增加选股策略
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oficcejo
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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小市值策略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 small_cap_selector import small_cap_selector
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from notification_service import notification_service
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from low_price_bull_monitor import low_price_bull_monitor
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from low_price_bull_service import low_price_bull_service
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def display_small_cap():
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"""显示小市值策略界面"""
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# 检查是否显示监控面板
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if st.session_state.get('show_small_cap_monitor'):
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from low_price_bull_monitor_ui import display_monitor_panel
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display_monitor_panel()
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# 返回按钮
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if st.button("🔙 返回选股", type="secondary"):
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del st.session_state.show_small_cap_monitor
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st.rerun()
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return
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st.markdown("顶部按钮区")
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col_select, col_monitor = st.columns([3, 1])
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with col_select:
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st.markdown("## 📊 小市值策略 - 小盘高成长股票筛选")
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with col_monitor:
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st.write("") # 占位
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if st.button("📊 策略监控", type="primary", use_container_width=True):
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st.session_state.show_small_cap_monitor = True
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st.rerun()
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st.markdown("---")
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st.markdown("""
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### 📋 选股策略说明
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**筛选条件**：
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- ✅ 总市值 ≤ 50亿
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- ✅ 营收增长率 ≥ 10%
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- ✅ 净利润增长率 ≥ 100%（净利润同比增长率）
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- ✅ 沪深A股
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- ✅ 非ST股票
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- ✅ 非创业板
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- ✅ 非科创板
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- ✅ 按总市值由小至大排名
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**量化交易策略**：
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- 💰 资金量：10万元
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- 📅 持股周期：5天
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- 💼 仓位控制：满仓
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- 📊 个股最大持仓：3成（30%）
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- 🎯 账户最大持股数：4只
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- 🛒 单日最大买入数：2只
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- 📈 买入时机：开盘买入
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- 📉 卖出时机：MA5下穿MA20或持股满5天
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""")
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st.markdown("---")
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# 参数设置
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col1, col2 = st.columns([2, 1])
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with col1:
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top_n = st.slider(
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"筛选数量",
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min_value=3,
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max_value=10,
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value=5,
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step=1,
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help="选择展示的股票数量"
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)
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with col2:
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st.info(f"💡 将筛选市值最小的前{top_n}只股票")
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st.markdown("---")
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# 开始选股按钮
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if st.button("🚀 开始小市值策略选股", type="primary", use_container_width=True):
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with st.spinner("正在获取数据，请稍候..."):
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# 创建选股器
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success, stocks_df, message = small_cap_selector.get_small_cap_stocks(top_n)
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if not success:
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st.error(f"❌ {message}")
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return
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st.success(f"✅ {message}")
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# 保存到session_state
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st.session_state.small_cap_stocks = stocks_df
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st.session_state.small_cap_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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# 显示选股结果
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if 'small_cap_stocks' in st.session_state and st.session_state.small_cap_stocks is not None:
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st.markdown("---")
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st.markdown("## 📈 选股结果")
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stocks_df = st.session_state.small_cap_stocks
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select_time = st.session_state.small_cap_time
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st.info(f"🕒 选股时间：{select_time} | 📊 股票数量：{len(stocks_df)} 只")
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# 显示股票列表
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display_stock_list(stocks_df)
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# 发送钉钉通知
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st.markdown("---")
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if st.button("📲 发送钉钉通知", type="secondary", use_container_width=True):
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send_dingtalk_notification(stocks_df)
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def display_stock_list(stocks_df: pd.DataFrame):
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"""显示股票列表"""
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for idx, row in stocks_df.iterrows():
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stock_code = row.get('股票代码', 'N/A')
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stock_name = row.get('股票简称', 'N/A')
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with st.expander(f"📊 {idx+1}. {stock_code} {stock_name}", expanded=True):
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display_stock_detail(row)
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def display_stock_detail(row: pd.Series):
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"""显示股票详细信息"""
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# 获取所有可能的字段
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financial_fields = [
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('总市值', row.get('总市值', row.get('总市值[20241211]', None))),
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('营收增长率', row.get('营收增长率', row.get('营业收入增长率', None))),
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('净利润增长率', row.get('净利润增长率', row.get('净利润同比增长率', None))),
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('股价', row.get('股价', row.get('最新价', None))),
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('市盈率', row.get('市盈率', row.get('市盈率TTM', None))),
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('市净率', row.get('市净率', row.get('市净率PB', None))),
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('所属行业', row.get('所属行业', row.get('所属同花顺行业', None))),
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]
