318 lines
12 KiB
Python
318 lines
12 KiB
Python
#!/usr/bin/env python3
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"""
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测试同花顺概念板块数据
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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 explore_ths_interfaces(fetcher: TushareFetcher):
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"""探索同花顺相关接口"""
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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("🔍 探索同花顺概念板块相关接口...")
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# 1. 获取同花顺概念指数列表
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try:
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logger.info("1. 获取同花顺概念指数列表...")
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ths_index = fetcher.pro.ths_index(exchange='A', type='N')
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logger.info(f"获取到 {len(ths_index)} 个同花顺概念指数")
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if not ths_index.empty:
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print("\n📋 同花顺概念指数（前20个）：")
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print(f"{'代码':<15} {'名称':<30} {'发布日期':<12}")
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print("-" * 60)
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for _, index in ths_index.head(20).iterrows():
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code = index['ts_code']
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name = index['name'][:28] + '..' if len(index['name']) > 28 else index['name']
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pub_date = index.get('list_date', 'N/A')
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print(f"{code:<15} {name:<30} {pub_date:<12}")
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return ths_index
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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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# 2. 尝试获取同花顺概念成分股
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try:
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logger.info("\n2. 测试获取同花顺概念成分股...")
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# 尝试获取一个概念的成分股
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sample_concept = "885311.TI" # 智能电网
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ths_member = fetcher.pro.ths_member(ts_code=sample_concept)
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logger.info(f"获取智能电网概念成分股: {len(ths_member)} 只")
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if not ths_member.empty:
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print(f"\n📊 智能电网概念成分股（前10只）：")
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for _, stock in ths_member.head(10).iterrows():
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print(f" {stock['code']}: {stock.get('name', 'N/A')}")
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except Exception as e:
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logger.error(f"获取同花顺概念成分股失败: {e}")
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# 3. 尝试获取同花顺概念日行情
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try:
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logger.info("\n3. 测试获取同花顺概念日行情...")
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today = datetime.now().strftime('%Y%m%d')
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yesterday = (datetime.now() - timedelta(days=1)).strftime('%Y%m%d')
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ths_daily = fetcher.pro.ths_daily(
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ts_code="885311.TI", # 智能电网
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start_date=yesterday,
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end_date=today
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)
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logger.info(f"获取智能电网概念日行情: {len(ths_daily)} 条记录")
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if not ths_daily.empty:
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print(f"\n📈 智能电网概念近期行情：")
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print(ths_daily[['trade_date', 'close', 'pct_chg', 'vol']].head())
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except Exception as e:
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logger.error(f"获取同花顺概念日行情失败: {e}")
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# 4. 探索其他可能的同花顺接口
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try:
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logger.info("\n4. 探索同花顺行业分类...")
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ths_industry = fetcher.pro.ths_index(exchange='A', type='I')
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logger.info(f"获取到 {len(ths_industry)} 个同花顺行业指数")
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if not ths_industry.empty:
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print(f"\n📊 同花顺行业指数（前10个）：")
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for _, index in ths_industry.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"获取同花顺行业分类失败: {e}")
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except Exception as e:
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logger.error(f"探索同花顺接口失败: {e}")
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def get_ths_concept_7day_ranking(fetcher: TushareFetcher):
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"""获取同花顺概念板块过去7个交易日排名"""
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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("📊 计算同花顺概念板块过去7个交易日涨幅...")
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# 获取同花顺概念指数列表
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ths_concepts = fetcher.pro.ths_index(exchange='A', type='N')
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if ths_concepts.empty:
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logger.error("未获取到同花顺概念指数")
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return
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# 过滤掉指数型板块，只保留真正的概念板块
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logger.info("过滤指数型板块...")
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index_keywords = [
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'成份股', '样本股', '成分股', '50', '100', '300', '500', '1000',
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'上证', '深证', '中证', '创业板', '科创板', '北证',
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'ETF', '指数', 'Index', '基准'
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]
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def is_concept_plate(name: str) -> bool:
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"""判断是否为真正的概念板块"""
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name_lower = name.lower()
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for keyword in index_keywords:
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if keyword.lower() in name_lower:
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return False
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return True
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# 过滤数据
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original_count = len(ths_concepts)
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ths_concepts = ths_concepts[ths_concepts['name'].apply(is_concept_plate)]
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filtered_count = len(ths_concepts)
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logger.info(f"过滤结果: {original_count} -> {filtered_count} 个概念板块（剔除{original_count - filtered_count}个指数型板块）")
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# 获取过去7个交易日
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trading_dates = []
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current = datetime.now()
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while len(trading_dates) < 7:
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if current.weekday() < 5: # 周一到周五
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trading_dates.append(current.strftime('%Y%m%d'))
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current -= timedelta(days=1)
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trading_dates.reverse() # 升序排列，最早的日期在前
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if len(trading_dates) < 2:
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logger.warning("交易日不足")
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return
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start_date = trading_dates[0] # 7个交易日前
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end_date = trading_dates[-1] # 最新交易日
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logger.info(f"分析周期: {start_date} 到 {end_date} (过去7个交易日)")
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# 计算各概念的7日涨幅
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concept_performance = []
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# 限制分析数量，避免API调用过多
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sample_concepts = ths_concepts.head(50) # 分析前50个概念（过滤后数量减少）
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logger.info(f"分析前 {len(sample_concepts)} 个同花顺概念...")
