Update app.py

app.py

@@ -1,453 +1,281 @@
 import pandas as pd
 import streamlit as st
+from datetime import datetime, timedelta
 import matplotlib.pyplot as plt
-import matplotlib.font_manager as font_manager
 import io
 import base64
-import os
-from datetime import datetime, timedelta
+import matplotlib.gridspec as gridspec
 import math
-from pypinyin import lazy_pinyin, Style
 from matplotlib.backends.backend_pdf import PdfPages
-import matplotlib.gridspec as gridspec
-from matplotlib.patches import FancyBboxPatch
+from matplotlib.patches import Rectangle # Replaced FancyBboxPatch
 
-# --- Constants for "Quick Print" (放映场次核对表) ---
+# --- Constants ---
 SPLIT_TIME = "17:30"
 BUSINESS_START = "09:30"
 BUSINESS_END = "01:30"
 BORDER_COLOR = '#A9A9A9'
 DATE_COLOR = '#A9A9A9'
+SEQ_COLOR = '#A9A9A9' # Color for the new serial number
 
-# --- Helper functions for "LED Screen" (放映时间核对表) ---
-def get_font(size=14):
-    """Loads a specific font file, falling back to a default if not found."""
-    font_path = "simHei.ttc"
-    if not os.path.exists(font_path):
-        font_path = "SimHei.ttf"  # Fallback font
-    # Add a final fallback for systems without Chinese fonts
-    try:
-        return font_manager.FontProperties(fname=font_path, size=size)
-    except RuntimeError:
-        # If the font file is not found, use a default font that should exist.
-        # This will likely not render Chinese characters correctly but prevents crashing.
-        return font_manager.FontProperties(family='sans-serif', size=size)
-
-
-def get_pinyin_abbr(text):
-    """Gets the first letter of the Pinyin for the first two Chinese characters of a text."""
-    if not text:
-        return ""
-    # Extract the first two Chinese characters
-    chars = [c for c in text if '\u4e00' <= c <= '\u9fff']
-    chars = chars[:2]
-    # Get the first letter of the pinyin for each character
-    pinyin_list = lazy_pinyin(chars, style=Style.FIRST_LETTER)
-    return ''.join(pinyin_list).upper()
-
-# --- Processing logic for "LED Screen" (放映时间核对表) ---
-def process_schedule_led(file):
-    """Processes the '放映时间核对表.xls' file."""
-    try:
-        # Attempt to read the date from a specific cell
-        date_df = pd.read_excel(file, header=None, skiprows=7, nrows=1, usecols=[3])
-        date_str = pd.to_datetime(date_df.iloc[0, 0]).strftime('%Y-%m-%d')
-        base_date = pd.to_datetime(date_str).date()
-    except Exception:
-        # Fallback to the current date if reading fails
-        date_str = datetime.today().strftime('%Y-%m-%d')
-        base_date = datetime.today().date()
-
+def process_schedule(file):
+    """处理上传的 Excel 文件，生成排序和分组后的打印内容"""
     try:
-        df = pd.read_excel(file, header=9, usecols=[1, 2, 4, 5])
-        df.columns = ['Hall', 'StartTime', 'EndTime', 'Movie']
-        df['Hall'] = df['Hall'].ffill()
-        df.dropna(subset=['StartTime', 'EndTime', 'Movie'], inplace=True)
-        df['Hall'] = df['Hall'].astype(str).str.extract(r'(\d+号)')
-
-        # Convert times to datetime objects, handling overnight screenings
