Update app.py

app.py

@@ -18,7 +18,7 @@ def clean_movie_title(title):
 
 def style_efficiency(row):
     green = 'background-color: #E6F5E6;'  # Light Green
-    red = 'background-color: #FFE5E5;'  # Light Red
+    red = 'background-color: #FFE5E5;'    # Light Red
     default = ''
     styles = [default] * len(row)
     seat_efficiency = row.get('座次效率', 0)
@@ -161,41 +161,43 @@ def get_circled_number(hall_name):
 def format_play_time(time_str):
     if not time_str or not isinstance(time_str, str): return None
     try:
-        parts = time_str.split(':');
-        hours = int(parts[0]);
-        minutes = int(parts[1])
+        parts = time_str.split(':'); hours = int(parts[0]); minutes = int(parts[1])
         return hours * 60 + minutes
     except (ValueError, IndexError):
         return None
 
 
-# --- NEW Helper function to add TMS location column ---
+# --- UPDATED Helper function to add TMS location column ---
 def add_tms_locations_to_analysis(analysis_df, tms_movie_list):
     locations = []
     for index, row in analysis_df.iterrows():
         movie_title = row['影片']
         found_versions = []
         for tms_movie in tms_movie_list:
-            if movie_title in tms_movie['assert_name']:
-                # Extract version name by removing the base title
+            # FIX 3: Change matching from 'in' to 'startswith'
+            if tms_movie['assert_name'].startswith(movie_title):
                 version_name = tms_movie['assert_name'].replace(movie_title, '').strip()
                 circled_halls = " ".join(sorted([get_circled_number(h) for h in tms_movie['halls']]))
-                found_versions.append(f"{version_name}：{circled_halls}")
-
+                
+                # FIX 2: Handle empty version name to remove colon
+                if version_name:
+                    found_versions.append(f"{version_name}：{circled_halls}")
+                else:
+                    found_versions.append(circled_halls)
+        
         locations.append('｜'.join(found_versions))
 
     analysis_df['影片所在影厅位置'] = locations
     return analysis_df
 
-
 # --- Streamlit Main UI ---
 st.title('影城排片效率与内容分析工具')
 st.write("上传 `影片映出日累计报表.xlsx` 进行效率分析，或点击下方按钮查询 TMS 服务器影片内容。")
 
 uploaded_file = st.file_uploader("请在此处上传 Excel 文件", type=['xlsx', 'xls', 'csv'])
-# NEW: Checkbox for the new feature
 query_tms_for_location = st.checkbox("查询 TMS 找影片所在影厅")
 
+
 if uploaded_file is not None:
     try:
         df = pd.read_excel(uploaded_file, skiprows=3, header=None)
@@ -214,17 +216,28 @@ if uploaded_file is not None:
                          '场次效率': '{:.2f}'}
 
         full_day_analysis = process_and_analyze_data(df.copy())
-        prime_time_analysis = process_and_analyze_data(
-            df[df['放映时间'].between(pd.to_datetime('14:00:00').time(), pd.to_datetime('21:00:00').time())].copy())
-
-        # --- NEW LOGIC: If checkbox is ticked, fetch data and modify dataframes ---
+        prime_time_analysis = process_and_analyze_data(df[df['放映时间'].between(pd.to_datetime('14:00:00').time(), pd.to_datetime('21:00:00').time())].copy())
+        
         if query_tms_for_location:
             with st.spinner("正在关联查询 TMS 服务器..."):
                 _, tms_movie_list = fetch_and_process_server_movies()
                 full_day_analysis = add_tms_locations_to_analysis(full_day_analysis, tms_movie_list)
                 prime_time_analysis = add_tms_locations_to_analysis(prime_time_analysis, tms_movie_list)
+                
+                # FIX 1: Reorder columns
+                if '影片所在影厅位置' in full_day_analysis.columns:
+                    cols_full = full_day_analysis.columns.tolist()
+                    cols_full.insert(1, cols_full.pop(cols_full.index('影片所在影厅位置')))
+                    full_day_analysis = full_day_analysis[cols_full]
+
+                if '影片所在影厅位置' in prime_time_analysis.columns:
+                    cols_prime = prime_time_analysis.columns.tolist()
+                    cols_prime.insert(1, cols_prime.pop(cols_prime.index('影片所在影厅位置')))
+                    prime_time_analysis = prime_time_analysis[cols_prime]
+
                 st.toast("TMS 影片位置关联成功！", icon="🔗")
 
+
         st.markdown("### 全天排片效率分析")
         if not full_day_analysis.empty:
             st.dataframe(
@@ -246,6 +259,7 @@ if uploaded_file is not None:
     except Exception as e:
         st.error(f"处理文件时出错: {e}")
 
+
 st.divider()
 st.markdown("### TMS 服务器影片内容查询")
 if st.button('点击查询 TMS 服务器'):
@@ -255,10 +269,7 @@ if st.button('点击查询 TMS 服务器'):
             st.toast("TMS 服务器数据获取成功！", icon="🎉")
 
             st.markdown("#### 按影片查看所在影厅")
-            view2_data = [{'影片名称': item['assert_name'],
-                           '所在影厅': " ".join(sorted([get_circled_number(h) for h in item['halls']])),
-                           '文件名': item['content_name'], '时长': format_play_time(item['play_time'])} for item in
-                          movie_list_sorted]
+            view2_data = [{'影片名称': item['assert_name'], '所在影厅': " ".join(sorted([get_circled_number(h) for h in item['halls']])), '文件名': item['content_name'], '时长': format_play_time(item['play_time'])} for item in movie_list_sorted]
             df_view2 = pd.DataFrame(view2_data)
             st.dataframe(df_view2, hide_index=True, use_container_width=True)
 
@@ -266,13 +277,10 @@ if st.button('点击查询 TMS 服务器'):
             hall_tabs = st.tabs(halls_data.keys())
             for tab, hall_name in zip(hall_tabs, halls_data.keys()):
                 with tab:
-                    view1_data_for_tab = [{'影片名称': item['details']['assert_name'], '所在影厅': " ".join(
-                        sorted([get_circled_number(h) for h in item['details']['halls']])),
-                                           '文件名': item['content_name'],
-                                           '时长': format_play_time(item['details']['play_time'])} for item in
-                                          halls_data[hall_name]]
+                    view1_data_for_tab = [{'影片名称': item['details']['assert_name'], '所在影厅': " ".join(sorted([get_circled_number(h) for h in item['details']['halls']])), '文件名': item['content_name'], '时长': format_play_time(item['details']['play_time'])} for item in halls_data[hall_name]]
                     df_view1_tab = pd.DataFrame(view1_data_for_tab)
                     st.dataframe(df_view1_tab, hide_index=True, use_container_width=True)
 
         except Exception as e:
-            st.error(f"查询服务器时出错: {e}")
+            st.error(f"查询服务器时出错: {e}")
+