Update app.py

app.py

@@ -1,429 +1,165 @@
-import pandas as pd
 import streamlit as st
-import matplotlib.pyplot as plt
-import matplotlib.font_manager as font_manager
-from matplotlib.lines import Line2D
-import io
-import base64
-import os
-from datetime import datetime, timedelta
-from pypinyin import lazy_pinyin, Style
-from matplotlib.backends.backend_pdf import PdfPages
-import matplotlib.gridspec as gridspec
-import math
-
-# --- 常量定义 ---
-SPLIT_TIME = "17:00"
-BUSINESS_START = "09:30"
-BUSINESS_END = "01:30"
-BORDER_COLOR = 'grey'
-DATE_COLOR = '#A9A9A9'
-A5_WIDTH_IN = 5.83
-A5_HEIGHT_IN = 8.27
-NUM_COLS = 3
-
-# --- 字体加载与文本处理函数 ---
-
-def get_font_regular(size=14):
-    """加载思源黑体-常规 (SimHei.ttf)"""
-    font_path = "SimHei.ttf"
-    if os.path.exists(font_path):
-        return font_manager.FontProperties(fname=font_path, size=size)
-    else:
-        st.warning("警告：未找到字体文件 'SimHei.ttf'，LED屏排片表显示可能不正确。")
-        return font_manager.FontProperties(family='sans-serif', size=size)
-
-def get_font_bold(size=14):
-    """加载思源黑体-粗体 (SourceHanSansOLD-Heavy-2.otf)"""
-    font_path = "SourceHanSansOLD-Heavy-2.otf"
-    if os.path.exists(font_path):
-        return font_manager.FontProperties(fname=font_path, size=size)
-    else:
-        st.warning("警告：未找到字体文件 'SourceHanSansOLD-Heavy-2.otf'，散场时间表显示可能不正确。")
-        return font_manager.FontProperties(family='sans-serif', size=size, weight='bold')
-
-def get_pinyin_abbr(text):
-    """获取中文文本前两个字的拼音首字母"""
-    if not text:
-        return ""
-    chars = [c for c in text if '\u4e00' <= c <= '\u9fff'][:2]
-    if not chars:
-        return ""
-    pinyin_list = lazy_pinyin(chars, style=Style.FIRST_LETTER)
-    return ''.join(pinyin_list).upper()
-
-def format_seq(n):
-    """将数字转换为带圈序号 (①, ②, ③...)"""
-    if not isinstance(n, int) or n <= 0:
-        return str(n)
-    circled_chars = "①②③④⑤⑥⑦⑧⑨⑩⑪⑫⑬⑭⑮⑯⑰⑱⑲⑳" \
-                      "㉑㉒㉓㉔㉕㉖㉗㉘㉙㉚㉛㉜㉝㉞㉟" \
-                      "㊱㊲㊳㊴㊵㊶㊷㊸㊹㊺㊻㊼㊽㊾㊿"
-    if 1 <= n <= 50:
-        return circled_chars[n - 1]
-    return f'({n})'
-
-# --- '放映时间核对表' 处理函数 ---
-def process_schedule_led(file):
-    """处理 '放映时间核对表.xls' 文件"""
+import pandas as pd
+import numpy as np
+
+# 设置页面布局为宽屏模式，并设置页面标题
+st.set_page_config(layout="wide", page_title="影城效率分析 - 最终版")
+
+
+def clean_movie_title(title):
+    """
+    清理并规范化电影标题，移除版本、语言等标识以便合并统计。
+    """
+    if not isinstance(title, str):
+        return title
+    suffixes_to_remove = [
+        '2D', '3D', '4D', '4K', 'IMAX', 'CINITY', '杜比', '巨幕',
+        '国语', '英语', '粤语', '日语', '原版', '修复版',
+        '(国)', '(英)', '(粤)'
+    ]
+    parts = title.split()
+    cleaned_parts = [p for p in parts if p.upper() not in [s.upper() for s in suffixes_to_remove]]
+    if not cleaned_parts:
+        return title
+    return ' '.join(cleaned_parts).strip()
+
+
+def style_efficiency(row):
+    """
+    根据效率值高亮特定行。
+    如果座次效率或场次效率 < 0.5 或 > 1.5，则高亮为淡黄色。
+    """
+    highlight = 'background-color: #FFFFE0;'
+    default = ''
+    seat_efficiency = row.get('座次效率', 0)
+    session_efficiency = row.get('场次效率', 0)
+    if (seat_efficiency < 0.5 or seat_efficiency > 1.5 or
+            session_efficiency < 0.5 or session_efficiency > 1.5):
+        return [highlight] * len(row)
+    return [default] * len(row)
+
+
+def process_and_analyze_data(df):
+    """
