"""
主力资金流向分析模块（P0）

功能：
1. 从数据库读取近N日资金流向数据
2. 计算主力连续净流入/流出天数、累计净流入额
3. 检测量价背离（资金流入+价格不涨 → 吸筹；资金流出+价格不跌 → 出货）
4. 返回资金面评分和信号列表

数据来源：stock_fund_flow_history 表（由 sync_fund_flow.py 每日同步）
"""
import logging
from datetime import datetime, timedelta

logger = logging.getLogger(__name__)


def get_fund_flow_history(stock_code, days=10):
    """
    从数据库读取近N日资金流向历史数据

    参数:
        stock_code: 股票代码
        days: 获取天数

    返回:
        list[dict]: 每日资金流向记录，按日期升序排列
    """
    from db import get_db, put_db

    conn = get_db()
    if not conn:
        return []

    try:
        cur = conn.cursor()
        start_date = (datetime.now() - timedelta(days=days + 5)).strftime('%Y-%m-%d')
        cur.execute("""
            SELECT trade_date, close_price, change_pct,
                   main_net_inflow, main_net_inflow_pct,
                   super_net_inflow, super_net_inflow_pct,
                   big_net_inflow, big_net_inflow_pct,
                   mid_net_inflow, mid_net_inflow_pct,
                   small_net_inflow, small_net_inflow_pct
            FROM stock_fund_flow_history
            WHERE code = %s AND trade_date >= %s
            ORDER BY trade_date ASC
        """, (stock_code, start_date))
        rows = cur.fetchall()

        records = []
        for row in rows:
            records.append({
                'date': row[0].strftime('%Y-%m-%d') if row[0] else '',
                'close_price': float(row[1] or 0),
                'change_pct': float(row[2] or 0),
                'main_net_inflow': float(row[3] or 0),
                'main_net_inflow_pct': float(row[4] or 0),
                'super_net_inflow': float(row[5] or 0),
                'super_net_inflow_pct': float(row[6] or 0),
                'big_net_inflow': float(row[7] or 0),
                'big_net_inflow_pct': float(row[8] or 0),
                'mid_net_inflow': float(row[9] or 0),
                'mid_net_inflow_pct': float(row[10] or 0),
                'small_net_inflow': float(row[11] or 0),
                'small_net_inflow_pct': float(row[12] or 0),
            })
        return records
    except Exception as e:
        logger.error(f"获取资金流向历史失败({stock_code}): {e}")
        return []
    finally:
        put_db(conn)


def _get_fund_flow_from_mairui(stock_code, days=10):
    """从麦蕊智数API获取资金流向数据，转换为与DB记录相同的格式。

    API: https://api.mairuiapi.com/hsstock/history/transaction/{code}/{licence}?lt={n}
    字段: zmbtdcje=主买特大单, zmbddcje=主买大单, zmbzdcje=主买中单, zmbxdcje=主买小单
          zmstdcje=主卖特大单, zmsddcje=主卖大单, zmszdcje=主卖中单, zmsxdcje=主卖小单
    """
    try:
        import requests
        from config import Config
        LICENCE = Config.MAIRUI_LICENCE or "5352ED2F-94E5-4E96-8B7F-B57BA75284E3"
        url = f"https://api.mairuiapi.com/hsstock/history/transaction/{stock_code}/{LICENCE}?lt={days}"
        resp = requests.get(url, timeout=10)
        if resp.status_code != 200:
            logger.warning(f"麦蕊资金流向API返回{resp.status_code}")
            return []

        data = resp.json()
        if not data or not isinstance(data, list):
            return []

        records = []
        for item in data:
            # 主买总额 = 特大单+大单+中单+小单
            buy_total = (
                float(item.get('zmbtdcje', 0) or 0) +
                float(item.get('zmbddcje', 0) or 0) +
                float(item.get('zmbzdcje', 0) or 0) +
                float(item.get('zmbxdcje', 0) or 0)
            )
            # 主卖总额
            sell_total = (
                float(item.get('zmstdcje', 0) or 0) +
                float(item.get('zmsddcje', 0) or 0) +
                float(item.get('zmszdcje', 0) or 0) +
                float(item.get('zmsxdcje', 0) or 0)
            )
            # 主力净流入 = (特大单+大单)买 - (特大单+大单)卖
            main_buy = float(item.get('zmbtdcje', 0) or 0) + float(item.get('zmbddcje', 0) or 0)
            main_sell = float(item.get('zmstdcje', 0) or 0) + float(item.get('zmsddcje', 0) or 0)
            main_net = main_buy - main_sell

