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 Rectangle # Replaced FancyBboxPatch # --- 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 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() # 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 ) # 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['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_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_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 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 # --- 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() 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() # Save PDF pdf_buffer = io.BytesIO() 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(fig) 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""" pdf_display = f'' return pdf_display # --- 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("上传【放映场次核对表.xls】文件", type=["xls", "xlsx"]) if uploaded_file: # 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.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.info("夜班部分没有数据")