feat: 添加新闻及资金流入排行榜

web/app.py

@@ -450,14 +450,22 @@ def main():
 
     page = st.sidebar.selectbox(
         "切换功能模块",
-        ["📊 股票分析", "⚙️ 配置管理", "💾 缓存管理", "💰 Token统计", "📈 历史记录", "🔧 系统状态"],
+        ["📊 股票分析","📰 新闻概况", "⚙️ 配置管理", "💾 缓存管理", "💰 Token统计", "📈 历史记录", "🔧 系统状态"],
         label_visibility="collapsed"
     )
 
     # 在功能选择和AI模型配置之间添加分隔线
     st.sidebar.markdown("---")
 
     # 根据选择的页面渲染不同内容
+    if page == "📰 新闻概况":
+        try:
+            from modules.news_display import render_news_display
+            render_news_display()
+        except ImportError as e:
+            st.error(f"新闻概况模块加载失败: {e}")
+            st.info("请确保已安装所有依赖包")
+        return
     if page == "⚙️ 配置管理":
         try:
             from modules.config_management import render_config_management

web/modules/news_display.py

@@ -0,0 +1,255 @@
+import streamlit as st
+import os
+import json
+import hashlib
+from datetime import datetime, timedelta
+import akshare as ak
+import pandas as pd
+from typing import List, Dict, Any
+
+# ======================================================================
+# 1. 配置与样式
+# ======================================================================
+st.set_page_config(page_title="市场动态看板", layout="wide")
+
+def load_css():
+    st.markdown("""
+    <style>
+    /* 新闻内容样式 */
+    .news-title {
+        font-weight: 700;
+        font-size: 16px;
+        color: #003366;
+        margin-bottom: 0px; /* 减少标题和内容的间距 */
+    }
+    .news-content {
+        font-size: 14px;
+        line-height: 1.5;
+        white-space: pre-wrap; /* 保持换行 */
+        word-break: break-word; /* 防止长链接溢出 */
+    }
+    /* 时间文本样式 */
+    .time-text {
+        font-size: 1.2em;
+        font-weight: bold;
+        color: #555;
+    }
+    /* 资金流卡片样式 */
+    .card {
+        border: 1px solid #ddd; padding: 15px; margin-bottom: 20px; 
+        border-radius: 8px; box-shadow: 0 2px 4px rgba(0,0,0,0.05);
+        max-height: 420px; overflow-y: auto;
+    }
+    .card h3 {
+        margin-top: 0; margin-bottom: 15px; border-bottom: 2px solid #eee;
+        padding-bottom: 10px; font-size: 18px;
+    }
+    .card .fund-flow-item {
+        padding: 8px 5px; border-bottom: 1px solid #eee;
+        display: flex; justify-content: space-between; align-items: center;
+    }
+    .card .fund-flow-item:last-child { border-bottom: none; }
+    .card .fund-flow-name { font-weight: bold; }
+    .card .fund-flow-value { color: #c00; font-family: monospace; }
+    </style>
+    """, unsafe_allow_html=True)
+
+# ======================================================================
+# 2. 数据获取与处理
+# ======================================================================
+
+@st.cache_resource
+def get_news_fetcher():
+    return NewsFetcher()
+
+class NewsFetcher:
+    def __init__(self, save_dir="data/news"):
+        self.save_dir = save_dir
+        os.makedirs(self.save_dir, exist_ok=True)
+        self.news_hashes = self._load_existing_hashes()
+    def _load_existing_hashes(self) -> set:
+        hashes = set()
+        today = datetime.now()
+        for i in range(3):
+            filename = self._get_news_filename(today - timedelta(days=i))
+            if os.path.exists(filename):
+                try:
+                    with open(filename, 'r', encoding='utf-8') as f:
+                        news_data = json.load(f)
+                        for item in news_data:
+                            h = item.get("hash") or self._calculate_hash(item.get("content", ""))
+                            hashes.add(h)
+                except (json.JSONDecodeError, IOError):
+                    continue
+        return hashes
+    def _calculate_hash(self, content: str) -> str:
+        return hashlib.md5(str(content).encode('utf-8')).hexdigest()
+    def _get_news_filename(self, date: datetime = None) -> str:
+        dt_str = (date or datetime.now()).strftime('%Y%m%d')
+        return os.path.join(self.save_dir, f"news_{dt_str}.json")
+    def fetch_and_save(self) -> bool:
+        try:
+            stock_info_global_cls_df = ak.stock_info_global_cls(symbol="全部")
+        except Exception as e:
+            st.error(f"获取新闻时出错: {e}")
+            return False
+        if stock_info_global_cls_df.empty: return True
+        news_list = []
+        for _, row in stock_info_global_cls_df.iterrows():
+            content = str(row.get("内容", ""))
+            content_hash = self._calculate_hash(content)
+            if content_hash in self.news_hashes: continue
+            self.news_hashes.add(content_hash)
+            pub_date = str(row.get("发布日期", ""))
+            pub_time = str(row.get("发布时间", ""))
+            news_item = {
+                "title": str(row.get("标题", "")), 
+                "content": content, 
+                "datetime": f"{pub_date} {pub_time}", 
+                "hash": content_hash,
+            }
+            news_list.append(news_item)
+        if not news_list: return True
+        filename = self._get_news_filename()
+        existing_data = []
+        if os.path.exists(filename):
+            try:
+                with open(filename, 'r', encoding='utf-8') as f:
+                    existing_data = json.load(f)
+            except (json.JSONDecodeError, IOError): pass
+        merged_news = sorted(existing_data + news_list, key=lambda x: x.get('datetime', '0'), reverse=True)
