app.py

import pandas as pd
import streamlit as st
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import io
import base64
import os
from datetime import datetime, timedelta
from matplotlib.backends.backend_pdf import PdfPages
from pypinyin import lazy_pinyin, Style

def get_font(size=14):
    """Loads the SimHei font for Chinese character support."""
    # Prioritize 'simHei.ttc' if it exists, otherwise fall back to 'SimHei.ttf'
    font_path = "simHei.ttc"
    if not os.path.exists(font_path):
        font_path = "SimHei.ttf"
    return font_manager.FontProperties(fname=font_path, size=size)

def get_pinyin_abbr(text):
    """Gets the first letter of the Pinyin for the first two Chinese characters of a text."""
    if not text:
        return ""
    # Extract the first two Chinese characters
    chars = [c for c in text if '\u4e00' <= c <= '\u9fff']
    chars = chars[:2]
    # Get the first letter of the pinyin for each character
    pinyin_list = lazy_pinyin(chars, style=Style.FIRST_LETTER)
    return ''.join(pinyin_list).upper()

def process_schedule(file):
    """Processes the uploaded Excel file to extract and clean movie schedule data."""
    try:
        # Try to read the date from a specific cell
        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:
        # Fallback to the current date if reading fails
        date_str = datetime.today().strftime('%Y-%m-%d')
        base_date = datetime.today().date()
    
    try:
        # Read the main schedule data
        df = pd.read_excel(file, header=9, usecols=[1, 2, 4, 5])
        df.columns = ['Hall', 'StartTime', 'EndTime', 'Movie']
        
        # Data cleaning
        df['Hall'] = df['Hall'].ffill()
        df.dropna(subset=['StartTime', 'EndTime', 'Movie'], inplace=True)
        df['Hall'] = df['Hall'].astype(str).str.extract(r'(\d+号)')
        
        # Convert times to datetime objects
        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
        )
        # Handle overnight screenings
        df.loc[df['EndTime_dt'] < df['StartTime_dt'], 'EndTime_dt'] += timedelta(days=1)
        df = df.sort_values(['Hall', 'StartTime_dt'])
        
        # Merge consecutive screenings of the same movie
        merged_rows = []
        for _, group in df.groupby('Hall'):
            group = group.sort_values('StartTime_dt')
            current = None
            for _, row in group.iterrows():
                if current is None:
                    current = row.copy()
                else:
                    if row['Movie'] == current['Movie']:
                        current['EndTime_dt'] = row['EndTime_dt'] # Extend the end time
                    else:
                        merged_rows.append(current)
                        current = row.copy()
            if current is not None:
                merged_rows.append(current)
        
        merged_df = pd.DataFrame(merged_rows)
        
        # Adjust times: start 10 mins earlier, end 5 mins earlier
        merged_df['StartTime_dt'] = merged_df['StartTime_dt'] - timedelta(minutes=10)
        merged_df['EndTime_dt'] = merged_df['EndTime_dt'] - timedelta(minutes=5)
        
        # Format times back to strings
        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', 'Movie', 'StartTime_str', 'EndTime_str']], date_str
    except Exception:
        return None, date_str

def create_print_layout(data, date_str):
    """Generates the print layout as PNG and PDF files based on the schedule data."""
    if data is None or data.empty:
        return None

    # Create figures for PNG and PDF output
    png_fig = plt.figure(figsize=(8.27, 11.69), dpi=300)
    png_ax = png_fig.add_subplot(111)
    png_ax.set_axis_off()
    png_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
    
    pdf_fig = plt.figure(figsize=(8.27, 11.69), dpi=300)
    pdf_ax = pdf_fig.add_subplot(111)
    pdf_ax.set_axis_off()
    pdf_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
    
    def process_figure(fig, ax):
        """A helper function to draw the schedule on a given matplotlib Axes object."""
        halls = sorted(data['Hall'].unique(), key=lambda h: int(h.replace('号','')) if h else 0)
        
        # --- Dynamic Row and Font Size Calculation ---
        total_movie_lines = len(data)
        if total_movie_lines == 0:
            return

        num_halls = len(halls)
        num_separators = num_halls - 1 if num_halls > 1 else 0

