增加更多的历史记录，修正部份API数据获取错误，增加备用API (#5)

* 增加更多的历史记录，修正部份数据获取错误

* 增加更多的历史记录，修正部份API数据获取错误，增加备用API

---------

Co-authored-by: bathfire <>

main_force_ui.py

@@ -30,7 +30,7 @@ def display_main_force_selector():
         st.markdown("## 🎯 主力选股 - 智能筛选优质标的")
     with col_history:
         st.write("")  # 占位
-        if st.button("📚 批量分析历史", use_container_width=True):
+        if st.button("📚 批量分析历史", width='content'):
             st.session_state.main_force_view_history = True
             st.rerun()
     
@@ -102,8 +102,8 @@ def display_main_force_selector():
         with col1:
             max_change = st.number_input(
                 "最大涨跌幅(%)",
-                min_value=10.0,
-                max_value=100.0,
+                min_value=5.0,
+                max_value=200.0,
                 value=30.0,
                 step=5.0,
                 help="过滤掉涨幅过高的股票，避免追高"
@@ -121,7 +121,7 @@ def display_main_force_selector():
         with col3:
             max_cap = st.number_input(
                 "最大市值(亿)",
-                min_value=100.0,
+                min_value=50.0,
                 max_value=50000.0,
                 value=5000.0,
                 step=100.0
@@ -137,7 +137,7 @@ def display_main_force_selector():
     st.markdown("---")
     
     # 开始分析按钮
-    if st.button("🚀 开始主力选股", type="primary", use_container_width=True):
+    if st.button("🚀 开始主力选股", type="primary", width='content'):
         
         with st.spinner("正在获取数据并分析，这可能需要几分钟..."):
             
@@ -148,7 +148,10 @@ def display_main_force_selector():
             result = analyzer.run_full_analysis(
                 start_date=start_date,
                 days_ago=days_ago,
-                final_n=final_n
+                final_n=final_n,
+                max_range_change=max_change,
+                min_market_cap=min_cap,
+                max_market_cap=max_cap
             )
             
             # 保存结果到session_state
@@ -277,7 +280,7 @@ def display_analysis_results(result: dict, analyzer):
         
         # 显示DataFrame
         display_df = analyzer.raw_stocks[final_cols].copy()
-        st.dataframe(display_df, use_container_width=True, height=400)
+        st.dataframe(display_df, width='content', height=400)
         
         # 显示统计
         st.caption(f"共 {len(display_df)} 只候选股票，显示 {len(final_cols)} 个字段")
@@ -309,7 +312,7 @@ def display_analysis_results(result: dict, analyzer):
         
         with col_batch3:
             st.write("")  # 占位
-            if st.button("🚀 开始批量分析", type="primary", use_container_width=True):
+            if st.button("🚀 开始批量分析", type="primary", width='content'):
                 # 准备数据：按主力资金净流入排序
                 df_sorted = analyzer.raw_stocks.copy()
                 
@@ -497,7 +500,7 @@ def run_main_force_batch_analysis():
         # 返回按钮
         col_back, col_clear = st.columns(2)
         with col_back:
-            if st.button("🔙 返回主力选股", use_container_width=True):
+            if st.button("🔙 返回主力选股", width='content'):
                 # 清除所有批量分析相关状态
                 if 'main_force_batch_trigger' in st.session_state:
                     del st.session_state.main_force_batch_trigger
@@ -508,7 +511,7 @@ def run_main_force_batch_analysis():
                 st.rerun()
         
         with col_clear:
-            if st.button("🔄 重新分析", use_container_width=True):
+            if st.button("🔄 重新分析", width='content'):
                 # 清除结果，保留触发标志和代码
                 if 'main_force_batch_results' in st.session_state:
                     del st.session_state.main_force_batch_results
@@ -569,11 +572,11 @@ def run_main_force_batch_analysis():
     
     start_analysis = False
     with col_confirm:
-        if st.button("🚀 确认开始分析", type="primary", use_container_width=True):
+        if st.button("🚀 确认开始分析", type="primary", width='content'):
             start_analysis = True
     
     with col_cancel:
-        if st.button("❌ 取消", type="secondary", use_container_width=True):
+        if st.button("❌ 取消", type="secondary", width='content'):
             # 清除所有批量分析相关状态
             if 'main_force_batch_trigger' in st.session_state:
                 del st.session_state.main_force_batch_trigger
@@ -858,7 +861,19 @@ def display_main_force_batch_results(batch_results):
             })
         
         df_display = pd.DataFrame(display_data)
-        st.dataframe(df_display, use_container_width=True, height=400)
+        
+        # 类型统一，避免Arrow序列化错误
+        numeric_cols = ['信心度', '止盈位', '止损位', '目标价']
+        for col in numeric_cols:
+            if col in df_display.columns:
+                df_display[col] = pd.to_numeric(df_display[col], errors='coerce')
+
+        text_cols = ['股票代码', '股票名称', '评级', '进场区间']
+        for col in text_cols:
+            if col in df_display.columns:
+                df_display[col] = df_display[col].astype(str)
+        
+        st.dataframe(df_display, width='content', height=400)
         
         # 详细分析结果（可展开）
         st.markdown("---")
@@ -977,5 +992,5 @@ def display_main_force_batch_results(batch_results):
             })
         
         df_failed = pd.DataFrame(failed_data)
-        st.dataframe(df_failed, use_container_width=True)
+        st.dataframe(df_failed, width='content')