+    核心数据处理与分析函数。
+    """
+    if df.empty:
+        return pd.DataFrame()
+
+    analysis_df = df.groupby('影片名称_清理后').agg(
+        座位数=('座位数', 'sum'),
+        场次=('影片名称_清理后', 'size'),
+        票房=('总收入', 'sum'),
+        人次=('总人次', 'sum')
+    ).reset_index()
+    analysis_df.rename(columns={'影片名称_清理后': '影片'}, inplace=True)
+
+    analysis_df = analysis_df.sort_values(by='票房', ascending=False).reset_index(drop=True)
+
+    total_seats = analysis_df['座位数'].sum()
+    total_sessions = analysis_df['场次'].sum()
+    total_revenue = analysis_df['票房'].sum()
+
+    analysis_df['均价'] = np.divide(analysis_df['票房'], analysis_df['人次']).fillna(0)
+    analysis_df['座次比'] = np.divide(analysis_df['座位数'], total_seats).fillna(0)
+    analysis_df['场次比'] = np.divide(analysis_df['场次'], total_sessions).fillna(0)
+    analysis_df['票房比'] = np.divide(analysis_df['票房'], total_revenue).fillna(0)
+    analysis_df['座次效率'] = np.divide(analysis_df['票房比'], analysis_df['座次比']).fillna(0)
+    analysis_df['场次效率'] = np.divide(analysis_df['票房比'], analysis_df['场次比']).fillna(0)
+
+    # **优化1：移除“序号”列的定义**
+    final_columns = [
+        '影片', '座位数', '场次', '票房', '人次', '均价',
+        '座次比', '场次比', '票房比', '座次效率', '场次效率'
+    ]
+    analysis_df = analysis_df[final_columns]
+
+    return analysis_df
+
+
+# --- Streamlit 用户界面 ---
+
+st.title('排片效率分析')
+st.write("上传 `影片映出日累计报表.xlsx` 文件。")
+
+uploaded_file = st.file_uploader("请在此处上传 Excel 文件", type=['xlsx', 'xls', 'csv'])
+
+if uploaded_file is not None:
     try:
-        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:
-        date_str = datetime.today().strftime('%Y-%m-%d')
-        base_date = datetime.today().date()
+        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']
+        df = df[required_cols]
+        df.dropna(subset=['影片名称', '放映时间'], inplace=True)
+
+        for col in ['座位数', '总收入', '总人次']:
+            df[col] = pd.to_numeric(df[col], errors='coerce').fillna(0)
+
+        df['放映时间'] = pd.to_datetime(df['放映时间'], format='%H:%M:%S', errors='coerce').dt.time
+        df.dropna(subset=['放映时间'], inplace=True)
+
+        df['影片名称_清理后'] = df['影片名称'].apply(clean_movie_title)
+
+        st.toast("文件上传成功，数据已按规则处理！", icon="🎉")
+
+        format_config = {
+            '座位数': '{:,.0f}', '场次': '{:,.0f}', '人次': '{:,.0f}',
+            '票房': '{:,.2f}', '均价': '{:.2f}', '座次比': '{:.2%}', '场次比': '{:.2%}',
+            '票房比': '{:.2%}', '座次效率': '{:.2f}', '场次效率': '{:.2f}',
+        }
+
+        # --- 1. 全天数据分析 ---
+        st.header("全天排片效率分析")
+
+        full_day_analysis = process_and_analyze_data(df.copy())
+
+        if not full_day_analysis.empty:
+            table_height = (len(full_day_analysis) + 1) * 35 + 3
+            # **优化2：使用 .hide(axis="index") 隐藏默认序号列**
+            st.dataframe(
+                full_day_analysis.style.format(format_config).apply(style_efficiency, axis=1).hide(axis="index"),
+                height=table_height,
+                use_container_width=True
+            )
+        else:
+            st.warning("全天数据不足，无法生成分析报告。")
+
+        # --- 2. 黄金时段数据分析 ---
+        st.header("黄金时段 (14:00 - 21:00) 排片效率分析")
+
+        start_time = pd.to_datetime('14:00:00').time()
+        end_time = pd.to_datetime('21:00:00').time()
+        prime_time_df = df[df['放映时间'].between(start_time, end_time)]
+