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for _, concept in sample_concepts.iterrows():
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ts_code = concept['ts_code']
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name = concept['name']
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try:
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# 获取过去7个交易日行情数据
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daily_data = fetcher.pro.ths_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 daily_data.empty:
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# 检查数据结构
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logger.debug(f"{name} 数据字段: {list(daily_data.columns)}")
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if len(daily_data) >= 2:
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# 按日期排序
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daily_data = daily_data.sort_values('trade_date')
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start_close = daily_data.iloc[0]['close']
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end_close = daily_data.iloc[-1]['close']
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if start_close > 0:
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period_change = (end_close - start_close) / start_close * 100
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# 检查涨跌幅字段名
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pct_change_col = None
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for col in ['pct_chg', 'pct_change', 'change']:
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if col in daily_data.columns:
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pct_change_col = col
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break
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latest_daily_change = daily_data.iloc[-1][pct_change_col] if pct_change_col else 0
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concept_performance.append({
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'ts_code': ts_code,
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'name': name,
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'period_change': period_change,
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'start_close': start_close,
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'end_close': end_close,
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'latest_daily_change': latest_daily_change,
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'trading_days': len(daily_data)
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})
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logger.debug(f"{name}: 过去7日{period_change:+.2f}%")
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except Exception as e:
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logger.debug(f"获取 {name} 数据失败: {e}")
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continue
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# 显示结果
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if concept_performance:
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df_ths = pd.DataFrame(concept_performance)
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df_ths = df_ths.sort_values('period_change', ascending=False)
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print(f"\n" + "="*80)
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print("📈 同花顺概念板块过去7个交易日涨幅排行榜")
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print("="*80)
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print(f"{'排名':<4} {'概念名称':<30} {'7日涨幅':<12} {'今日涨幅':<12} {'指数代码':<15}")
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print("-" * 80)
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for i, (_, concept) in enumerate(df_ths.iterrows()):
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rank = i + 1
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name = concept['name'][:28] + '..' if len(concept['name']) > 28 else concept['name']
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period_chg = f"{concept['period_change']:+.2f}%"
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daily_chg = f"{concept['latest_daily_change']:+.2f}%"
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ts_code = concept['ts_code']
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print(f"{rank:<4} {name:<30} {period_chg:<12} {daily_chg:<12} {ts_code:<15}")
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# 强势概念TOP15
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print(f"\n🚀 同花顺强势概念TOP15:")
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for i, (_, concept) in enumerate(df_ths.head(15).iterrows()):
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print(f" {i+1:2d}. {concept['name']}: {concept['period_change']:+.2f}%")
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# 弱势概念TOP10
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print(f"\n📉 同花顺弱势概念TOP10:")
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weak_concepts = df_ths.tail(10).iloc[::-1] # 反转顺序
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for i, (_, concept) in enumerate(weak_concepts.iterrows()):
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print(f" {i+1:2d}. {concept['name']}: {concept['period_change']:+.2f}%")
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return df_ths
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else:
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logger.warning("未能计算同花顺概念涨幅")
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except Exception as e:
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logger.error(f"获取同花顺概念排名失败: {e}")
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def compare_concept_sources(fetcher: TushareFetcher):
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"""对比东财和同花顺概念数据"""
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try:
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logger.info("📊 对比东财 vs 同花顺概念数据...")
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# 获取东财概念数量
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today = datetime.now().strftime('%Y%m%d')
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dc_concepts = fetcher.pro.dc_index(trade_date=today)
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dc_count = len(dc_concepts) if not dc_concepts.empty else 0
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# 获取同花顺概念数量
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ths_concepts = fetcher.pro.ths_index(exchange='A', type='N')
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ths_count = len(ths_concepts) if not ths_concepts.empty else 0
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print(f"\n📊 概念板块数据源对比:")
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print(f" 东财概念板块: {dc_count} 个")
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print(f" 同花顺概念: {ths_count} 个")
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# 数据特点对比
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print(f"\n📈 数据特点对比:")
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print(f" 东财概念:")
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print(f" - 更新频率: 每日更新")
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print(f" - 数据字段: 涨跌幅、市值、上涨下跌股数等")
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print(f" - 适用场景: 实时概念轮动分析")
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print(f" 同花顺概念:")
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print(f" - 更新频率: 每日更新")
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print(f" - 数据字段: 指数价格、涨跌幅、成交量等")
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print(f" - 适用场景: 概念指数走势分析")
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except Exception as e:
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logger.error(f"对比概念数据源失败: {e}")
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def main():
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"""主函数"""
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logger.info("🚀 开始探索同花顺概念板块数据...")
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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. 探索同花顺接口
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ths_index = explore_ths_interfaces(fetcher)
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print("\n" + "="*80 + "\n")
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# 2. 计算同花顺概念过去7个交易日排名
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get_ths_concept_7day_ranking(fetcher)
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print("\n" + "="*80 + "\n")
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# 3. 对比数据源
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compare_concept_sources(fetcher)
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logger.info("✅ 探索完成!")
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if __name__ == "__main__":
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main() |