+        with open(filename, 'w', encoding='utf-8') as f:
+            json.dump(merged_news, f, ensure_ascii=False, indent=2)
+        return True
+    def get_latest_news(self, days: int = 1) -> List[Dict[str, Any]]:
+        news_data = []
+        today = datetime.now()
+        for i in range(days):
+            filename = self._get_news_filename(today - timedelta(days=i))
+            if os.path.exists(filename):
+                try:
+                    with open(filename, 'r', encoding='utf-8') as f:
+                        news_data.extend(json.load(f))
+                except (json.JSONDecodeError, IOError): continue
+        seen_hashes = set()
+        unique_news = []
+        for item in sorted(news_data, key=lambda x: x.get('datetime', '0'), reverse=True):
+            item_hash = item.get('hash')
+            if item_hash not in seen_hashes:
+                unique_news.append(item)
+                seen_hashes.add(item_hash)
+        return unique_news
+
+@st.cache_data(ttl=600)
+def get_fund_flow_data(data_type: str) -> pd.DataFrame:
+    try:
+        if data_type == "industry":
+            return ak.stock_fund_flow_industry()
+        elif data_type == "concept":
+            return ak.stock_fund_flow_concept()
+        else:
+            return pd.DataFrame()
+    except Exception as e:
+        st.error(f"获取 {data_type} 资金流数据失败: {e}", icon="🚨")
+        return pd.DataFrame()
+
+# ======================================================================
+# 3. UI 渲染函数
+# ======================================================================
+
+def display_news_timeline(news_list: List[Dict[str, Any]], limit: int):
+    st.header("实时新闻")
+    if not news_list:
+        st.info("暂无新闻数据。请尝试调整侧边栏天数。")
+        return
+
+    for news in news_list[:limit]:
+        try:
+            dt_obj = datetime.strptime(news['datetime'], "%Y-%m-%d %H:%M:%S")
+            time_str = dt_obj.strftime("%H:%M")
+        except (ValueError, KeyError):
+            time_str = "N/A"
+
+        col_time, col_content = st.columns([1, 9])
+        with col_time:
+            st.markdown(f'<p class="time-text">{time_str}</p>', unsafe_allow_html=True)
+        with col_content:
+            st.markdown(f"<p class='news-title'>{news.get('title', '无标题')}</p>", unsafe_allow_html=True)
+            st.markdown(f"<p class='news-content'>{news.get('content', '无内容')}</p>", unsafe_allow_html=True)
+
+        st.divider()
+
+def display_fund_flow_card(title: str, df: pd.DataFrame, name_col: str, value_col: str):
+    html_parts = [f'<div class="card"><h3>{title}</h3>']
+    if df.empty:
+        html_parts.append("<p>暂无数据</p>")
+    else:
+        if value_col in df.columns:
+            df_sorted = df.sort_values(by=value_col, ascending=False).head(15)
+        else:
+            df_sorted = df.head(15)
+            st.warning(f"资金流数据中未找到列 '{value_col}' 用于排序。")
+        for _, row in df_sorted.iterrows():
+            name = row.get(name_col, '未知')
+            value = row.get(value_col, 'N/A')
+            value_str = f"{value}亿" if isinstance(value, (int, float)) else "N/A"
+            html_parts.append(
+                f'<div class="fund-flow-item">'
+                f'  <span class="fund-flow-name">{name}</span>'
+                f'  <span class="fund-flow-value">{value_str}</span>'
+                f'</div>'
+            )
+    html_parts.append('</div>')
+    st.markdown("".join(html_parts), unsafe_allow_html=True)
+
+# ======================================================================
+# 4. 主应用逻辑
+# ======================================================================
+
+def render_news_display():
+    load_css()
+    st.title("📈 市场动态看板")
+
+    st.sidebar.title("🛠️ 控制面板")
+
+    days = st.sidebar.slider("显示最近几天新闻", 1, 7, 3, key="days_slider")
+    limit = st.sidebar.slider("最多显示新闻条数", 10, 100, 50, key="limit_slider")
+
+    news_fetcher = get_news_fetcher()
+
+    # 初始化 session_state
+    if 'prev_days' not in st.session_state:
+        st.session_state.prev_days = None
+    if 'prev_limit' not in st.session_state:
+        st.session_state.prev_limit = None
+    if 'data_refreshed' not in st.session_state:
+        st.session_state.data_refreshed = False
+
+    # 滑块变化则刷新数据
+    if (days != st.session_state.prev_days) or (limit != st.session_state.prev_limit) or (not st.session_state.data_refreshed):
+        with st.spinner("正在刷新新闻数据..."):
+            st.cache_data.clear()
+            news_fetcher.fetch_and_save()
+        st.session_state.prev_days = days
+        st.session_state.prev_limit = limit
+        st.session_state.data_refreshed = True
+
+    col_left, col_right = st.columns([2, 1])
+
+    with col_left:
+        with st.container(height=800, border=False):
+            news_list = news_fetcher.get_latest_news(days=days)
+            display_news_timeline(news_list, limit)
+
+    with col_right:
+        st.header("资金流排行")
+        df_industry = get_fund_flow_data("industry")
+        display_fund_flow_card("行业资金流", df_industry, name_col="行业", value_col="流入资金")
+        df_concept = get_fund_flow_data("concept")
+        display_fund_flow_card("概念资金流", df_concept, name_col="行业", value_col="流入资金")
+
+def main():
+    render_news_display()
+
+if __name__ == "__main__":
+    main()