"""
五维分析引擎 + 自动状态分类

维度: time(时效) / heat(热度) / content(内容) / propagation(传播) / audience(受众)
状态: emerging → rising → hot → cooling → expired
"""
import json, math
from datetime import datetime, timedelta
from appPublic.uniqueID import getID
from sqlor.dbpools import DBPools

def now_str():
    return datetime.now().strftime('%Y-%m-%d %H:%M:%S')

DIM_NAMES = {
    'time': '时效维度',
    'heat': '热度指标',
    'content': '内容属性',
    'propagation': '传播路径',
    'audience': '受众画像',
}

async def analyze_item(item):
    """分析单条热点，返回 (new_status, dimensions_dict, detail)"""
    now = datetime.now()
    try:
        first_seen = datetime.strptime(str(item.get('first_seen', '')), '%Y-%m-%d %H:%M:%S')
    except Exception:
        first_seen = now

    hours_alive = max(0.1, (now - first_seen).total_seconds() / 3600)
    heat = float(item.get('heat_score', 0))
    engagement = int(item.get('engagement_count', 0))
    comments = int(item.get('comment_count', 0))
    shares = int(item.get('share_count', 0))

    # ---- 五维评分 (0-100) ----
    dims = {}

    # 时效: 越新越高
    dims['time'] = 95 if hours_alive < 1 else 85 if hours_alive < 6 else \
                   70 if hours_alive < 24 else 50 if hours_alive < 72 else \
                   30 if hours_alive < 168 else 10

    # 热度: 绝对值
    dims['heat'] = 95 if heat > 1e4 else 85 if heat > 5e3 else \
                   70 if heat > 1e3 else 55 if heat > 500 else \
                   35 if heat > 100 else 15

    # 内容: 标题长度 + 摘要丰富度 + 标签
    title_len = len(item.get('title', ''))
    summary_len = len(item.get('summary', ''))
    dims['content'] = min(100, (20 if title_len > 15 else 10) +
                          (30 if summary_len > 100 else 15) +
                          (25 if item.get('tags') else 0) +
                          (25 if item.get('category') else 0))

    # 传播: 互动总量
    total_eng = engagement + comments * 2 + shares * 3
    dims['propagation'] = 95 if total_eng > 1e4 else 80 if total_eng > 5e3 else \
                          60 if total_eng > 1e3 else 35 if total_eng > 100 else 10

    # 受众: 互动率
    rate = total_eng / heat if heat > 0 else 0
    dims['audience'] = 90 if rate > 0.5 else 70 if rate > 0.2 else \
                       45 if rate > 0.05 else 25 if total_eng > 0 else 5

    # ---- 状态分类 ----
    decay = math.exp(-hours_alive / 168)   # 7天半衰期
    adjusted_heat = heat * decay
    velocity = round(heat / hours_alive, 2)

    if hours_alive > 336:       # >14天
        new_status = 'expired'
    elif hours_alive > 168:     # 7-14天
        new_status = 'cooling'
    elif adjusted_heat > 5000:
        new_status = 'hot'
    elif adjusted_heat > 500:
        new_status = 'rising' if velocity > 50 else 'emerging'
    elif adjusted_heat > 100:
        new_status = 'rising' if velocity > 100 else 'emerging'
    else:
        new_status = 'emerging'

    detail = {
        'hours_alive': round(hours_alive, 1),
        'adjusted_heat': round(adjusted_heat, 2),
        'heat_velocity': velocity,
        'total_engagement': total_eng,
        'decay_factor': round(decay, 4),
    }

    return new_status, dims, detail


async def save_analysis(item_id, dims, detail, now=None):
    """保存/更新五维分析记录"""
    if now is None:
        now = now_str()
    db = DBPools()

    async with db.sqlorContext('sage') as sor:
        for dim, score in dims.items():
            analysis_data = json.dumps({
                'dimension': dim,
                'dimension_cn': DIM_NAMES.get(dim, dim),
                'score': score,
                'detail': detail,
            }, ensure_ascii=False)

            old = await sor.sqlExe(
                "select id from hotspot_analysis where item_id=${iid}$ and dimension=${dim}$",
                {'iid': item_id, 'dim': dim})
            if old:
                await sor.U('hotspot_analysis', {
                    'id': old[0]['id'], 'score': score,
                    'analysis_data': analysis_data, 'analyzed_at': now,
                })
            else:
                await sor.C('hotspot_analysis', {
                    'id': getID(), 'item_id': item_id,
                    'dimension': dim, 'score': score,
                    'analysis_data': analysis_data, 'analyzed_at': now,
                })


async def run_analysis(limit=500):
    """批量分析最近的热点 (默认500条)"""
    db = DBPools()
    now = now_str()
    results = {'analyzed': 0, 'status_changes': 0}

    async with db.sqlorContext('sage') as sor:
        items = await sor.sqlExe(
            "select * from hotspot_item order by first_seen desc limit ${n}$",
            {'n': limit})

    for item in items:
        current_status = item.get('status', 'emerging')
        new_status, dims, detail = await analyze_item(item)

        await save_analysis(item['id'], dims, detail, now)

        if new_status != current_status:
            results['status_changes'] += 1

        async with db.sqlorContext('sage') as sor:
            await sor.U('hotspot_item', {
                'id': item['id'],
                'heat_score': round(detail['adjusted_heat'], 2),
                'heat_velocity': detail['heat_velocity'],
                'status': new_status,
                'last_updated': now,
            })

        results['analyzed'] += 1

    return results