+        prime_time_analysis = process_and_analyze_data(prime_time_df.copy())
+
+        if not prime_time_analysis.empty:
+            table_height_prime = (len(prime_time_analysis) + 1) * 35 + 3
+            # **优化2：同样隐藏黄金时段表格的默认序号**
+            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
+            )
+        else:
+            st.warning("黄金时段内没有有效场次数据，无法生成分析报告。")
+
+        # --- 3. 一键复制影片列表 ---
+        if not full_day_analysis.empty:
+            st.header("复制当日影片列表")
+
+            movie_titles = full_day_analysis['影片'].tolist()
+            formatted_titles = ''.join([f'《{title}》' for title in movie_titles])
+
+            st.code(formatted_titles, language='text')
 
-    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)')
-        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'])
-        merged_rows = []
-        for _, group in df.groupby('Hall'):
-            current = None
-            for _, row in group.sort_values('StartTime_dt').iterrows():
-                if current is None:
-                    current = row.copy()
-                elif 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)
-        merged_df['StartTime_dt'] -= timedelta(minutes=10)
-        merged_df['EndTime_dt'] -= timedelta(minutes=5)
-        merged_df['Seq'] = merged_df.groupby('Hall').cumcount() + 1
-        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', 'Seq', 'Movie', 'StartTime_str', 'EndTime_str']], date_str
-    except Exception as e:
-        st.error(f"处理数据出错: {e}。请检查文件格式是否正确。")
-        return None, date_str
-
-def create_print_layout_led(data, date_str):
-    """为 '放映时间核对表' 生成打印布局 (使用 Regular 字体)"""
-    if data is None or data.empty:
-        return None
-    A4_width_in, A4_height_in = 8.27, 11.69
-    dpi = 300
-    total_content_rows = len(data)
-    
-    # --- 已修改部分：如果数据条数小于25条，则按25条计算行高以防止字体过大 ---
-    layout_rows = max(total_content_rows, 25)
-    totalA = layout_rows + 2
-    # --- 修改结束 ---
-
-    row_height = A4_height_in / totalA
-    data = data.reset_index(drop=True)
-    data['hall_str'] = '$' + data['Hall'].str.replace('号', '') + '^{\#}$'
-    data['seq_str'] = data['Seq'].apply(format_seq)
-    data['pinyin_abbr'] = data['Movie'].apply(get_pinyin_abbr)
-    data['time_str'] = data['StartTime_str'] + ' - ' + data['EndTime_str']
-    
-    temp_fig = plt.figure(figsize=(A4_width_in, A4_height_in), dpi=dpi)
-    renderer = temp_fig.canvas.get_renderer()
-    base_font_size_pt = (row_height * 0.9) * 72
-    seq_font_size_pt = (row_height * 0.5) * 72
-
-    def get_col_width_in(series, font_size_pt, is_math=False):
-        if series.empty: return 0
-        font_prop = get_font_regular(font_size_pt) # 使用 Regular 字体
-        longest_str_idx = series.astype(str).str.len().idxmax()
-        max_content = str(series.loc[longest_str_idx])
-        text_width_px, _, _ = renderer.get_text_width_height_descent(max_content, font_prop, ismath=is_math)
-        return (text_width_px / dpi) * 1.1
-
-    margin_col_width = row_height
-    hall_col_width = get_col_width_in(data['hall_str'], base_font_size_pt, is_math=True)
-    seq_col_width = get_col_width_in(data['seq_str'], seq_font_size_pt)
-    pinyin_col_width = get_col_width_in(data['pinyin_abbr'], base_font_size_pt)
-    time_col_width = get_col_width_in(data['time_str'], base_font_size_pt)
