Create app.py

app.py

@@ -0,0 +1,282 @@
+import pandas as pd
+import streamlit as st
+from datetime import datetime, timedelta
+import matplotlib.pyplot as plt
+import io
+import base64
+import matplotlib.gridspec as gridspec
+import math
+from matplotlib.backends.backend_pdf import PdfPages # 新增导入
+
+SPLIT_TIME = "17:30"
+BUSINESS_START = "09:30"
+BUSINESS_END = "01:30"
+BORDER_COLOR = '#A9A9A9'
+DATE_COLOR = '#A9A9A9'
+
+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:
+        # 读取 Excel，跳过前 8 行
+        df = pd.read_excel(file, skiprows=8)
+        
+        # 提取所需列 (G9, H9, J9)
+        df = df.iloc[:, [6, 7, 9]]  # G, H, J 列
+        df.columns = ['Hall', 'StartTime', 'EndTime']
+        
+        # 清理数据
+        df = df.dropna(subset=['Hall', 'StartTime', 'EndTime'])
+        
+        # 转换影厅格式为 "#号" 格式
+        df['Hall'] = df['Hall'].str.extract(r'(\d+)号').astype(str) + ' '
+        
+        # 保存原始时间字符串用于诊断
+        df['original_end'] = df['EndTime']
+        
+        # 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'])
+        
+        # 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')
+        
+        # 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 (PNG 和 PDF)"""
+    if data.empty:
+        return None
+
+    # --- 创建 PNG 图形 ---
+    png_fig = plt.figure(figsize=(5.83, 8.27), dpi=300) # A5 竖向
+    png_ax_container = png_fig.add_subplot(111) # 创建一个容器轴，用于隐藏外部边框
+    png_ax_container.set_axis_off()
+    png_fig.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
+
+    # --- 创建 PDF 图形 ---
+    pdf_fig = plt.figure(figsize=(5.83, 8.27), dpi=300) # A5 竖向
+    pdf_ax_container = pdf_fig.add_subplot(111)
+    pdf_ax_container.set_axis_off()
+    pdf_fig.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
+
+    # --- 内部绘图函数 ---
+    def process_figure(fig, is_pdf=False):
+        # 设置字体
+        plt.rcParams['font.family'] = 'sans-serif'
+        plt.rcParams['font.sans-serif'] = ['Arial Unicode MS'] # 确保字体可用
+
+        # 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 (在 figure 内部创建)
+        gs = gridspec.GridSpec(num_rows + 1, num_cols, hspace=0.1, wspace=0.1, height_ratios=[0.2] + [1] * num_rows, figure=fig) # 将日期行放在顶部
+
+        # 调整基础字体大小，避免过大或过小
+        # A5 宽度大约 1749 像素 @ 300dpi, 高度 2481
+        # 每列宽度约 1749 * 0.9 / 3 = 525 像素
+        # 每行高度约 (2481 * 0.9 * (1 / (1.2))) / num_rows
+        # 字体大小与单元格大小相关，这里用经验值调整
+        available_height_per_row = (8.27 * 0.9 * (1 / 1.2)) / num_rows if num_rows > 0 else 1
+        base_fontsize = min(40, max(10, available_height_per_row * 72 * 0.5)) # 72 points per inch, 估算系数
+
+        data_values = data.values.tolist()
+
+        # 补全空位，确保是3的倍数
+        while len(data_values) % num_cols != 0:
+            data_values.append(['', ''])
+
+        rows_per_col_layout = math.ceil(len(data_values) / num_cols) # 按列优先排列的行数
+
+        # 按列优先排序数据 (Z字形)
+        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
+
+        # 绘制数据单元格
+        for idx, (hall, end_time) in enumerate(sorted_data):
+            if hall and end_time:
+                row_grid = idx // num_cols + 1 # +1 因为日期占了第0行
+                col_grid = idx % num_cols
+
+                if row_grid < num_rows + 1: # 确保索引在网格内
+                    ax = fig.add_subplot(gs[row_grid, col_grid]) # 使用 fig.add_subplot
+
+                    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',
+                            transform=ax.transAxes) # 使用相对坐标
+
+                    ax.set_xticks([])
+                    ax.set_yticks([])
+                else:
+                     print(f"Warning: Index out of bounds - idx={idx}, row_grid={row_grid}, col_grid={col_grid}")
+
+
+        # 添加日期信息到第一个子图的顶部
+        ax_date = fig.add_subplot(gs[0, :]) # 跨越第一行的所有列
+        ax_date.text(0.01, 0.5, f"{date_str} {title}", # 调整位置和对齐
+                     fontsize=base_fontsize * 0.5, # 调整日期字体大小
+                     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') # 使背景透明
+
+
+    # --- 处理图形 ---
+    process_figure(png_fig)
+    process_figure(pdf_fig, is_pdf=True)
+
+    # --- 保存 PNG ---
+    png_buffer = io.BytesIO()
+    png_fig.savefig(png_buffer, format='png', bbox_inches='tight', pad_inches=0.05)
+    png_buffer.seek(0)
+    png_base64 = base64.b64encode(png_buffer.getvalue()).decode()
+    plt.close(png_fig)
+
+    # --- 保存 PDF ---
+    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,{png_base64}',
+        'pdf': f'data:application/pdf;base64,{pdf_base64}'
+    }
+
+# --- 新增 PDF 显示函数 ---
+def display_pdf(base64_pdf):
+    """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
+
+# 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"])
+
+if uploaded_file:
+    part1, part2, date_str = process_schedule(uploaded_file)
+
+    if part1 is not None and part2 is not None:
+        # 生成包含 PNG 和 PDF 的字典
+        part1_output = create_print_layout(part1, "A", date_str)
+        part2_output = 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_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.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"])
+                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")
+
+