app.py

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

# Constants
SPLIT_TIME = "17:30"
BUSINESS_START = "09:30"
BUSINESS_END = "01:30"
BORDER_COLOR = 'grey' # Changed to grey for the new border
DATE_COLOR = '#A9A9A9'
A5_WIDTH_IN = 5.83
A5_HEIGHT_IN = 8.27
NUM_COLS = 3


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('%-H:%M')

        # 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):
    """创建精确的 A5 表格打印布局 (PNG 和 PDF)"""
    if data.empty:
        return None

    # --- 内部绘图函数 ---
    def generate_figure():
        # --- 1. 计算布局和字体大小 ---
        total_items = len(data)
        num_rows = math.ceil(total_items / NUM_COLS) if total_items > 0 else 1

        # 定义日期标题行的高度（英寸），数据行将填充剩余空间
        date_header_height_in = 0.3
        data_area_height_in = A5_HEIGHT_IN - date_header_height_in

        # 计算每个数据单元格的尺寸（英寸）
        cell_width_in = A5_WIDTH_IN / NUM_COLS
        cell_height_in = data_area_height_in / num_rows

        # 将单元格宽度转换为点（1 英寸 = 72 点）
        cell_width_pt = cell_width_in * 72
        cell_height_pt = cell_height_in * 72

        # --- 动态字体大小计算 ---
        # 目标：文本总宽度为单元格宽度的 90%
        target_text_width_pt = cell_width_pt * 0.9
        # 启发式估算：假设最长文本为 "10 23:59" (8个字符)，平均字符宽度约为字体大小的0.6倍
        # FONT_SIZE = target_width / (num_chars * avg_char_width_factor)
        fontsize_from_width = target_text_width_pt / (8 * 0.6)
        # 字体高度不能超过单元格高度（留出20%的垂直边距）
        fontsize_from_height = cell_height_pt * 0.8
        # 选择两者中较小的一个，以确保文本能完全容纳
        base_fontsize = min(fontsize_from_width, fontsize_from_height)

        # --- 2. 创建图形和网格 ---
        fig = plt.figure(figsize=(A5_WIDTH_IN, A5_HEIGHT_IN), dpi=300)
        # 设置无边距，让网格填满整个图纸
        fig.subplots_adjust(left=0, right=1, top=1, bottom=0)

        # 设置字体
        plt.rcParams['font.family'] = 'sans-serif'
        plt.rcParams['font.sans-serif'] = ['Arial Unicode MS'] # 确保字体可用

        # 创建网格，顶部为日期行，下方为数据行
        # 使用高度（英寸）作为比率，GridSpec会自动归一化
        gs = gridspec.GridSpec(
            num_rows + 1, NUM_COLS,
            hspace=0, wspace=0, # 无单元格间距
            height_ratios=[date_header_height_in] + [cell_height_in] * num_rows,
            figure=fig
        )

        # --- 3. 补全和排序数据 ---
        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

        # --- 4. 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 因为日期行占了第0行
                col_grid = idx % NUM_COLS

                ax = fig.add_subplot(gs[row_grid, col_grid])

                # --- 设置点状虚线边框 ---
                for spine in ax.spines.values():
                    spine.set_visible(True)
                    spine.set_linestyle((0, (1, 2)))  # 点状线: (offset, (on_length, off_length))
                    spine.set_color(BORDER_COLOR)
                    spine.set_linewidth(0.75) # 点状线可能需要稍粗一点才清晰

                # 绘制居中对齐的文本
                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)

                ax.set_xticks([])
                ax.set_yticks([])
                ax.set_facecolor('none')

        # --- 5. 绘制日期标题 ---
        ax_date = fig.add_subplot(gs[0, :])
        ax_date.text(0.01, 0.5, f"{date_str} {title}",
                     fontsize=base_fontsize * 0.5, # 日期字体稍小
                     color=DATE_COLOR, fontweight='bold',
                     ha='left', va='center',
                     transform=ax_date.transAxes)
        ax_date.set_axis_off() # 完全隐藏日期行的边框和刻度
        ax_date.set_facecolor('none')

        return fig

    # --- 生成并保存图形 ---
    fig_for_output = generate_figure()

    # 保存为 PNG
    png_buffer = io.BytesIO()
    fig_for_output.savefig(png_buffer, format='png') # 无需 bbox_inches='tight'
    png_buffer.seek(0)
    png_base64 = base64.b64encode(png_buffer.getvalue()).decode()

    # 保存为 PDF
    pdf_buffer = io.BytesIO()
    with PdfPages(pdf_buffer) as pdf:
        pdf.savefig(fig_for_output) # 无需 bbox_inches='tight'
    pdf_buffer.seek(0)
    pdf_base64 = base64.b64encode(pdf_buffer.getvalue()).decode()

    plt.close(fig_for_output) # 关闭图形，释放内存

    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'<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")