Update app.py

app.py

@@ -8,61 +8,43 @@ from matplotlib.patches import Rectangle
 import matplotlib.gridspec as gridspec
 import math
 
-# 定义全局常量
-SPLIT_TIME = "17:30"  # 分界线时间
-BUSINESS_START = "09:30"  # 营业开始时间
-BUSINESS_END = "01:30"  # 营业结束时间
-BORDER_COLOR = '#A9A9A9'  # 深灰色边框
+# [前面的常量定义和 process_schedule 函数保持不变]
+SPLIT_TIME = "17:30"
+BUSINESS_START = "09:30"
+BUSINESS_END = "01:30"
+BORDER_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 = df.iloc[:, [6, 7, 9]]
         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) + '#'
-        
-        # 转换时间格式
         df['StartTime'] = pd.to_datetime(df['StartTime']).dt.strftime('%H:%M')
         df['EndTime'] = pd.to_datetime(df['EndTime']).dt.strftime('%H:%M')
         
-        # 将时间转换为 datetime 对象便于比较
         base_date = datetime.today().date()
         df['StartTime'] = pd.to_datetime(base_date.strftime('%Y-%m-%d ') + df['StartTime'])
         df['EndTime'] = pd.to_datetime(base_date.strftime('%Y-%m-%d ') + df['EndTime'])
         
-        # 处理跨天情况
         df.loc[df['EndTime'] < df['StartTime'], 'EndTime'] += timedelta(days=1)
         
-        # 筛选营业时间内的场次
         business_start = datetime.strptime(base_date.strftime('%Y-%m-%d ') + BUSINESS_START, '%Y-%m-%d %H:%M')
         business_end = datetime.strptime(base_date.strftime('%Y-%m-%d ') + BUSINESS_END, '%Y-%m-%d %H:%M')
         if business_end < business_start:
             business_end += timedelta(days=1)
             
-        mask = (
-            (df['StartTime'] >= business_start) | 
-            (df['StartTime'] <= business_end)
-        )
+        mask = (df['StartTime'] >= business_start) | (df['StartTime'] <= business_end)
         df = df[mask]
         
-        # 按散场时间排序
         df = df.sort_values('EndTime')
         
-        # 分割数据
         split_time = datetime.strptime(base_date.strftime('%Y-%m-%d ') + SPLIT_TIME, '%Y-%m-%d %H:%M')
         part1 = df[df['EndTime'] <= split_time].copy()
         part2 = df[df['EndTime'] > split_time].copy()
         
-        # 格式化时间显示
         for part in [part1, part2]:
             part['EndTime'] = part['EndTime'].dt.strftime('%-I:%M')
             
@@ -77,66 +59,70 @@ def create_print_layout(data, title):
     if data.empty:
         return None
         
-    # 设置 A5 纸张竖向尺寸（单位：英寸）
+    # 设置 A5 纸张竖向尺寸
     fig = plt.figure(figsize=(5.83, 8.27), dpi=300)
-    
-    # 减小边距，最大化利用空间
     plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
     
-    # 计算行数和列数
+    # 设置字体
+    plt.rcParams['font.family'] = 'sans-serif'
+    plt.rcParams['font.sans-serif'] = ['SimHei']
+    
+    # 计算行数和总数
     total_items = len(data)
-    num_cols = 3  # 固定为3列
-    num_rows = math.ceil(total_items / num_cols)  # 计算需要的行数
+    num_cols = 3
+    num_rows = math.ceil(total_items / num_cols)
     
-    # 创建网格，减小间距
+    # 创建网格
     gs = gridspec.GridSpec(num_rows, num_cols, hspace=0.1, wspace=0.1)
     
-    # 设置字体和样式
-    plt.rcParams['font.family'] = 'sans-serif'
-    plt.rcParams['font.sans-serif'] = ['SimHei']  # 中文字体
-    
-    # 计算适合的字体大小（考虑到竖向布局和3列）
-    base_fontsize = min(50, 280 / num_rows)  # 调整基础字体大小
+    # 计算字体大小
+    base_fontsize = min(50, 280 / num_rows)
     
-    # 重新组织数据为竖向排列
-    reshaped_data = []
+    # 重要改动：正确的竖向排序逻辑
     data_values = data.values.tolist()
     
-    # 填充空值确保数据长度是3的倍数
+    # 确保数据长度是3的倍数
     while len(data_values) % 3 != 0:
         data_values.append(['', ''])
+        
+    # 计算每列应该包含的行数
+    rows_per_col = math.ceil(len(data_values) / 3)
+    
+    # 创建一个新的数据列表，用于存储重新排序后的数据
+    sorted_data = [['', '']] * len(data_values)
     
-    # 按竖向顺序重新排列数据
-    num_rows = len(data_values) // 3
-    for col in range(3):
-        for row in range(num_rows):
-            idx = row + col * num_rows
-            if idx < len(data_values):
-                reshaped_data.append(data_values[idx])
+    # 正确的竖向排序逻辑
+    for i, item in enumerate(data_values):
+        if item[0] and item[1]:  # 只处理非空数据
+            # 计算���的位置
+            row = i % rows_per_col
+            col = i // rows_per_col
+            new_index = row * 3 + col
+            if new_index < len(sorted_data):
+                sorted_data[new_index] = item
     
     # 填充数据
-    for idx, (hall, end_time) in enumerate(reshaped_data):
+    for idx, (hall, end_time) in enumerate(sorted_data):
         if hall and end_time:  # 只处理非空数据
             row = idx // 3
             col = idx % 3
             
-            # 创建子图
             ax = plt.subplot(gs[row, col])
             
-            # 设置更深的边框颜色
+            # 设置边框
             for spine in ax.spines.values():
                 spine.set_color(BORDER_COLOR)
                 spine.set_linewidth(0.5)
             
-            # 将影厅和时间紧密连接显示
+            # 显示文本
             display_text = f"{hall}{end_time}"
             ax.text(0.5, 0.5, display_text,
-                    fontsize=base_fontsize, 
-                    fontweight='bold', 
-                    ha='center', 
+                    fontsize=base_fontsize,
+                    fontweight='bold',
+                    ha='center',
                     va='center')
             
-            # 设置更小的内边距
+            # 设置边距
             ax.set_xlim(-0.02, 1.02)
             ax.set_ylim(-0.02, 1.02)
             
@@ -144,7 +130,7 @@ def create_print_layout(data, title):
             ax.set_xticks([])
             ax.set_yticks([])
     
-    # 将图表转换为 base64 字符串
+    # 转换为图片
     buffer = io.BytesIO()
     plt.savefig(buffer, format='png', bbox_inches='tight', pad_inches=0.05)
     buffer.seek(0)