-        df['StartTime_dt'] = pd.to_datetime(df['StartTime'], format='%H:%M', errors='coerce').apply(
-            lambda t: t.replace(year=base_date.year, month=base_date.month, day=base_date.day) if pd.notnull(t) else t
-        )
-        df['EndTime_dt'] = pd.to_datetime(df['EndTime'], format='%H:%M', errors='coerce').apply(
-            lambda t: t.replace(year=base_date.year, month=base_date.month, day=base_date.day) if pd.notnull(t) else t
-        )
-        df.loc[df['EndTime_dt'] < df['StartTime_dt'], 'EndTime_dt'] += timedelta(days=1)
-        df = df.sort_values(['Hall', 'StartTime_dt'])
-
-        # Merge consecutive screenings of the same movie
-        merged_rows = []
-        for hall, group in df.groupby('Hall'):
-            group = group.sort_values('StartTime_dt')
-            current = None
-            for _, row in group.iterrows():
-                if current is None:
-                    current = row.copy()
-                else:
-                    if row['Movie'] == current['Movie']:
-                        current['EndTime_dt'] = row['EndTime_dt']
-                    else:
-                        merged_rows.append(current)
-                        current = row.copy()
-            if current is not None:
-                merged_rows.append(current)
-
-        merged_df = pd.DataFrame(merged_rows)
-
-        # Adjust start and end times
-        merged_df['StartTime_dt'] = merged_df['StartTime_dt'] - timedelta(minutes=10)
-        merged_df['EndTime_dt'] = merged_df['EndTime_dt'] - timedelta(minutes=5)
-
-        merged_df['StartTime_str'] = merged_df['StartTime_dt'].dt.strftime('%H:%M')
-        merged_df['EndTime_str'] = merged_df['EndTime_dt'].dt.strftime('%H:%M')
-
-        return merged_df[['Hall', 'Movie', 'StartTime_str', 'EndTime_str']], date_str
-    except Exception as e:
-        st.error(f"An error occurred during file processing: {e}")
-        return None, date_str
-
-# --- Layout generation for "LED Screen" (放映时间核对表) ---
-def create_print_layout_led(data, date_str):
-    """Generates PNG and PDF layouts for the 'LED Screen' schedule."""
-    if data is None or data.empty:
-        return None
-
-    # Create figures for PNG and PDF output with A4 dimensions
-    png_fig = plt.figure(figsize=(8.27, 11.69), dpi=300)
-    png_ax = png_fig.add_subplot(111)
-    png_ax.set_axis_off()
-    png_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
-
-    pdf_fig = plt.figure(figsize=(8.27, 11.69), dpi=300)
-    pdf_ax = pdf_fig.add_subplot(111)
-    pdf_ax.set_axis_off()
-    pdf_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
-
-    def process_figure(fig, ax):
-        halls = sorted(data['Hall'].unique(), key=lambda h: int(h.replace('号','')) if h else 0)
-
-        num_separators = len(halls) - 1
-        total_layout_rows = len(data) + num_separators + 2
-        
-        available_height = 0.96
-        row_height = available_height / total_layout_rows
+        # 读取 Excel，跳过前 8 行
+        df = pd.read_excel(file, skiprows=8)
 
