: {item_id}")
            return False

    except Exception as e:
        logger.error(f"Failed to update A3 metrics for {item_id}: {e}")
        await session.rollback()
        return False


async def get_and_update_video_analysis(
    session: AsyncSession, item_id: str
) -> Dict[str, Any]:
    """
    获取视频分析数据并更新数据库中的A3指标 (T-024 + T-025 组合)。

    Args:
        session: 数据库会话
        item_id: 视频ID

    Returns:
        Dict: 完整的视频分析数据
    """
    # 获取分析数据
    result = await get_video_analysis_data(session, item_id)

    # 提取A3指标
    a3_metrics = result.get("a3_metrics", {})
    cost_raw = result.get("cost_metrics_raw", {})

    # 更新数据库
    await update_video_a3_metrics(
        session=session,
        item_id=item_id,
        total_new_a3_cnt=a3_metrics.get("a3_increase_cnt", 0),
        heated_new_a3_cnt=a3_metrics.get("ad_a3_increase_cnt", 0),
        natural_new_a3_cnt=a3_metrics.get("natural_a3_increase_cnt", 0),
        total_cost=cost_raw.get("cost", 0),
    )

    return result