#!/usr/bin/env python3
"""
诊断板块资金异动检测
检查为什么没有找到异动板块
"""
import asyncio
import sys
import os
from datetime import datetime, timedelta

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from app.utils.logger import logger
from app.config import get_settings
from app.astock_agent.tushare_client import get_tushare_client


async def diagnose_sector_detection():
    """诊断板块检测"""
    print("\n" + "=" * 80)
    print("🔍 板块资金异动诊断")
    print("=" * 80)

    settings = get_settings()
    ts_client = get_tushare_client(settings.tushare_token)

    # 获取热门概念板块
    print("\n【第一步】获取热门概念板块...")
    hot_concept_sectors = [
        '人工智能', '新能源汽车', '芯片', '半导体', '5G',
        '智能电网', '物联网', '云计算', '大数据', '区块链'
    ]

    sectors_df = ts_client.get_concept_sectors()

    # 找到热门板块
    hot_sectors_codes = []
    for hot_name in hot_concept_sectors:
        matches = sectors_df[sectors_df['name'].str.contains(hot_name, na=False)]
        if not matches.empty:
            for _, row in matches.iterrows():
                hot_sectors_codes.append({
                    'ts_code': row['ts_code'],
                    'name': row['name']
                })

    print(f"✓ 找到 {len(hot_sectors_codes)} 个热门板块")

    # 检查这些板块的资金异动
    print("\n【第二步】检查板块资金异动（量比、额比、涨幅）...")
    print("=" * 80)

    today = datetime.now().strftime('%Y%m%d')
    yesterday = (datetime.now() - timedelta(days=10)).strftime('%Y%m%d')

    # 宽松模式的阈值
    vol_threshold = 1.5
    amount_threshold = 1.3
    min_change = 0.5

    qualified_sectors = []

    for sector_info in hot_sectors_codes[:15]:  # 只检查前15个
        ts_code = sector_info['ts_code']
        name = sector_info['name']

        try:
            daily_df = ts_client.pro.ths_daily(
                ts_code=ts_code,
                start_date=yesterday,
                end_date=today
            )

            if daily_df.empty or len(daily_df) < 2:
                print(f"  ⚠️  {name}: 数据不足")
                continue

            daily_df = daily_df.sort_values('trade_date')
            latest = daily_df.iloc[-1]
            prev = daily_df.iloc[-2]

            latest_vol = float(latest.get('vol', 0))
            latest_avg_price = float(latest.get('avg_price', 0))
            latest_amount = latest_vol * latest_avg_price * 100  # 估算成交额

            prev_vol = float(prev.get('vol', 0))
            prev_avg_price = float(prev.get('avg_price', 0))
            prev_amount = prev_vol * prev_avg_price * 100
            change_pct = float(latest.get('pct_change', 0))

            # 计算量比和额比
            vol_ratio = latest_vol / prev_vol if prev_vol > 0 else 0
            amount_ratio = latest_amount / prev_amount if prev_amount > 0 else 0

            # 判断是否符合条件
            is_volume_surge = vol_ratio >= vol_threshold
            is_amount_surge = amount_ratio >= amount_threshold
            has_min_change = change_pct >= min_change
            is_qualified = (is_volume_surge or is_amount_surge) and has_min_change

            # 显示结果
            status = "✅" if is_qualified else "❌"
            vol_status = "🔥" if is_volume_surge else "📊"
            amount_status = "🔥" if is_amount_surge else "📊"
            change_status = "✓" if has_min_change else "✗"

            print(f"  {status} {name}")
            print(f"      涨跌幅: {change_pct:+.2f}% {change_status}")
            print(f"      量比: {vol_ratio:.2f}x {vol_status} (需要≥{vol_threshold})")
            print(f"      额比: {amount_ratio:.2f}x {amount_status} (需要≥{amount_threshold})")

            if is_qualified:
                qualified_sectors.append({
                    'name': name,
                    'change_pct': change_pct,
                    'vol_ratio': vol_ratio,
                    'amount_ratio': amount_ratio
                })

        except Exception as e:
            print(f"  ❌ {name}: 查询失败 ({e})")
            continue

    print("\n" + "=" * 80)
    print(f"【结果】找到 {len(qualified_sectors)} 个符合资金异动条件的板块")

    if len(qualified_sectors) == 0:
        print("\n⚠️  没有板块符合条件，可能原因：")
        print("  1. 市场整体资金流入不足（量比、额比都未达标）")
        print("  2. 板块涨幅不够（需要≥0.5%）")
        print("  3. 阈值设置过高（当前：量比≥1.5，额比≥1.3）")
        print("\n建议放宽阈值：")
        print("  - 量比阈值: 1.5 → 1.2")
        print("  - 额比阈值: 1.3 → 1.1")
        print("  - 最小涨幅: 0.5% → 0.3%")
    else:
        print("\n✅ 符合条件的板块：")
        for idx, sector in enumerate(qualified_sectors, 1):
            print(f"  {idx}. {sector['name']}: {sector['change_pct']:+.2f}%, "
                  f"量比{sector['vol_ratio']:.2f}x, 额比{sector['amount_ratio']:.2f}x")

    print("=" * 80)


async def main():
    await diagnose_sector_detection()


if __name__ == "__main__":
    asyncio.run(main())