"""
测试A股板块异动监控 - Tushare 版本（详细调试）
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from app.config import get_settings


def test_tushare_detailed():
    """详细测试 Tushare 板块数据"""
    print("=" * 60)
    print("Tushare 板块数据详细测试")
    print("=" * 60)
    print()

    settings = get_settings()
    token = settings.tushare_token

    from app.astock_agent.tushare_client import TushareClient

    ts_client = TushareClient(token=token)

    # 1. 测试获取概念板块列表
    print("1. 获取概念板块列表...")
    sectors_df = ts_client.get_concept_sectors()
    print(f"   ✅ 获取到 {len(sectors_df)} 个概念板块")
    print(f"   示例板块:")
    for idx, row in sectors_df.head(5).iterrows():
        print(f"     - {row['name']}: {row['ts_code']}")
    print()

    # 2. 测试获取单个板块行情
    print("2. 获取单个板块行情（以人工智能为例）...")
    ai_sectors = sectors_df[sectors_df['name'].str.contains('人工智能', na=False)]

    if not ai_sectors.empty:
        ai_code = ai_sectors.iloc[0]['ts_code']
        print(f"   找到人工智能板块: {ai_code}")

        daily_df = ts_client.get_sector_daily(ai_code)
        if not daily_df.empty:
            print(f"   ✅ 获取到 {len(daily_df)} 天行情数据")
            latest = daily_df.sort_values('trade_date').iloc[-1]
            print(f"   最新行情 ({latest['trade_date']}):")
            print(f"     - 收盘价: {latest['close']:.2f}")
            print(f"     - 涨跌幅: {latest.get('pct_chg', 'N/A')}%")
        else:
            print(f"   ❌ 行情数据为空")
    else:
        print(f"   ⚠️ 未找到人工智能板块")
    print()

    # 3. 测试获取板块成分股
    print("3. 获取板块成分股...")
    if not ai_sectors.empty:
        members_df = ts_client.get_sector_members(ai_code)
        if not members_df.empty:
            print(f"   ✅ 获取到 {len(members_df)} 个成分股")
            print(f"   前5个成分股:")
            for idx, row in members_df.head(5).iterrows():
                print(f"     - {row.get('name', row.get('member_name', 'N/A'))}: {row['ts_code']}")
        else:
            print(f"   ❌ 成分股数据为空")
    print()

    # 4. 测试获取异动板块（降低阈值）
    print("4. 检测异动板块（阈值 0%）...")
    hot_df = ts_client.get_hot_sectors(threshold=0.0)

    if hot_df.empty:
        print("   ⚠️ 未检测到上涨的板块")
    else:
        print(f"   ✅ 检测到 {len(hot_df)} 个上涨板块")
        print(f"   涨幅最高的 5 个板块:")
        for idx, row in hot_df.head(5).iterrows():
            print(f"     {idx}. {row['name']}: {row['change_pct']:+.2f}%")
    print()

    print("=" * 60)
    print("测试完成！")
    print("=" * 60)


if __name__ == "__main__":
    test_tushare_detailed()