-        fig_height_inches = fig.get_figheight()
-        row_height_points = row_height * fig_height_inches * 72
-        font_size = row_height_points * 0.9
+        # 提取所需列 (G9, H9, J9)
+        df = df.iloc[:, [6, 7, 9]]  # G, H, J 列
+        df.columns = ['Hall', 'StartTime', 'EndTime']
 
-        date_font = get_font(font_size * 0.8)
-        hall_font = get_font(font_size)
-        movie_font = get_font(font_size)
+        # 清理数据
+        df = df.dropna(subset=['Hall', 'StartTime', 'EndTime'])
 
-        col_hall_left = 0.0
-        col_movie_right = 0.50
-        col_seq_left = 0.52
-        col_pinyin_left = 0.62
-        col_time_left = 0.75
+        # 转换影厅格式为 "#号" 格式
+        df['Hall'] = df['Hall'].str.extract(r'(\d+)号').astype(str) + ' '
 
-        ax.text(col_hall_left, 0.99, date_str, color='#A9A9A9',
-                ha='left', va='top', fontproperties=date_font, transform=ax.transAxes)
-        
-        y_position = 0.98 - row_height
-        
-        for i, hall in enumerate(halls):
-            hall_data = data[data['Hall'] == hall]
-            
-            if i > 0:
-                ax.axhline(y=y_position + row_height / 2, xmin=col_hall_left, xmax=0.97, color='black', linewidth=0.7)
-                y_position -= row_height
-
-            movie_count = 1
-            for _, row in hall_data.iterrows():
-                if movie_count == 1:
-                    ax.text(col_hall_left, y_position, f"{hall.replace('号', '')}#",
-                            ha='left', va='center', fontweight='bold',
-                            fontproperties=hall_font, transform=ax.transAxes)
-                
-                ax.text(col_movie_right, y_position, row['Movie'],
-                        ha='right', va='center', fontproperties=movie_font, transform=ax.transAxes)
-
-                ax.text(col_seq_left, y_position, f"{movie_count}.",
-                        ha='left', va='center', fontproperties=movie_font, transform=ax.transAxes)
-
-                pinyin_abbr = get_pinyin_abbr(row['Movie'])
-                ax.text(col_pinyin_left, y_position, pinyin_abbr,
-                        ha='left', va='center', fontproperties=movie_font, transform=ax.transAxes)
-                
-                ax.text(col_time_left, y_position, f"{row['StartTime_str']}-{row['EndTime_str']}",
-                        ha='left', va='center', fontproperties=movie_font, transform=ax.transAxes)
-
-                y_position -= row_height
-                movie_count += 1
-
-    process_figure(png_fig, png_ax)
-    process_figure(pdf_fig, pdf_ax)
-    
-    png_buffer = io.BytesIO()
-    png_fig.savefig(png_buffer, format='png', bbox_inches='tight', pad_inches=0.05)
-    png_buffer.seek(0)
-    image_base64 = base64.b64encode(png_buffer.getvalue()).decode()
-    plt.close(png_fig)
-    
-    pdf_buffer = io.BytesIO()
-    with PdfPages(pdf_buffer) as pdf:
-        pdf.savefig(pdf_fig, bbox_inches='tight', pad_inches=0.05)
-    pdf_buffer.seek(0)
-    pdf_base64 = base64.b64encode(pdf_buffer.getvalue()).decode()
-    plt.close(pdf_fig)
-    
-    return {
-        'png': f"data:image/png;base64,{image_base64}",
-        'pdf': f"data:application/pdf;base64,{pdf_base64}"
-    }
+        # 保存原始时间字符串用于诊断
+        df['original_end'] = df['EndTime']
 
-# --- Processing logic for "Quick Print" (放映场次核对表) ---
-def process_schedule_quick(file):
-    """Processes the '放映场次核对表.xls' file."""
-    try:
-        df = pd.read_excel(file, skiprows=8)
-        df = df.iloc[:, [6, 7, 9]]
-        df.columns = ['Hall', 'StartTime', 'EndTime']
-        df = df.dropna(subset=['Hall', 'StartTime', 'EndTime'])
-        df['Hall'] = df['Hall'].str.extract(r'(\d+)号').astype(str) + ' '
-        
+        # 转换时间为 datetime 对象
         base_date = datetime.today().date()
-        df['StartTime'] = pd.to_datetime(df['StartTime'])
-        df['EndTime'] = pd.to_datetime(df['EndTime'])
-
-        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")
-        if business_end < business_start:
-            business_end += timedelta(days=1)
-
-        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)
-        
-        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()))
+        # Using errors='coerce' will turn unparseable times into NaT (Not a Time)
+        df['StartTime'] = pd.to_datetime(df['StartTime'], errors='coerce')
+        df['EndTime'] = pd.to_datetime(df['EndTime'], errors='coerce')
+        df = df.dropna(subset=['StartTime', 'EndTime']) # Drop rows where time conversion failed
+
+        # 设置基准时间
+        business_start_time = datetime.strptime(BUSINESS_START, "%H:%M").time()
+        business_end_time = datetime.strptime(BUSINESS_END, "%H:%M").time()
+
+        # 处理跨天情况：结束时间小于开始时间，则结束时间加一天
+        # This logic handles cases like 9:30 AM to 1:30 AM (next day)
+        df['EndTime_adjusted'] = df.apply(
+            lambda row: row['EndTime'] + timedelta(days=1) if row['EndTime'].time() < row['StartTime'].time() else row['EndTime'],
+            axis=1
         )
-        df = df[valid_times]
-        df = df.sort_values('EndTime')
         
-        split_time_dt = datetime.strptime(f"{base_date} {SPLIT_TIME}", "%Y-%m-%d %H:%M")
+        # 按散场时间排序 (using the adjusted time)
+        df = df.sort_values('EndTime_adjusted')
+
+        # 分割数据
+        split_dt = datetime.strptime(SPLIT_TIME, "%H:%M").time()
         
