201 lines
6.9 KiB
Python
201 lines
6.9 KiB
Python
"""
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板块异动分析
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检测板块涨跌幅、量能、资金流向异动
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"""
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import pandas as pd
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from typing import Dict, List, Optional, Tuple
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from datetime import datetime
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from app.utils.logger import logger
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from app.utils.error_handler import notify_error
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from .akshare_client import get_akshare_client
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class SectorChangeAnalyzer:
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"""板块异动分析器"""
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def __init__(self, change_threshold: float = 2.0):
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"""
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初始化异动分析器
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Args:
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change_threshold: 涨跌幅阈值（%）
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"""
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self.change_threshold = change_threshold
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self.akshare = get_akshare_client()
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def detect_sector_changes(self) -> List[Dict]:
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"""
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检测异动板块（使用概念板块）
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Returns:
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异动板块列表
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"""
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try:
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# 获取概念板块行情
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df = self.akshare.get_concept_spot()
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if df.empty:
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logger.warning("概念板块行情数据为空")
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return []
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# 转换数据类型（概念板块返回的列名）
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df['涨跌幅'] = pd.to_numeric(df['涨跌幅'], errors='coerce')
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df['涨跌额'] = pd.to_numeric(df['涨跌额'], errors='coerce')
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df['最新价'] = pd.to_numeric(df['最新价'], errors='coerce')
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df['成交额'] = pd.to_numeric(df['成交额'], errors='coerce')
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# 筛选异动板块
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hot_sectors = df[df['涨跌幅'] >= self.change_threshold].copy()
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if hot_sectors.empty:
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return []
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# 排序：涨幅优先，然后成交额
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hot_sectors = hot_sectors.sort_values(
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by=['涨跌幅', '成交额'],
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ascending=[False, False]
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)
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# 转换为结果列表
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results = []
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for _, row in hot_sectors.iterrows():
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results.append({
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'name': row['板块名称'],
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'change_pct': float(row['涨跌幅']),
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'change_amount': float(row.get('涨跌额', 0)),
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'volume': float(row.get('成交量', 0)) if '成交量' in row else 0.0,
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'amount': float(row.get('成交额', 0)),
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'leading_stock': row.get('领涨股', ''),
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'ups': int(row.get('上涨家数', 0)),
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'downs': int(row.get('下跌家数', 0)),
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'timestamp': datetime.now()
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})
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logger.info(f"检测到 {len(results)} 个异动概念板块")
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return results
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except Exception as e:
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error_msg = f"检测板块异动失败: {e}"
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logger.error(error_msg)
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# 如果是连接错误，发送通知
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if 'Connection' in str(e) or 'RemoteDisconnected' in str(e):
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notify_error(
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title="A股板块监控 - 数据源连接失败",
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message=f"akshare 概念板块 API 连接失败\n\n错误: {e}\n\n可能原因：\n- eastmoney API 服务不稳定\n- 网络连接问题\n- 建议：稍后自动重试或考虑使用 tushare",
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level="warning"
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)
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return []
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def analyze_sector_momentum(self, sector_name: str) -> Dict:
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"""
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分析板块动能
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Args:
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sector_name: 板块名称
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Returns:
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板块动能分析结果
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"""
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try:
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# 获取板块成分股
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stocks_df = self.akshare.get_concept_stocks(sector_name)
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if stocks_df.empty:
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return {}
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# 获取实时行情
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spot_df = self.akshare.get_stock_spot()
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if spot_df.empty:
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return {}
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# 合并数据
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merged = pd.merge(
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stocks_df,
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spot_df,
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on='代码',
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how='inner'
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)
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if merged.empty:
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return {}
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# 计算统计
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total_stocks = len(merged)
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up_stocks = len(merged[merged['涨跌幅'] > 0])
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down_stocks = len(merged[merged['涨跌幅'] < 0])
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avg_change = merged['涨跌幅'].mean()
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max_change = merged['涨跌幅'].max()
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# 计算总成交额
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total_amount = merged['成交额'].sum() if '成交额' in merged.columns else 0
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# 找出涨幅最大的股票
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if not merged.empty:
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top_stock = merged.loc[merged['涨跌幅'].idxmax()]
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else:
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top_stock = None
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return {
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'sector_name': sector_name,
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'total_stocks': total_stocks,
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'up_stocks': up_stocks,
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'down_stocks': down_stocks,
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'up_down_ratio': f"{up_stocks}:{down_stocks}",
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'avg_change': float(avg_change) if pd.notna(avg_change) else 0,
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'max_change': float(max_change) if pd.notna(max_change) else 0,
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'total_amount': float(total_amount),
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'top_stock': {
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'code': top_stock['代码'] if top_stock is not None else '',
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'name': top_stock['名称'] if top_stock is not None else '',
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'change': float(top_stock['涨跌幅']) if top_stock is not None else 0,
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} if top_stock is not None else None
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}
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except Exception as e:
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logger.error(f"分析板块动能失败 {sector_name}: {e}")
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return {}
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def get_hot_reason(self, sector_name: str, top_stocks: List[Dict]) -> str:
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"""
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推测异动原因（基于龙头股分析）
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Args:
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sector_name: 板块名称
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top_stocks: 龙头股列表
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Returns:
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异动原因描述
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"""
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try:
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if not top_stocks:
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return "板块整体异动"
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# 简单的原因分析
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reasons = []
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# 检查是否有涨停股
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limit_up_count = sum(1 for s in top_stocks if s.get('change_pct', 0) >= 9.9)
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if limit_up_count > 0:
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reasons.append(f"{limit_up_count}只个股涨停")
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# 检查平均涨幅
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avg_change = sum(s.get('change_pct', 0) for s in top_stocks) / len(top_stocks)
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if avg_change >= 7:
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reasons.append("板块全线爆发")
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# 检查是否集中在某个龙头
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if len(top_stocks) >= 2:
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top1_change = top_stocks[0].get('change_pct', 0)
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top2_change = top_stocks[1].get('change_pct', 0)
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if top1_change - top2_change > 3:
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reasons.append(f"{top_stocks[0].get('name', '')}龙头领涨")
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if reasons:
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return "，".join(reasons)
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else:
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return "资金集中流入"
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except Exception as e:
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logger.error(f"推测异动原因失败: {e}")
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return "板块异动"
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