            # 超大单净流入
            super_net = float(item.get('zmbtdcje', 0) or 0) - float(item.get('zmstdcje', 0) or 0)

            # 总成交额
            total_amount = buy_total + sell_total
            main_net_pct = round(main_net / total_amount * 100, 2) if total_amount > 0 else 0
            super_net_pct = round(super_net / total_amount * 100, 2) if total_amount > 0 else 0

            # 大单净流入
            big_net = float(item.get('zmbddcje', 0) or 0) - float(item.get('zmsddcje', 0) or 0)
            big_net_pct = round(big_net / total_amount * 100, 2) if total_amount > 0 else 0

            # 中单净流入
            mid_net = float(item.get('zmbzdcje', 0) or 0) - float(item.get('zmszdcje', 0) or 0)
            mid_net_pct = round(mid_net / total_amount * 100, 2) if total_amount > 0 else 0

            # 小单净流入
            small_net = float(item.get('zmbxdcje', 0) or 0) - float(item.get('zmsxdcje', 0) or 0)
            small_net_pct = round(small_net / total_amount * 100, 2) if total_amount > 0 else 0

            # 日期解析
            t_str = str(item.get('t', ''))
            date_str = t_str[:10] if t_str else ''

            records.append({
                'date': date_str,
                'close_price': 0,
                'change_pct': 0,
                'main_net_inflow': round(main_net, 2),
                'main_net_inflow_pct': main_net_pct,
                'super_net_inflow': round(super_net, 2),
                'super_net_inflow_pct': super_net_pct,
                'big_net_inflow': round(big_net, 2),
                'big_net_inflow_pct': big_net_pct,
                'mid_net_inflow': round(mid_net, 2),
                'mid_net_inflow_pct': mid_net_pct,
                'small_net_inflow': round(small_net, 2),
                'small_net_inflow_pct': small_net_pct,
            })

        # 按日期升序排列
        records.sort(key=lambda x: x['date'])
        logger.info(f"麦蕊API获取{stock_code}资金流向{len(records)}条")
        return records
    except Exception as e:
        logger.warning(f"麦蕊资金流向API失败({stock_code}): {e}")
        return []


def analyze_fund_flow(stock_code, days=5):
    """
    分析主力资金流向，返回资金面评分和信号

    数据源优先级：
    1. DB stock_fund_flow_history 表（有最新数据时）
    2. 麦蕊智数API hsstock/history/transaction（DB数据过期时补充）

    参数:
        stock_code: 股票代码
        days: 分析最近几天的资金流向

    返回:
        dict: {
            'score': int,          # 资金面评分增减（-20 ~ +20）
            'signals': list,       # 资金信号列表
            'summary': str,        # 白话总结
            'details': dict,       # 详细数据
            'reasons': list,       # 评分原因列表
        }
    """
    records = get_fund_flow_history(stock_code, days=days + 5)

    # 检查DB数据是否足够新（最近3天内有数据）
    use_mairui = False
    if len(records) < 2:
        use_mairui = True
    else:
        from datetime import date
        latest_date = records[-1].get('date', '')
        if latest_date:
            try:
                latest = datetime.strptime(latest_date, '%Y-%m-%d').date()
                if (date.today() - latest).days > 5:
                    use_mairui = True
            except ValueError:
                use_mairui = True

    if use_mairui:
        # 用麦蕊API获取资金流向数据
        mairui_records = _get_fund_flow_from_mairui(stock_code, days + 5)
        if mairui_records:
            records = mairui_records

    if len(records) < 2:
        return {
            'score': 0,
            'signals': [],
            'summary': '暂无资金流向数据',
            'details': {},
            'reasons': [],
        }

    recent = records[-days:] if len(records) >= days else records

    # 计算连续净流入/流出天数
    consecutive_inflow = 0
    consecutive_outflow = 0
    for r in reversed(recent):
        if r['main_net_inflow'] > 0:
            if consecutive_outflow > 0:
                break
            consecutive_inflow += 1
        elif r['main_net_inflow'] < 0:
            if consecutive_inflow > 0:
                break
            consecutive_outflow += 1

    # 累计净流入
    total_main_inflow = sum(r['main_net_inflow'] for r in recent)
    avg_main_pct = sum(r['main_net_inflow_pct'] for r in recent) / len(recent) if recent else 0

    # 超大单累计
    total_super_inflow = sum(r['super_net_inflow'] for r in recent)
    avg_super_pct = sum(r['super_net_inflow_pct'] for r in recent) / len(recent) if recent else 0