-        part1 = df[df['time_for_comparison'] <= split_time_dt].copy()
-        part2 = df[df['time_for_comparison'] > split_time_dt].copy()
+        part1 = df[df['EndTime_adjusted'].dt.time <= split_dt].copy()
+        part2 = df[df['EndTime_adjusted'].dt.time > split_dt].copy()
 
+        # 格式化时间显示 (use original EndTime for display)
         for part in [part1, part2]:
-            part['EndTime'] = part['EndTime'].dt.strftime('%-H:%M')
-        
+            part['EndTime_formatted'] = part['EndTime'].dt.strftime('%-I:%M')
+
+        # 读取日期单元格 C6
         date_df = pd.read_excel(file, skiprows=5, nrows=1, usecols=[2], header=None)
         date_cell = date_df.iloc[0, 0]
-        
+
         try:
             if isinstance(date_cell, str):
+                # Assuming format like '2023-10-27'
                 date_str = datetime.strptime(date_cell, '%Y-%m-%d').strftime('%Y-%m-%d')
             else:
+                # Assuming it's a datetime object
                 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
+
+        return part1[['Hall', 'EndTime_formatted']], part2[['Hall', 'EndTime_formatted']], date_str
 
     except Exception as e:
         st.error(f"处理文件时出错: {str(e)}")
         return None, None, None
 
-# --- Layout generation for "Quick Print" (放映场次核对表) ---
-def create_print_layout_quick(data, title, date_str):
-    """Creates print layout for the 'Quick Print' schedule."""
+
+def create_print_layout(data, title, date_str):
+    """
+    创建符合新要求的打印布局 (PNG 和 PDF)。
+    1. 动态计算边距。
+    2. 使用灰色虚线圆点作为单元格边框。
+    3. 单元格内容区域为单元格的90%。
+    4. 在左上角添加灰色序号。
+    """
     if data.empty:
         return None
 
-    png_fig = plt.figure(figsize=(5.83, 8.27), dpi=300) # A5
-    png_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
-
-    pdf_fig = plt.figure(figsize=(5.83, 8.27), dpi=300) # A5
-    pdf_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
-
-    def process_figure(fig, is_pdf=False):
-        plt.rcParams['font.family'] = 'sans-serif'
-        plt.rcParams['font.sans-serif'] = ['Arial Unicode MS', 'Heiti TC', 'SimHei']
-
-        total_items = len(data)
-        num_cols = 3
-        num_rows = math.ceil(total_items / num_cols)
-
-        gs = gridspec.GridSpec(num_rows + 1, num_cols, hspace=0.05, wspace=0.05, height_ratios=[0.1] + [1] * num_rows, figure=fig)
-
-        target_width_px = 1
-        if total_items > 0:
-            ax_temp = fig.add_subplot(gs[1, 0])
-            fig.canvas.draw()
-            target_width_px = ax_temp.get_window_extent().width * 0.90
-            ax_temp.remove()
-
-        available_height_per_row = (8.27 * 0.9 * (1 / 1.2)) / num_rows if num_rows > 0 else 1
-        date_fontsize = min(40, max(10, available_height_per_row * 72 * 0.5))
-
-        data_values = data.values.tolist()
-        while len(data_values) % num_cols != 0:
-            data_values.append(['', ''])
-        rows_per_col_layout = math.ceil(len(data_values) / num_cols)
-
-        sorted_data = [['', '']] * len(data_values)
-        for i, item in enumerate(data_values):
-            if item[0] and item[1]:
-                row_in_col = i % rows_per_col_layout
-                col_idx = i // rows_per_col_layout
-                new_index = row_in_col * num_cols + col_idx
-                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_grid = idx // num_cols + 1
-                col_grid = idx % num_cols
-
-                if row_grid < num_rows + 1:
-                    ax = fig.add_subplot(gs[row_grid, col_grid])
-                    for spine in ax.spines.values():
-                        spine.set_visible(False)
-
-                    bbox = FancyBboxPatch(
-                        (0.01, 0.01), 0.98, 0.98,
-                        boxstyle="round,pad=0,rounding_size=0.02",
-                        edgecolor=BORDER_COLOR, facecolor='none',
-                        linewidth=0.5, transform=ax.transAxes, clip_on=False
-                    )
-                    ax.add_patch(bbox)
-
-                    display_text = f"{hall}{end_time}"
-                    t = ax.text(0.5, 0.5, display_text,
-                                fontweight='bold', ha='center', va='center',
-                                transform=ax.transAxes)
-                    
-                    current_size = 120
-                    while current_size > 1:
-                        t.set_fontsize(current_size)
-                        text_bbox = t.get_window_extent(renderer=fig.canvas.get_renderer())
-                        if text_bbox.width <= target_width_px:
-                            break
-                        current_size -= 2
-
-                    ax.set_xticks([])
-                    ax.set_yticks([])
-
-        ax_date = fig.add_subplot(gs[0, :])
-        ax_date.text(0.01, 0.5, f"{date_str} {title}",
-                     fontsize=date_fontsize * 0.5,
-                     color=DATE_COLOR, fontweight='bold',
-                     ha='left', va='center', transform=ax_date.transAxes)
-        for spine in ax_date.spines.values():
-            spine.set_visible(False)
-        ax_date.set_xticks([])
-        ax_date.set_yticks([])
-        ax_date.set_facecolor('none')
-
-    process_figure(png_fig)
-    process_figure(pdf_fig, is_pdf=True)
+    # --- Constants ---
+    A5_WIDTH_IN = 5.83
+    A5_HEIGHT_IN = 8.27
+    DPI = 300
+    NUM_COLS = 3
+
+    # --- Setup Figure ---
+    fig = plt.figure(figsize=(A5_WIDTH_IN, A5_HEIGHT_IN), dpi=DPI)
+    
+    # --- Font Setup ---
+    plt.rcParams['font.family'] = 'sans-serif'
+    plt.rcParams['font.sans-serif'] = ['Arial Unicode MS', 'Heiti TC', 'sans-serif']
+
 
