238 lines
8.2 KiB
Python
238 lines
8.2 KiB
Python
#!/usr/bin/env python3
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"""
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使用Tushare直接获取板块数据的测试
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"""
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import sys
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from pathlib import Path
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import pandas as pd
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from datetime import datetime, timedelta
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# 添加项目根目录到路径
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current_dir = Path(__file__).parent
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sys.path.insert(0, str(current_dir))
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from src.data.tushare_fetcher import TushareFetcher
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from loguru import logger
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def get_concept_sectors(fetcher: TushareFetcher):
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"""获取概念板块数据"""
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try:
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if not fetcher.pro:
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logger.error("需要Tushare Pro权限")
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return
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logger.info("尝试获取概念板块数据...")
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# 1. 尝试获取概念板块列表
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try:
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concept_list = fetcher.pro.concept()
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logger.info(f"获取到 {len(concept_list)} 个概念板块")
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if not concept_list.empty:
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print("概念板块列表（前10个）：")
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for _, concept in concept_list.head(10).iterrows():
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print(f" {concept['code']}: {concept['name']}")
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except Exception as e:
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logger.error(f"获取概念板块列表失败: {e}")
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# 2. 尝试获取同花顺概念指数
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try:
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ths_concept = fetcher.pro.ths_index(exchange='A', type='N')
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logger.info(f"获取同花顺概念指数: {len(ths_concept)} 个")
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if not ths_concept.empty:
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print("\n同花顺概念指数（前10个）：")
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for _, index in ths_concept.head(10).iterrows():
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print(f" {index['ts_code']}: {index['name']}")
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except Exception as e:
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logger.error(f"获取同花顺概念指数失败: {e}")
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# 3. 尝试获取行业指数
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try:
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industry_index = fetcher.pro.index_basic(market='SW')
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logger.info(f"获取申万行业指数: {len(industry_index)} 个")
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if not industry_index.empty:
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print("\n申万行业指数（前10个）：")
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for _, index in industry_index.head(10).iterrows():
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print(f" {index['ts_code']}: {index['name']}")
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except Exception as e:
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logger.error(f"获取申万行业指数失败: {e}")
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except Exception as e:
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logger.error(f"获取板块数据失败: {e}")
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def analyze_hot_concepts(fetcher: TushareFetcher):
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"""分析热门概念板块"""
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try:
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if not fetcher.pro:
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logger.error("需要Tushare Pro权限")
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return
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logger.info("分析热门概念板块...")
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# 获取今日涨跌停统计
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today = datetime.now().strftime('%Y%m%d')
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try:
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# 获取涨停股票
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limit_up = fetcher.pro.limit_list(trade_date=today, limit_type='U')
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logger.info(f"今日涨停股票: {len(limit_up)} 只")
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if not limit_up.empty:
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print(f"\n今日涨停股票（前10只）：")
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for _, stock in limit_up.head(10).iterrows():
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print(f" {stock['ts_code']}: {stock['name']} (+{stock['pct_chg']:.2f}%)")
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# 分析涨停股票的行业分布
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if 'industry' in limit_up.columns:
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industry_counts = limit_up['industry'].value_counts()
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print(f"\n涨停股票行业分布：")
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for industry, count in industry_counts.head(5).items():
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print(f" {industry}: {count}只")
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except Exception as e:
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logger.error(f"获取涨停数据失败: {e}")
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# 获取龙虎榜数据
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try:
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top_list = fetcher.pro.top_list(trade_date=today)
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logger.info(f"今日龙虎榜: {len(top_list)} 只股票")
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if not top_list.empty:
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print(f"\n今日龙虎榜股票（前5只）：")
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for _, stock in top_list.head(5).iterrows():
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print(f" {stock['ts_code']}: {stock['name']} 净买入: {stock['amount']:.0f}万元")
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except Exception as e:
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logger.error(f"获取龙虎榜数据失败: {e}")
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except Exception as e:
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logger.error(f"分析热门概念失败: {e}")
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def get_sector_performance_direct(fetcher: TushareFetcher):
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"""直接通过指数数据获取板块表现"""
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try:
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if not fetcher.pro:
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logger.error("需要Tushare Pro权限")
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return
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logger.info("通过指数数据分析板块表现...")
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# 获取申万一级行业指数
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try:
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sw_index = fetcher.pro.index_basic(market='SW', level='L1')
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logger.info(f"获取申万一级行业指数: {len(sw_index)} 个")
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if sw_index.empty:
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logger.warning("未获取到申万行业指数")
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return
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# 获取最近两个交易日的指数行情
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end_date = datetime.now().strftime('%Y%m%d')
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start_date = (datetime.now() - timedelta(days=7)).strftime('%Y%m%d')
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sector_performance = []
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for _, index in sw_index.head(15).iterrows(): # 分析前15个行业
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ts_code = index['ts_code']
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name = index['name']
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try:
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# 获取指数行情
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index_data = fetcher.pro.index_daily(
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ts_code=ts_code,
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start_date=start_date,
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end_date=end_date
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)
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if not index_data.empty and len(index_data) >= 2:
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# 计算涨跌幅
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latest = index_data.iloc[0]
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previous = index_data.iloc[1]
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change_pct = (latest['close'] - previous['close']) / previous['close'] * 100
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sector_performance.append({
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'name': name,
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'code': ts_code,
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'change_pct': change_pct,
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'latest_close': latest['close'],
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'volume': latest['vol']
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})
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logger.debug(f"{name}: {change_pct:+.2f}%")
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except Exception as e:
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logger.debug(f"获取 {name} 指数数据失败: {e}")
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continue
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# 输出结果
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if sector_performance:
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df = pd.DataFrame(sector_performance)
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df = df.sort_values('change_pct', ascending=False)
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print("\n" + "="*60)
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print("📈 申万行业指数表现排行")
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print("="*60)
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print(f"{'排名':<4} {'行业名称':<20} {'涨跌幅':<10} {'最新点位':<10}")
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print("-" * 60)
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for i, (_, row) in enumerate(df.iterrows()):
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rank = i + 1
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name = row['name'][:18] + '..' if len(row['name']) > 18 else row['name']
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change = f"{row['change_pct']:+.2f}%"
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close = f"{row['latest_close']:.2f}"
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print(f"{rank:<4} {name:<20} {change:<10} {close:<10}")
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# 强势行业
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print(f"\n🚀 强势行业TOP5:")
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for _, row in df.head(5).iterrows():
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print(f" {row['name']}: {row['change_pct']:+.2f}%")
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# 弱势行业
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print(f"\n📉 弱势行业TOP5:")
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for _, row in df.tail(5).iterrows():
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print(f" {row['name']}: {row['change_pct']:+.2f}%")
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except Exception as e:
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logger.error(f"获取申万指数失败: {e}")
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except Exception as e:
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logger.error(f"分析板块表现失败: {e}")
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def main():
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"""主函数"""
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logger.info("测试Tushare板块数据接口...")
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# 初始化Tushare数据获取器
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token = "0ed6419a00d8923dc19c0b58fc92d94c9a0696949ab91a13aa58a0cc"
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fetcher = TushareFetcher(token=token)
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# 1. 获取板块分类数据
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get_concept_sectors(fetcher)
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print("\n" + "="*80 + "\n")
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# 2. 分析热门概念
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analyze_hot_concepts(fetcher)
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print("\n" + "="*80 + "\n")
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# 3. 通过指数直接获取板块表现
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get_sector_performance_direct(fetcher)
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logger.info("测试完成!")
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if __name__ == "__main__":
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main() |