Update app.py

app.py

@@ -6,6 +6,7 @@ import io
 import base64
 import matplotlib.gridspec as gridspec
 import math
+import re  # 新增正则模块
 
 SPLIT_TIME = "17:30"
 BUSINESS_START = "09:30"
@@ -26,8 +27,8 @@ def process_schedule(file):
         # 清理数据
         df = df.dropna(subset=['Hall', 'StartTime', 'EndTime'])
         
-        # 关键修改：影厅格式转换为带LaTeX上标井号
-        df['Hall'] = df['Hall'].str.extract(r'(\d+)号').astype(str) + r'$^{\#}$'  # <-- 修正后的表达式
+        # 转换影厅格式为带LaTeX上标井号
+        df['Hall'] = df['Hall'].str.extract(r'(\d+)号').astype(str) + r'$^{\#}$'
         
         # 保存原始时间字符串用于诊断
         df['original_end'] = df['EndTime']
@@ -80,196 +81,6 @@ def process_schedule(file):
         part1 = df[df['time_for_comparison'] <= split_time_for_comparison].copy()
         part2 = df[df['time_for_comparison'] > split_time_for_comparison].copy()
         
-        # 格式化时间显示
-        for part in [part1, part2]:
-            part['EndTime'] = part['EndTime'].dt.strftime('%-I:%M')
-        
-        # 关键修改：精确读取C6单元格
-        date_df = pd.read_excel(
-            file,
-            skiprows=5,    # 跳过前5行（0-4）
-            nrows=1,       # 只读1行
-            usecols=[2],   # 第三列（C列）
-            header=None    # 无表头
-        )
-        date_cell = date_df.iloc[0, 0]
-        
-        try:
-            # 处理不同日期格式
-            if isinstance(date_cell, str):
-                date_str = datetime.strptime(date_cell, '%Y-%m-%d').strftime('%Y-%m-%d')
-            else:
-                date_str = pd.to_datetime(date_cell).strftime('%Y-%m-%d')
-        except:
-            date_str = datetime.today().strftime('%Y-%m-%d')
-        
-        return part1[['Hall', 'EndTime']], part2[['Hall', 'EndTime']], date_str
-    
-    except Exception as e:
-        st.error(f"处理文件时出错: {str(e)}")
-        return None, None, None
-
-def create_print_layout(data, title, date_str):
-    """创建打印布局"""
-    if data.empty:
-        return None
-        
-    # 设置 A5 纸张竖向尺寸
-    fig = plt.figure(figsize=(5.83, 8.27), dpi=300)
-    plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
-    
-    # 设置字体
-    plt.rcParams['font.family'] = 'sans-serif'
-    plt.rcParams['font.sans-serif'] = ['Arial Unicode MS']
-    
-    # 计算行数和总数
-    total_items = len(data)
-    num_cols = 3
-    num_rows = math.ceil(total_items / num_cols)
-    
-    # 创建网格
-    gs = gridspec.GridSpec(num_rows + 1, num_cols, hspace=0.1, wspace=0.1, height_ratios=[1] * num_rows + [0.2])
-    
-    base_fontsize = min(30, 265 / num_rows)
-    
-    data_values = data.values.tolist()
-    
-    while len(data_values) % 3 != 0:
-        data_values.append(['', ''])
-        
-    rows_per_col = math.ceil(len(data_values) / 3)
-    
-    sorted_data = [['', '']] * len(data_values)
-    
-    for i, item in enumerate(data_values):
-        if item[0] and item[1]:
-            row = i % rows_per_col
-            col = i // rows_per_col
-            new_index = row * 3 + col
-            if new_index < len(sorted_data):
-                sorted_data[new_index] = item
-    
-    for idx, (hall, end_time) in enumerate(sorted_data):
-        if hall and end_time:
-            row = idx // 3
-            col = idx % 3
-            
-            ax = plt.subplot(gs[row, col])
-            
-            for spine in ax.spines.values():
-                spine.set_color(BORDER_COLOR)
-                spine.set_linewidth(0.5)
-            
-            display_text = f"{hall}{end_time}"
-            ax.text(0.5, 0.5, display_text,
-                    fontsize=base_fontsize,
-                    fontweight='bold',
-                    ha='center',
-                    va='center')
-            
-            ax.set_xlim(-0.02, 1.02)
-            ax.set_ylim(-0.02, 1.02)