+    # --- Data Preparation ---
+    total_items = len(data)
+    # Augment data with an original index for numbering
+    data_values_with_index = [(i, row) for i, row in enumerate(data.values.tolist())]
+    
+    # Pad data to be a multiple of NUM_COLS
+    padded_total = math.ceil(total_items / NUM_COLS) * NUM_COLS
+    while len(data_values_with_index) < padded_total:
+        data_values_with_index.append((None, ['', '']))
+
+    num_rows = padded_total // NUM_COLS
+
+    # --- Layout Calculation (Request 1) ---
+    if num_rows > 0:
+        # "A5 paper height / num_rows / 4 is the padding for all sides"
+        padding_in = (A5_HEIGHT_IN / num_rows / 4)
+        # Cap padding to prevent it from being excessively large
+        padding_in = min(padding_in, 0.5) 
+    else:
+        padding_in = 0.25 # Default padding if no rows
+
+    # Convert padding to relative figure coordinates for subplots_adjust
+    left_margin = padding_in / A5_WIDTH_IN
+    right_margin = 1 - left_margin
+    bottom_margin = padding_in / A5_HEIGHT_IN
+    top_margin = 1 - bottom_margin
+    
+    # Adjust overall figure margins
+    fig.subplots_adjust(left=left_margin, right=right_margin, top=top_margin, bottom=bottom_margin, hspace=0.4, wspace=0.4)
+
+    # --- Grid & Font Size ---
+    gs = gridspec.GridSpec(num_rows + 1, NUM_COLS, height_ratios=[0.2] + [1] * num_rows, figure=fig)
+
+    if num_rows > 0:
+        content_area_height_in = A5_HEIGHT_IN * (top_margin - bottom_margin)
+        cell_height_in = content_area_height_in / num_rows * (1 - fig.subplotpars.hspace)
+        base_fontsize = min(40, max(10, cell_height_in * 72 * 0.4)) # 72 pt/inch, 40% of cell height
+    else:
+        base_fontsize = 20
+
+    # --- Z-Sort (Column-major) Data for Layout ---
+    rows_per_col_layout = num_rows
+    sorted_data = [(None, ['',''])] * padded_total
+    for i, item_tuple in enumerate(data_values_with_index):
+        if item_tuple[0] is not None:
+            original_data_index = i # Index from the time-sorted list
+            row_in_col = original_data_index % rows_per_col_layout
+            col_idx = original_data_index // rows_per_col_layout
+            new_grid_index = row_in_col * NUM_COLS + col_idx
+            if new_grid_index < len(sorted_data):
+                sorted_data[new_grid_index] = item_tuple
+
+    # --- Drawing Logic ---
+    for grid_idx, item_tuple in enumerate(sorted_data):
+        original_index, (hall, end_time) = item_tuple
+        
+        if original_index is not None:
+            row_grid = grid_idx // NUM_COLS + 1 # +1 because date is in row 0
+            col_grid = grid_idx % NUM_COLS
+            
+            ax = fig.add_subplot(gs[row_grid, col_grid])
+            ax.set_axis_off()
+
+            # --- Cell Border (Request 2) & Content Area (Request 3) ---
+            # Draw a dotted rectangle. Content will be placed inside this.
+            # Making the rect slightly smaller creates a visual 90% area.
+            cell_border = Rectangle((0.05, 0.05), 0.9, 0.9,
+                                    edgecolor=BORDER_COLOR,
+                                    facecolor='none',
+                                    linestyle=(0, (1, 1.5)), # Dotted line with round caps
+                                    linewidth=1,
+                                    transform=ax.transAxes,
+                                    clip_on=False)
+            ax.add_patch(cell_border)
+
+            # --- Cell Content ---
+            display_text = f"{hall}{end_time}"
+            ax.text(0.5, 0.5, display_text,
+                    fontsize=base_fontsize,
+                    fontweight='bold',
+                    ha='center', va='center',
+                    transform=ax.transAxes)
+
+            # --- Cell Numbering (Request 4) ---
+            # Serial number is original_index + 1
+            ax.text(0.12, 0.82, str(original_index + 1),
+                    fontsize=base_fontsize * 0.5,
+                    color=SEQ_COLOR,
+                    fontweight='normal',
+                    ha='center', va='center',
+                    transform=ax.transAxes)
+
+    # --- Date Header ---
+    ax_date = fig.add_subplot(gs[0, :])
+    ax_date.set_axis_off()
+    ax_date.text(0, 0.5, f"{date_str} {title}",
+                 fontsize=base_fontsize * 0.6,
+                 color=DATE_COLOR,
+                 fontweight='bold',
+                 ha='left', va='center',
+                 transform=ax_date.transAxes)
+
+    # --- Save to Buffers ---
+    # Save PNG
     png_buffer = io.BytesIO()
-    png_fig.savefig(png_buffer, format='png', bbox_inches='tight', pad_inches=0.02)
+    fig.savefig(png_buffer, format='png', bbox_inches='tight', pad_inches=0.02)
     png_buffer.seek(0)
     png_base64 = base64.b64encode(png_buffer.getvalue()).decode()
-    plt.close(png_fig)
 