-    movie_col_width = A4_width_in - (
-        margin_col_width * 2 + hall_col_width + seq_col_width + pinyin_col_width + time_col_width)
-    plt.close(temp_fig)
-    
-    col_widths = {'hall': hall_col_width, 'seq': seq_col_width, 'movie': movie_col_width, 'pinyin': pinyin_col_width,
-                  'time': time_col_width}
-    col_x_starts = {}
-    current_x = margin_col_width
-    for col_name in ['hall', 'seq', 'movie', 'pinyin', 'time']:
-        col_x_starts[col_name] = current_x
-        current_x += col_widths[col_name]
-
-    def draw_figure(fig, ax):
-        renderer = fig.canvas.get_renderer()
-        for col_name in ['hall', 'seq', 'movie', 'pinyin']:
-            x_line = col_x_starts[col_name] + col_widths[col_name]
-            line_top_y, line_bottom_y = A4_height_in - row_height, row_height
-            ax.add_line(Line2D([x_line, x_line], [line_bottom_y, line_top_y], color='gray', linestyle=':', linewidth=0.5))
-        
-        last_hall_drawn = None
-        for i, row in data.iterrows():
-            y_bottom = A4_height_in - (i + 2) * row_height
-            y_center = y_bottom + row_height / 2
-            
-            if row['Hall'] != last_hall_drawn:
-                ax.text(col_x_starts['hall'] + col_widths['hall'] / 2, y_center, row['hall_str'],
-                        fontproperties=get_font_regular(base_font_size_pt), ha='center', va='center')
-                last_hall_drawn = row['Hall']
-            
-            ax.text(col_x_starts['seq'] + col_widths['seq'] / 2, y_center, row['seq_str'],
-                    fontproperties=get_font_regular(seq_font_size_pt), ha='center', va='center')
-            ax.text(col_x_starts['pinyin'] + col_widths['pinyin'] / 2, y_center, row['pinyin_abbr'],
-                    fontproperties=get_font_regular(base_font_size_pt), ha='center', va='center')
-            ax.text(col_x_starts['time'] + col_widths['time'] / 2, y_center, row['time_str'],
-                    fontproperties=get_font_regular(base_font_size_pt), ha='center', va='center')
-            
-            movie_font_size = base_font_size_pt
-            movie_font_prop = get_font_regular(movie_font_size)
-            text_w_px, _, _ = renderer.get_text_width_height_descent(row['Movie'], movie_font_prop, ismath=False)
-            text_w_in = text_w_px / dpi
-            max_width_in = col_widths['movie'] * 0.9
-            
-            if text_w_in > max_width_in:
-                movie_font_size *= (max_width_in / text_w_in)
-                movie_font_prop = get_font_regular(movie_font_size)
-            
-            ax.text(col_x_starts['movie'] + 0.05, y_center, row['Movie'], fontproperties=movie_font_prop, ha='left', va='center')
-            
-            is_last_in_hall = (i == len(data) - 1) or (row['Hall'] != data.loc[i + 1, 'Hall'])
-            line_start_x = margin_col_width
-            line_end_x = A4_width_in - margin_col_width
-            if is_last_in_hall:
-                ax.add_line(Line2D([line_start_x, line_end_x], [y_bottom, y_bottom], color='black', linestyle='-', linewidth=0.8))
-            else:
-                ax.add_line(Line2D([line_start_x, line_end_x], [y_bottom, y_bottom], color='gray', linestyle=':', linewidth=0.5))
-
-    outputs = {}
-    for format_type in ['png', 'pdf']:
-        fig = plt.figure(figsize=(A4_width_in, A4_height_in), dpi=dpi)
-        ax = fig.add_axes([0, 0, 1, 1])
-        ax.set_axis_off()
-        ax.set_xlim(0, A4_width_in)
-        ax.set_ylim(0, A4_height_in)
-        ax.text(margin_col_width, A4_height_in - (row_height / 2), date_str,
-                fontproperties=get_font_regular(10), color='#A9A9A9', ha='left', va='center')
-        
-        draw_figure(fig, ax)
-        
-        buf = io.BytesIO()
-        fig.savefig(buf, format=format_type, dpi=dpi, bbox_inches='tight', pad_inches=0)
-        buf.seek(0)
-        data_uri = base64.b64encode(buf.getvalue()).decode()
-        mime_type = 'image/png' if format_type == 'png' else 'application/pdf'
-        outputs[format_type] = f"data:{mime_type};base64,{data_uri}"
-        plt.close(fig)
-        
-    return outputs
-
-# --- '放映场次核对表' 处理函数 ---
-def process_schedule_times(file):
-    """处理 '放映场次核对表.xls' 文件"""
-    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) + ' '
-        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()))))
-        df = df[valid_times]
-
-        df = df.sort_values('EndTime')
-        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()
-
-        for part in [part1, part2]:
-            part['EndTime'] = part['EndTime'].dt.strftime('%-H:%M')
-
-        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):
-                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"处理文件出错: {str(e)}")
-        return None, None, None
-
-def create_print_layout_times(data, title, date_str):
-    """为 '放映场次核对表' 生成打印布局 (使用 Bold 字体)"""
-    if data.empty:
-        return None
-
-    def generate_figure():
-        total_items = len(data)
-        num_rows = math.ceil(total_items / NUM_COLS) if total_items > 0 else 1
-        date_header_height_in = 0.3
-        data_area_height_in = A5_HEIGHT_IN - date_header_height_in
-        cell_width_in = A5_WIDTH_IN / NUM_COLS
-        cell_height_in = data_area_height_in / num_rows
-        cell_width_pt = cell_width_in * 72
-        cell_height_pt = cell_height_in * 72
-        target_text_width_pt = cell_width_pt * 0.9
-        fontsize_from_width = target_text_width_pt / (8 * 0.6)
-        fontsize_from_height = cell_height_pt * 0.8
-        base_fontsize = min(fontsize_from_width, fontsize_from_height)
-        
-        fig = plt.figure(figsize=(A5_WIDTH_IN, A5_HEIGHT_IN), dpi=300)
-        fig.subplots_adjust(left=0, right=1, top=1, bottom=0)
-        
-        gs = gridspec.GridSpec(
-            num_rows + 1, NUM_COLS,
-            hspace=0, wspace=0,
-            height_ratios=[date_header_height_in] + [cell_height_in] * num_rows,
-            figure=fig)
-        
-        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
-                ax = fig.add_subplot(gs[row_grid, col_grid])
-                for spine in ax.spines.values():
-                    spine.set_visible(True)
-                    spine.set_linestyle((0, (1, 2)))
-                    spine.set_color(BORDER_COLOR)
-                    spine.set_linewidth(0.75)
-                
-                display_text = f"{hall}{end_time}"
-                ax.text(0.5, 0.5, display_text,
-                        fontproperties=get_font_bold(base_fontsize), # 使用 Bold 字体
-                        ha='center', va='center',