-            
-            ax.set_xticks([])
-            ax.set_yticks([])
-    
-    # 添加日期信息
-    ax_date = plt.subplot(gs[0, 0])
-    ax_date.text(0.05, 0.95, f"{date_str} {title}",
-                 fontsize=base_fontsize * 0.4,
-                 color=DATE_COLOR,
-                 fontweight='bold',
-                 ha='left',
-                 va='top')
-    
-    for spine in ax_date.spines.values():
-        spine.set_visible(False)
-    ax_date.set_xticks([])
-    ax_date.set_yticks([])
-    
-    # 转换为图片
-    buffer = io.BytesIO()
-    plt.savefig(buffer, format='png', bbox_inches='tight', pad_inches=0.05)
-    buffer.seek(0)
-    image_base64 = base64.b64encode(buffer.getvalue()).decode()
-    plt.close()
-    
-    return f'data:image/png;base64,{image_base64}'
-
-# Streamlit 界面
-st.set_page_config(page_title="散厅时间快捷打印", layout="wide")
-st.title("散厅时间快捷打印")
-
-uploaded_file = st.file_uploader("上传【放映场次核对表.xls】文件", type=["xls", "xlsx"])
-
-if uploaded_file:
-    part1, part2, date_str = process_schedule(uploaded_file)
-    
-    if part1 is not None and part2 is not None:
-        part1_image = create_print_layout(part1, "A", date_str)
-        part2_image = create_print_layout(part2, "C", date_str)
-        
-        col1, col2 = st.columns(2)
-        
-        with col1:
-            st.subheader("白班散场预览（时间 ≤ 17:30）")
-            if part1_image:
-                st.image(part1_image)
-            else:
-                st.info("白班部分没有数据")
-        
-        with col2:
-            st.subheader("夜班散场预览（时间 > 17:30）")
-            if part2_image:
-                st.image(part2_image)
-            else:
-                st.info("夜班部分没有数据")        base_date = datetime.today().date()
-        df['StartTime'] = pd.to_datetime(df['StartTime'])
-        df['EndTime'] = pd.to_datetime(df['EndTime'])
-        
-        # 设置基准时间
-        business_start = datetime.strptime(f"{base_date} {BUSINESS_START}", "%Y-%m-%d %H:%M")
-        business_end = datetime.strptime(f"{base_date} {BUSINESS_END}", "%Y-%m-%d %H:%M")
-        
-        # 处理跨天情况
-        if business_end < business_start:
-            business_end += timedelta(days=1)
-        
-        # 标准化所有时间到同一天
-        for idx, row in df.iterrows():
-            end_time = row['EndTime']
-            if end_time.hour < 9:
-                df.at[idx, 'EndTime'] = end_time + timedelta(days=1)
-            
-            if row['StartTime'].hour >= 21 and end_time.hour < 9:
-                df.at[idx, 'EndTime'] = end_time + timedelta(days=1)
-        
-        # 筛选营业时间内的场次
-        df['time_for_comparison'] = df['EndTime'].apply(
-            lambda x: datetime.combine(base_date, x.time())
-        )
-        
-        df.loc[df['time_for_comparison'].dt.hour < 9, 'time_for_comparison'] += timedelta(days=1)
-        
-        valid_times = (
-            ((df['time_for_comparison'] >= datetime.combine(base_date, business_start.time())) &
-             (df['time_for_comparison'] <= datetime.combine(base_date + timedelta(days=1), business_end.time())))
-        )
-        
-        df = df[valid_times]
-        
-        # 按散场时间排序
-        df = df.sort_values('EndTime')
-        
-        # 分割数据
-        split_time = datetime.strptime(f"{base_date} {SPLIT_TIME}", "%Y-%m-%d %H:%M")
-        split_time_for_comparison = df['time_for_comparison'].apply(
-            lambda x: datetime.combine(base_date, split_time.time())
-        )
-        
-        part1 = df[df['time_for_comparison'] <= split_time_for_comparison].copy()
-        part2 = df[df['time_for_comparison'] > split_time_for_comparison].copy()
-        
         # 格式化时间显示
         for part in [part1, part2]:
             part['EndTime'] = part['EndTime'].dt.strftime('%-I:%M')