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# 检查是否有任何有效数据
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has_any_data = any(is_valid_value(value) for _, value in financial_fields)
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# 决定布局
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if has_any_data:
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col1, col2 = st.columns(2)
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else:
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col1 = st.container()
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col2 = None
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with col1:
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st.markdown("#### 📊 基本信息")
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st.markdown(f"**股票代码**: {row.get('股票代码', 'N/A')}")
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st.markdown(f"**股票名称**: {row.get('股票简称', 'N/A')}")
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# 只有当有财务数据时才显示财务指标
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if col2 is not None:
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with col2:
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st.markdown("#### 💼 财务指标")
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for field_name, value in financial_fields:
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if is_valid_value(value):
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formatted_value = format_value(value, get_suffix(field_name))
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st.markdown(f"**{field_name}**: {formatted_value}")
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# 添加监控按钮
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st.markdown("---")
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st.markdown("#### 📊 策略监控")
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from low_price_bull_monitor_ui import add_stock_to_monitor_button
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stock_code = row.get('股票代码', '')
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stock_name = row.get('股票简称', '')
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price = row.get('股价', row.get('最新价', None))
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# 去掉代码后缀
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if isinstance(stock_code, str) and '.' in stock_code:
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stock_code = stock_code.split('.')[0]
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# 转换价格
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try:
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price_float = float(price) if price and not pd.isna(price) else None
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except:
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price_float = None
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if stock_code and stock_name:
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add_stock_to_monitor_button(stock_code, stock_name, price_float)
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def is_valid_value(value):
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"""判断值是否有效"""
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if value is None:
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return False
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if pd.isna(value):
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return False
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if str(value).strip() in ['', 'N/A', 'nan', 'None']:
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return False
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return True
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def format_value(value, suffix=''):
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"""格式化显示值"""
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if isinstance(value, (int, float)):
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if abs(value) >= 100000000: # 亿
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return f"{value/100000000:.2f}亿{suffix}"
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elif abs(value) >= 10000: # 万
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return f"{value/10000:.2f}万{suffix}"
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else:
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return f"{value:.2f}{suffix}"
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return f"{value}{suffix}"
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def get_suffix(field_name: str) -> str:
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"""获取字段后缀"""
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suffix_map = {
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'总市值': '元',
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'股价': '元',
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'营收增长率': '%',
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'净利润增长率': '%',
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}
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return suffix_map.get(field_name, '')
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def send_dingtalk_notification(stocks_df: pd.DataFrame):
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"""发送钉钉通知"""
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try:
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if not notification_service.config['webhook_enabled']:
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st.warning("⚠️ Webhook通知未启用，请在系统配置中启用")
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return
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# 构建消息
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keyword = notification_service.config.get('webhook_keyword', 'aiagents通知')
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message_text = f"### {keyword} - 小市值策略选股完成\n\n"
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message_text += "**筛选策略**: 总市值≤50亿 + 营收增长率≥10% + 净利润增长率≥100% + 沪深A股\n\n"
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message_text += f"**筛选数量**: {len(stocks_df)} 只\n\n"
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message_text += "**精选股票**:\n\n"
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for idx, row in stocks_df.iterrows():
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stock_code = row.get('股票代码', 'N/A')
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stock_name = row.get('股票简称', 'N/A')
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message_text += f"{idx+1}. {stock_code} {stock_name}\n\n"
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message_text += f"**生成时间**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
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message_text += "_此消息由AI股票分析系统自动发送_"
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# 直接发送钉钉Webhook
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if notification_service.config['webhook_type'] == 'dingtalk':
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import requests
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data = {
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"msgtype": "markdown",
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"markdown": {
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"title": f"{keyword}",
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"text": message_text
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}
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}
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response = requests.post(
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notification_service.config['webhook_url'],
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json=data,
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headers={'Content-Type': 'application/json'},
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timeout=10
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)
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if response.status_code == 200:
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st.success("✅ 钉钉通知发送成功")
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else:
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st.error(f"❌ 钉钉通知发送失败: HTTP {response.status_code}")
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else:
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st.warning("⚠️ 当前仅支持钉钉通知")
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except Exception as e:
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st.error(f"❌ 发送通知失败: {str(e)}")
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