    # 量价背离检测
    # 吸筹：主力净流入但价格不涨（涨幅<2%）
    # 出货：主力净流出但价格不跌（跌幅<2%）
    accumulation = False
    distribution = False
    if total_main_inflow > 0:
        price_changes = [r['change_pct'] for r in recent]
        avg_price_change = sum(price_changes) / len(price_changes) if price_changes else 0
        if avg_price_change < 2:
            accumulation = True

    if total_main_inflow < 0:
        price_changes = [r['change_pct'] for r in recent]
        avg_price_change = sum(price_changes) / len(price_changes) if price_changes else 0
        if avg_price_change > -2:
            distribution = True

    # 单日超大单突击
    big_surge = False
    big_surge_day = None
    for r in recent:
        if r['super_net_inflow_pct'] > 15:
            big_surge = True
            big_surge_day = r['date']
            break

    # 评分计算
    score = 0
    reasons = []
    signals = []

    if consecutive_inflow >= 3:
        score += 10
        reasons.append(f'主力连续{consecutive_inflow}日净流入(+10)')
        signals.append({
            'type': 'fund_continuous_inflow',
            'name': '主力持续流入',
            'direction': 'buy',
            'strength': 80,
            'description': f'主力资金连续{consecutive_inflow}日净流入，累计{total_main_inflow/10000:.0f}万元',
        })

    if consecutive_outflow >= 3:
        score -= 10
        reasons.append(f'主力连续{consecutive_outflow}日净流出(-10)')
        signals.append({
            'type': 'fund_continuous_outflow',
            'name': '主力持续流出',
            'direction': 'sell',
            'strength': 75,
            'description': f'主力资金连续{consecutive_outflow}日净流出，累计{total_main_inflow/10000:.0f}万元',
        })

    if accumulation:
        score += 8
        reasons.append('主力暗中吸筹(+8)')
        signals.append({
            'type': 'fund_accumulation',
            'name': '主力吸筹',
            'direction': 'buy',
            'strength': 85,
            'description': f'主力净流入但价格未涨，暗中吸筹，可能即将拉升',
        })

    if distribution:
        score -= 8
        reasons.append('主力暗中出货(-8)')
        signals.append({
            'type': 'fund_distribution',
            'name': '主力出货',
            'direction': 'sell',
            'strength': 80,
            'description': f'主力净流出但价格未跌，暗中出货，需警惕',
        })

    if big_surge:
        score += 5
        reasons.append(f'超大单突击流入({big_surge_day})(+5)')
        signals.append({
            'type': 'fund_big_surge',
            'name': '大单突击',
            'direction': 'buy',
            'strength': 70,
            'description': f'{big_surge_day}超大单净流入占比>15%，大机构突击入场',
        })

    # 主力净流入占比评分
    if avg_main_pct > 10:
        score += 5
        reasons.append(f'主力净流入占比{avg_main_pct:.1f}%(+5)')
    elif avg_main_pct < -10:
        score -= 5
        reasons.append(f'主力净流出占比{abs(avg_main_pct):.1f}%(-5)')

    score = max(-20, min(20, score))

    # 白话总结
    summary_parts = []
    if consecutive_inflow >= 3:
        summary_parts.append(f'近{consecutive_inflow}天主力持续买入，累计流入{total_main_inflow/10000:.0f}万元')
    elif consecutive_outflow >= 3:
        summary_parts.append(f'近{consecutive_outflow}天主力持续卖出，累计流出{abs(total_main_inflow)/10000:.0f}万元')
    elif total_main_inflow > 0:
        summary_parts.append(f'近期主力总体净流入{total_main_inflow/10000:.0f}万元')
    elif total_main_inflow < 0:
        summary_parts.append(f'近期主力总体净流出{abs(total_main_inflow)/10000:.0f}万元')

    if accumulation:
        summary_parts.append('但价格没怎么涨，像是在暗中吸筹')
    if distribution:
        summary_parts.append('但价格没怎么跌，像是在暗中出货，要小心')

    summary = '，'.join(summary_parts) if summary_parts else '资金面无明显方向'

    return {
        'score': score,
        'signals': signals,
        'summary': summary,
        'details': {
            'consecutive_inflow': consecutive_inflow,
            'consecutive_outflow': consecutive_outflow,
            'total_main_inflow': round(total_main_inflow, 2),
            'avg_main_pct': round(avg_main_pct, 2),
            'total_super_inflow': round(total_super_inflow, 2),
            'avg_super_pct': round(avg_super_pct, 2),
            'accumulation': accumulation,
            'distribution': distribution,
            'recent_days': len(recent),
            'daily_data': recent,
        },
        'reasons': reasons,
    }