+    # Save PDF
     pdf_buffer = io.BytesIO()
-    with PdfPages(pdf_buffer) as pdf:
-        pdf.savefig(pdf_fig, bbox_inches='tight', pad_inches=0.02)
+    fig.savefig(pdf_buffer, format='pdf', bbox_inches='tight', pad_inches=0.02)
     pdf_buffer.seek(0)
     pdf_base64 = base64.b64encode(pdf_buffer.getvalue()).decode()
-    plt.close(pdf_fig)
+    
+    plt.close(fig)
 
     return {
         'png': f'data:image/png;base64,{png_base64}',
         'pdf': f'data:application/pdf;base64,{pdf_base64}'
     }
 
-# --- Generic Helper to Display PDF ---
 def display_pdf(base64_pdf):
-    """Generates the HTML to embed and display a PDF in Streamlit."""
-    pdf_display = f"""
-    <iframe src="{base64_pdf}" width="100%" height="800" type="application/pdf"></iframe>
-    """
+    """在Streamlit中嵌入显示PDF"""
+    pdf_display = f'<iframe src="{base64_pdf}" width="100%" height="800" type="application/pdf"></iframe>'
     return pdf_display
 
-# --- Main Streamlit App ---
-st.set_page_config(page_title="影院排期打印工具", layout="wide")
-st.title("影院排期打印工具")
+# --- Streamlit UI ---
+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(
-    "选择【放映时间核对表.xls】或【放映场次核对表.xls】文件",
-    accept_multiple_files=False,
-    type=["xls"]
-)
+uploaded_file = st.file_uploader("上传【放映场次核对表.xls】文件", type=["xls", "xlsx"])
 
 if uploaded_file:
-    with st.spinner("文件正在处理中，请稍候..."):
-        # --- Route to the correct processor based on filename ---
-
-        # 1. Logic for "LED 屏幕时间表打印"
-        if "放映时间核对表" in uploaded_file.name:
-            st.subheader("LED 屏幕时间表")
-            schedule, date_str = process_schedule_led(uploaded_file)
-            if schedule is not None:
-                output = create_print_layout_led(schedule, date_str)
-                if output:
-                    tab1, tab2 = st.tabs(["PDF 预览", "PNG 预览"])
-                    with tab1:
-                        st.markdown(display_pdf(output['pdf']), unsafe_allow_html=True)
-                    with tab2:
-                        st.image(output['png'], use_container_width=True)
-                else:
-                    st.info("没有可显示的数据。")
+    # Use new column name 'EndTime_formatted' for display
+    part1, part2, date_str = process_schedule(uploaded_file)
+    if part1 is not None and part2 is not None:
+        part1_data_for_layout = part1[['Hall', 'EndTime_formatted']]
+        part2_data_for_layout = part2[['Hall', 'EndTime_formatted']]
+        
+        part1_output = create_print_layout(part1_data_for_layout, "A", date_str)
+        part2_output = create_print_layout(part2_data_for_layout, "C", date_str)
+
+        col1, col2 = st.columns(2)
+
+        with col1:
+            st.subheader("白班散场预览（散场时间 ≤ 17:30）")
+            if part1_output:
+                tab1_1, tab1_2 = st.tabs(["PDF 预览", "PNG 预览"])
+                with tab1_1:
+                    st.markdown(display_pdf(part1_output['pdf']), unsafe_allow_html=True)
+                with tab1_2:
+                    st.image(part1_output['png'])
             else:
-                st.error("无法处理文件，请检查文件格式或内容是否正确。")
-
-        # 2. Logic for "散厅时间快捷打印"
-        elif "放映场次核对表" in uploaded_file.name:
-            part1_data, part2_data, date_str = process_schedule_quick(uploaded_file)
-
-            if part1_data is not None and part2_data is not None:
-                part1_output = create_print_layout_quick(part1_data, "A", date_str)
-                part2_output = create_print_layout_quick(part2_data, "C", date_str)
-
-                col1, col2 = st.columns(2)
-
-                with col1:
-                    st.subheader("白班散场预览（时间 ≤ 17:30）")
-                    if part1_output:
-                        tab1_1, tab1_2 = st.tabs(["PDF 预览 ", "PNG 预览 "]) # Added space to make keys unique
-                        with tab1_1:
-                            st.markdown(display_pdf(part1_output['pdf']), unsafe_allow_html=True)
-                        with tab1_2:
-                            st.image(part1_output['png'])
-                    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_output:
-                        tab2_1, tab2_2 = st.tabs(["PDF 预览  ", "PNG 预览  "]) # Added spaces to make keys unique
-                        with tab2_1:
-                            st.markdown(display_pdf(part2_output['pdf']), unsafe_allow_html=True)
-                        with tab2_2:
-                            st.image(part2_output['png'])
-                    else:
-                        st.info("夜班部分没有数据")
+                st.info("白班部分没有数据")
+
+        with col2:
+            st.subheader("夜班散场预览（散场时间 > 17:30）")
+            if part2_output:
+                tab2_1, tab2_2 = st.tabs(["PDF 预览", "PNG 预览"])
+                with tab2_1:
+                    st.markdown(display_pdf(part2_output['pdf']), unsafe_allow_html=True)
+                with tab2_2:
+                    st.image(part2_output['png'])
             else:
-                st.error("无法处理文件，请检查文件格式或内容是否正确。")
-        
-        # 3. Fallback for incorrect file
-        else:
-            st.warning("文件名不匹配。请上传名为【放映时间核对表.xls】或【放映场次核对表.xls】的文件。")
+                st.info("夜班部分没有数据")