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 from matplotlib.patches import FancyBboxPatch # 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() # 减小边距，例如从 0.05 减小到 0.02 png_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02) # --- 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() # 减小边距，例如从 0.05 减小到 0.02 pdf_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02) # --- 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) # 减小子图间距 hspace/wspace，减小日期行高度比例 height_ratios gs = gridspec.GridSpec(num_rows + 1, num_cols, hspace=0.05, wspace=0.05, height_ratios=[0.1] + [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 # --- 修改开始：绘制圆角矩形 --- # 隐藏原始边框 for spine in ax.spines.values(): spine.set_visible(False) # 创建圆角矩形 Patch bbox = FancyBboxPatch( (0.01, 0.01), # 左下角坐标 (稍微内缩一点避免接触边缘) 0.98, 0.98, # 宽度和高度 (占满大部分区域) boxstyle="round,pad=0,rounding_size=0.02", # 圆角样式，rounding_size 控制圆角程度 edgecolor=BORDER_COLOR, facecolor='none', # 无填充色 linewidth=0.5, transform=ax.transAxes, # 使用相对坐标 clip_on=False # 避免被裁剪 ) # 添加 Patch 到 Axes ax.add_patch(bbox) # --- 修改结束 --- 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() # 可以尝试减小 pad_inches， even set to 0 png_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) # --- 保存 PDF --- pdf_buffer = io.BytesIO() with PdfPages(pdf_buffer) as pdf: # 可以尝试减小 pad_inches， even set to 0 pdf.savefig(pdf_fig, bbox_inches='tight', pad_inches=0.02) 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'' 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")