Update app.py

app.py

@@ -114,7 +114,8 @@ def fetch_and_process_server_movies(priority_movie_titles=None):
         if not content_name: continue
         movie_details[content_name] = {
             'assert_name': movie.get('ASSERT_NAME'),
-            'halls': sorted([h.get('HALL_NAME') for h in movie.get('HALL_INFO', [])])
+            'halls': sorted([h.get('HALL_NAME') for h in movie.get('HALL_INFO', [])]),
+            'play_time': movie.get('PLAY_TIME')
         }
 
     # 4. Prepare data for the two display views
@@ -137,7 +138,8 @@ def fetch_and_process_server_movies(priority_movie_titles=None):
             view2_list.append({
                 'assert_name': details['assert_name'],
                 'content_name': content_name,
-                'halls': details['halls']
+                'halls': details['halls'],
+                'play_time': details['play_time']
             })
 
     priority_list = [item for item in view2_list if
@@ -158,6 +160,19 @@ def get_circled_number(hall_name):
     return mapping.get(num_str, '')
 
 
+def format_play_time(time_str):
+    """Converts HH:MM:SS to total minutes (integer)."""
+    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])
+        return hours * 60 + minutes
+    except (ValueError, IndexError):
+        return None
+
+
 # --- 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。")
@@ -167,7 +182,6 @@ full_day_analysis = pd.DataFrame()
 
 if uploaded_file is not None:
     try:
-        # Efficiency analysis part
         df = pd.read_excel(uploaded_file, skiprows=3, header=None)
         df.rename(columns={0: '影片名称', 2: '放映时间', 5: '总人次', 6: '总收入', 7: '座位数'}, inplace=True)
         required_cols = ['影片名称', '放映时间', '座位数', '总收入', '总人次']
@@ -189,7 +203,7 @@ if uploaded_file is not None:
             table_height = (len(full_day_analysis) + 1) * 35 + 3
             st.dataframe(
                 full_day_analysis.style.format(format_config).apply(style_efficiency, axis=1).hide(axis="index"),
-                height=table_height, use_container_width=True)
+                height=table_height, use_container_width=True, hide_index = True)
 
         st.markdown("#### 黄金时段排片效率分析 (14:00-21:00)")
         start_time, end_time = pd.to_datetime('14:00:00').time(), pd.to_datetime('21:00:00').time()
@@ -199,7 +213,7 @@ if uploaded_file is not None:
             table_height_prime = (len(prime_time_analysis) + 1) * 35 + 3
             st.dataframe(
                 prime_time_analysis.style.format(format_config).apply(style_efficiency, axis=1).hide(axis="index"),
-                height=table_height_prime, use_container_width=True)
+                height=table_height_prime, use_container_width=True, hide_index = True)
 
         if not full_day_analysis.empty:
             st.markdown("##### 复制当日排片列表")
@@ -211,36 +225,41 @@ if uploaded_file is not None:
         st.error(f"处理文件时出错: {e}")
 
 
-# --- New Feature Module ---
 st.markdown("### TMS 服务器影片内容查询")
 if st.button('点击查询 TMS 服务器'):
-    with st.spinner("正在从 TMS 服务器获取数据中，请稍候..."):
+    with st.spinner("正在从 TMS 服务器获取数据中..."):
         try:
             priority_titles = full_day_analysis['影片'].tolist() if not full_day_analysis.empty else []
             halls_data, movie_list_sorted = fetch_and_process_server_movies(priority_titles)
             st.toast("TMS 服务器数据获取成功！", icon="🎉")
 
-            # --- View by Movie (in a single expander) ---
+            # --- View by Movie (Table Format) ---
             st.markdown("#### 按影片查看所在影厅")
-            with st.expander("点击展开 / 折叠影片列表", expanded = True):
-                for item in movie_list_sorted:
-                    circled_halls = " ".join(sorted([get_circled_number(h) for h in item['halls']]))
-                    st.markdown(f"**{item['assert_name']}** - {circled_halls} - `{item['content_name']}`")
 
-            # --- View by Hall ---
+            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)
+
+            # --- View by Hall (Table Format) ---
             st.markdown("#### 按影厅查看影片内容")
             hall_tabs = st.tabs(halls_data.keys())
             for tab, hall_name in zip(hall_tabs, halls_data.keys()):
                 with tab:
-                    for movie_item in halls_data[hall_name]:
-                        details = movie_item['details']
-                        content_name = movie_item['content_name']
-                        assert_name = details['assert_name']
-
-                        display_name = assert_name if assert_name else content_name
-                        circled_halls = " ".join(sorted([get_circled_number(h) for h in details['halls']]))
-
-                        st.markdown(f"- **{display_name}** - {circled_halls} - `{content_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}")
+
+