-                        transform=ax.transAxes)
-                ax.set_xticks([])
-                ax.set_yticks([])
-                ax.set_facecolor('none')
-        
-        ax_date = fig.add_subplot(gs[0, :])
-        ax_date.text(0.01, 0.5, f"{date_str} {title}",
-                     fontproperties=get_font_bold(base_fontsize * 0.5), # 使用 Bold 字体
-                     color=DATE_COLOR,
-                     ha='left', va='center',
-                     transform=ax_date.transAxes)
-        ax_date.set_axis_off()
-        ax_date.set_facecolor('none')
-        
-        return fig
-
-    fig_for_output = generate_figure()
-    png_buffer = io.BytesIO()
-    fig_for_output.savefig(png_buffer, format='png')
-    png_buffer.seek(0)
-    png_base64 = base64.b64encode(png_buffer.getvalue()).decode()
-    
-    pdf_buffer = io.BytesIO()
-    with PdfPages(pdf_buffer) as pdf:
-        pdf.savefig(fig_for_output)
-    pdf_buffer.seek(0)
-    pdf_base64 = base64.b64encode(pdf_buffer.getvalue()).decode()
-    
-    plt.close(fig_for_output)
-    return {'png': f'data:image/png;base64,{png_base64}', 'pdf': f'data:application/pdf;base64,{pdf_base64}'}
-
-def display_pdf(base64_pdf):
-    """在Streamlit中嵌入显示PDF"""
-    return f'<iframe src="{base64_pdf}" width="100%" height="800" type="application/pdf"></iframe>'
-
-# --- Streamlit 主程序 ---
-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")
-
-uploaded_file = st.file_uploader("请上传 '放映时间核对表.xls' 或 '放映场次核对表.xls'",
-                                 type=["xls", "xlsx"])
-
-if uploaded_file:
-    # 根据文件名中的关键字判断使用哪个处理流程
-    if "时间" in uploaded_file.name:
-        st.header("LED屏排片表")
-        with st.spinner("正在处理文件，请稍候..."):
-            schedule, date_str = process_schedule_led(uploaded_file)
-            if schedule is not None and not schedule.empty:
-                output = create_print_layout_led(schedule, date_str)
-                tab1, tab2 = st.tabs(["PDF 预览", "图片预览 (PNG)"])
-                with tab1:
-                    st.markdown(display_pdf(output['pdf']), unsafe_allow_html=True)
-                with tab2:
-                    st.image(output['png'], use_container_width=True)
-            else:
-                st.error("无法处理文件。请检查文件内容和格式是否正确。")
-                
-    elif "场次" in uploaded_file.name:
-        st.header("散场时间快捷打印")
-        part1, part2, date_str = process_schedule_times(uploaded_file)
-        if part1 is not None and part2 is not None:
-            part1_output = create_print_layout_times(part1, "A", date_str)
-            part2_output = create_print_layout_times(part2, "C", date_str)
-            
-            col1, col2 = st.columns(2)
-            with col1:
-                st.subheader("白班 (散场时间 ≤ 17:00)")
-                if part1_output:
-                    tab1_1, tab1_2 = st.tabs(["PDF 预览 ", "图片预览 (PNG) "]) 
-                    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("白班没有排期数据。")
-
-            with col2:
-                st.subheader("晚班 (散场时间 > 17:00)")
-                if part2_output:
-                    tab2_1, tab2_2 = st.tabs(["PDF 预览  ", "图片预览 (PNG)  "])
-                    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("晚班没有排期数据。")
+        st.error(f"处理文件时出错: {e}")
+        st.warning("请确保上传的文件是'影片映出日累计报表.xlsx'，并且格式正确。")
+
+else:
+    st.info("请上传文件以开始分析。")