oficcejo
182 lines
7.9 KiB
Python
182 lines
7.9 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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主力选股批量分析历史记录UI模块
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"""
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import streamlit as st
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import pandas as pd
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from datetime import datetime
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from main_force_batch_db import batch_db
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def display_batch_history():
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"""显示批量分析历史记录"""
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# 返回按钮
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col_back, col_stats = st.columns([1, 4])
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with col_back:
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if st.button("← 返回主页"):
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st.session_state.main_force_view_history = False
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st.rerun()
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st.markdown("## 📚 主力选股批量分析历史记录")
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st.markdown("---")
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# 获取统计信息
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try:
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stats = batch_db.get_statistics()
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# 显示统计指标
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col1, col2, col3, col4, col5 = st.columns(5)
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with col1:
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st.metric("总记录数", f"{stats['total_records']} 条")
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with col2:
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st.metric("分析股票总数", f"{stats['total_stocks_analyzed']} 只")
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with col3:
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st.metric("成功分析", f"{stats['total_success']} 只")
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with col4:
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st.metric("成功率", f"{stats['success_rate']}%")
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with col5:
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st.metric("平均耗时", f"{stats['average_time']:.1f}秒")
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st.markdown("---")
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except Exception as e:
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st.warning(f"⚠️ 无法获取统计信息: {str(e)}")
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# 获取历史记录
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try:
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history_records = batch_db.get_all_history(limit=50)
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if not history_records:
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st.info("📝 暂无批量分析历史记录")
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return
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st.markdown(f"### 📋 最近 {len(history_records)} 条记录")
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# 显示每条记录
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for idx, record in enumerate(history_records):
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with st.expander(
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f"🔍 {record['analysis_date']} | "
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f"共{record['batch_count']}只 | "
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f"成功{record['success_count']}只 | "
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f"{record['analysis_mode']} | "
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f"耗时{record['total_time']/60:.1f}分钟",
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expanded=(idx == 0) # 第一条默认展开
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):
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# 记录基本信息
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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st.write(f"**分析时间**: {record['analysis_date']}")
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with col2:
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st.write(f"**分析模式**: {record['analysis_mode']}")
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with col3:
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st.write(f"**总数**: {record['batch_count']} 只")
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with col4:
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st.write(f"**耗时**: {record['total_time']/60:.1f} 分钟")
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col5, col6, col7, col8 = st.columns(4)
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with col5:
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st.metric("✅ 成功", record['success_count'])
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with col6:
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st.metric("❌ 失败", record['failed_count'])
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with col7:
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success_rate = (record['success_count'] / record['batch_count'] * 100) if record['batch_count'] > 0 else 0
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st.metric("成功率", f"{success_rate:.1f}%")
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with col8:
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avg_time = record['total_time'] / record['batch_count'] if record['batch_count'] > 0 else 0
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st.metric("平均耗时", f"{avg_time:.1f}秒")
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st.markdown("---")
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# 成功的股票
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results = record.get('results', [])
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success_results = [r for r in results if r.get('success', False)]
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failed_results = [r for r in results if not r.get('success', False)]
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if success_results:
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st.markdown(f"#### ✅ 成功分析的股票 ({len(success_results)} 只)")
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# 构建结果表格
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table_data = []
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for r in success_results:
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stock_info = r.get('stock_info', {})
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final_decision = r.get('final_decision', {})
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table_data.append({
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'代码': r.get('symbol', 'N/A'),
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'名称': stock_info.get('name', stock_info.get('股票名称', 'N/A')),
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'评级': final_decision.get('rating', final_decision.get('investment_rating', 'N/A')),
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'信心度': f"{final_decision.get('confidence_level', 0)}%",
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'进场区间': final_decision.get('entry_range', 'N/A'),
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'止盈位': final_decision.get('take_profit', 'N/A'),
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'止损位': final_decision.get('stop_loss', 'N/A')
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})
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df = pd.DataFrame(table_data)
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st.dataframe(df, use_container_width=True)
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# 显示详细分析（可展开）
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with st.expander("📊 查看详细分析报告"):
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for r in success_results:
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stock_info = r.get('stock_info', {})
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final_decision = r.get('final_decision', {})
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st.markdown(f"### {r.get('symbol', 'N/A')} - {stock_info.get('name', stock_info.get('股票名称', 'N/A'))}")
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# 投资建议
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st.markdown("#### 💡 投资建议")
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st.write(final_decision.get('operation_advice', final_decision.get('investment_advice', '无')))
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# 风险提示
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st.markdown("#### ⚠️ 风险提示")
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st.write(final_decision.get('risk_warning', '无'))
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st.markdown("---")
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# 失败的股票
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if failed_results:
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st.markdown(f"#### ❌ 分析失败的股票 ({len(failed_results)} 只)")
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fail_data = []
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for r in failed_results:
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fail_data.append({
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'代码': r.get('symbol', 'N/A'),
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'错误原因': r.get('error', '未知错误')
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})
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df_fail = pd.DataFrame(fail_data)
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st.dataframe(df_fail, use_container_width=True)
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# 操作按钮
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col_del, col_reload = st.columns([1, 1])
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with col_del:
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if st.button(f"🗑️ 删除此记录", key=f"del_{record['id']}"):
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if batch_db.delete_record(record['id']):
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st.success("✅ 删除成功")
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st.rerun()
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else:
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st.error("❌ 删除失败")
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with col_reload:
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if st.button(f"🔄 加载到当前结果", key=f"reload_{record['id']}"):
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# 将历史记录加载到session_state
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st.session_state.main_force_batch_results = {
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"results": record['results'],
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"total": record['batch_count'],
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"success": record['success_count'],
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"failed": record['failed_count'],
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"elapsed_time": record['total_time'],
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"analysis_mode": record['analysis_mode']
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}
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st.session_state.main_force_view_history = False
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st.success("✅ 已加载到当前结果，返回主页查看")
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st.rerun()
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except Exception as e:
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st.error(f"❌ 获取历史记录失败: {str(e)}")
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import traceback
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st.code(traceback.format_exc())
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