        # Total vertical slots include movies, separators, and padding
        num_slots = total_movie_lines + num_separators + 2 # "+2" for top/bottom padding

        ax_top = 0.98
        ax_bottom = 0.02
        ax_height_fraction = ax_top - ax_bottom
        fig_height_inches = 11.69

        # Calculate font size to be 90% of the calculated row height
        slot_height_points = (fig_height_inches * ax_height_fraction * 72) / num_slots
        font_size = slot_height_points * 0.9
        
        content_font = get_font(font_size)
        hall_font = get_font(font_size * 1.1) # Hall font is slightly larger
        date_font = get_font(12)

        # --- Drawing Logic ---
        ax.text(0.0, 1.0, date_str, color='#A9A9A9',
                ha='left', va='top', fontproperties=date_font, transform=ax.transAxes)

        line_height = ax_height_fraction / num_slots
        y_position = ax_top - line_height  # Start after top padding

        for i, hall in enumerate(halls):
            hall_data = data[data['Hall'] == hall]
            hall_num = hall.replace("号", "")
            
            # Use a flag to print the hall number only once per hall
            is_first_movie_in_hall = True
            movie_count = 1
            
            for _, row in hall_data.iterrows():
                # Display Hall Number once for the block, on the same line as the first movie
                if is_first_movie_in_hall:
                    ax.text(0.03, y_position, f"${hall_num}^{{\\#}}$",
                            fontweight='bold', ha='left', va='top',
                            fontproperties=hall_font, transform=ax.transAxes, zorder=2)
                    is_first_movie_in_hall = False

                # --- New Content Layout ---
                # Left-aligned content: Seq. Number, Pinyin, Time
                ax.text(0.12, y_position, f"{movie_count}.", fontproperties=content_font, ha='left', va='top', transform=ax.transAxes)
                ax.text(0.18, y_position, get_pinyin_abbr(row['Movie']), fontproperties=content_font, ha='left', va='top', transform=ax.transAxes)
                ax.text(0.28, y_position, f"{row['StartTime_str']} - {row['EndTime_str']}", fontproperties=content_font, ha='left', va='top', transform=ax.transAxes)

                # Right-aligned content: Movie Name
                ax.text(0.97, y_position, row['Movie'], fontproperties=content_font, ha='right', va='top', transform=ax.transAxes, clip_on=True)
                
                y_position -= line_height
                movie_count += 1
            
            # --- Separator Line ---
            if i < num_separators:
                # The line is drawn in the middle of the separator's allocated slot
                line_y = y_position + (line_height / 2)
                ax.axhline(y=line_y, color='black', linewidth=0.8, xmin=0.03, xmax=0.97)
                y_position -= line_height # Move down past the separator slot

    # Process both the PNG and PDF figures
    process_figure(png_fig, png_ax)
    process_figure(pdf_fig, pdf_ax)
    
    # Save PNG to a buffer
    png_buffer = io.BytesIO()
    png_fig.savefig(png_buffer, format='png', bbox_inches='tight', pad_inches=0.05)
    png_buffer.seek(0)
    image_base64 = base64.b64encode(png_buffer.getvalue()).decode()
    plt.close(png_fig)
    
    # Save PDF to a buffer
    pdf_buffer = io.BytesIO()
    with PdfPages(pdf_buffer, 'w') 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,{image_base64}",
        'pdf': f"data:application/pdf;base64,{pdf_base64}"
    }

def display_pdf(base64_pdf):
    """Embeds the PDF in the Streamlit app for display."""
    return f'<iframe src="{base64_pdf}" width="100%" height="800" type="application/pdf"></iframe>'

# --- Streamlit App UI ---
st.set_page_config(page_title="LED 屏幕时间表打印", layout="wide")
st.title("LED 屏幕时间表打印")

uploaded_file = st.file_uploader("选择打开【放映时间核对表.xls】文件", type=["xls"])

if uploaded_file:
    with st.spinner("文件正在处理中，请稍候..."):
        schedule, date_str = process_schedule(uploaded_file)
        if schedule is not None:
            output = create_print_layout(schedule, date_str)
            
            # Create tabs for PDF and PNG previews
            tab1, tab2 = st.tabs(["PDF 预览", "PNG 预览"])
            
            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，请检查文件格式或内容是否正确。")