Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
|
@@ -0,0 +1,228 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import pandas as pd
|
| 2 |
+
import streamlit as st
|
| 3 |
+
from datetime import datetime, timedelta
|
| 4 |
+
import matplotlib.pyplot as plt
|
| 5 |
+
import io
|
| 6 |
+
import base64
|
| 7 |
+
import matplotlib.gridspec as gridspec
|
| 8 |
+
import math
|
| 9 |
+
|
| 10 |
+
SPLIT_TIME = "17:30"
|
| 11 |
+
BUSINESS_START = "09:30"
|
| 12 |
+
BUSINESS_END = "01:30"
|
| 13 |
+
BORDER_COLOR = '#A9A9A9'
|
| 14 |
+
DATE_COLOR = '#A9A9A9'
|
| 15 |
+
|
| 16 |
+
def process_schedule(file):
|
| 17 |
+
"""处理上传的 Excel 文件,生成排序和分组后的打印内容"""
|
| 18 |
+
try:
|
| 19 |
+
# 读取 Excel,跳过前 8 行
|
| 20 |
+
df = pd.read_excel(file, skiprows=8)
|
| 21 |
+
|
| 22 |
+
# 提取所需列 (G9, H9, J9)
|
| 23 |
+
df = df.iloc[:, [6, 7, 9]] # G, H, J 列
|
| 24 |
+
df.columns = ['Hall', 'StartTime', 'EndTime']
|
| 25 |
+
|
| 26 |
+
# 清理数据
|
| 27 |
+
df = df.dropna(subset=['Hall', 'StartTime', 'EndTime'])
|
| 28 |
+
|
| 29 |
+
# 转换影厅格式为 "#号" 格式
|
| 30 |
+
df['Hall'] = df['Hall'].str.extract(r'(\d+)号').astype(str) + ' '
|
| 31 |
+
|
| 32 |
+
# 保存原始时间字符串用于诊断
|
| 33 |
+
df['original_end'] = df['EndTime']
|
| 34 |
+
|
| 35 |
+
# 转换时间为 datetime 对象
|
| 36 |
+
base_date = datetime.today().date()
|
| 37 |
+
df['StartTime'] = pd.to_datetime(df['StartTime'])
|
| 38 |
+
df['EndTime'] = pd.to_datetime(df['EndTime'])
|
| 39 |
+
|
| 40 |
+
# 设置基准时间
|
| 41 |
+
business_start = datetime.strptime(f"{base_date} {BUSINESS_START}", "%Y-%m-%d %H:%M")
|
| 42 |
+
business_end = datetime.strptime(f"{base_date} {BUSINESS_END}", "%Y-%m-%d %H:%M")
|
| 43 |
+
|
| 44 |
+
# 处理跨天情况
|
| 45 |
+
if business_end < business_start:
|
| 46 |
+
business_end += timedelta(days=1)
|
| 47 |
+
|
| 48 |
+
# 标准化所有时间到同一天
|
| 49 |
+
for idx, row in df.iterrows():
|
| 50 |
+
end_time = row['EndTime']
|
| 51 |
+
if end_time.hour < 9:
|
| 52 |
+
df.at[idx, 'EndTime'] = end_time + timedelta(days=1)
|
| 53 |
+
|
| 54 |
+
if row['StartTime'].hour >= 21 and end_time.hour < 9:
|
| 55 |
+
df.at[idx, 'EndTime'] = end_time + timedelta(days=1)
|
| 56 |
+
|
| 57 |
+
# 筛选营业时间内的场次
|
| 58 |
+
df['time_for_comparison'] = df['EndTime'].apply(
|
| 59 |
+
lambda x: datetime.combine(base_date, x.time())
|
| 60 |
+
)
|
| 61 |
+
|
| 62 |
+
df.loc[df['time_for_comparison'].dt.hour < 9, 'time_for_comparison'] += timedelta(days=1)
|
| 63 |
+
|
| 64 |
+
valid_times = (
|
| 65 |
+
((df['time_for_comparison'] >= datetime.combine(base_date, business_start.time())) &
|
| 66 |
+
(df['time_for_comparison'] <= datetime.combine(base_date + timedelta(days=1), business_end.time())))
|
| 67 |
+
)
|
| 68 |
+
|
| 69 |
+
df = df[valid_times]
|
| 70 |
+
|
| 71 |
+
# 按散场时间排序
|
| 72 |
+
df = df.sort_values('EndTime')
|
| 73 |
+
|
| 74 |
+
# 分割数据
|
| 75 |
+
split_time = datetime.strptime(f"{base_date} {SPLIT_TIME}", "%Y-%m-%d %H:%M")
|
| 76 |
+
split_time_for_comparison = df['time_for_comparison'].apply(
|
| 77 |
+
lambda x: datetime.combine(base_date, split_time.time())
|
| 78 |
+
)
|
| 79 |
+
|
| 80 |
+
part1 = df[df['time_for_comparison'] <= split_time_for_comparison].copy()
|
| 81 |
+
part2 = df[df['time_for_comparison'] > split_time_for_comparison].copy()
|
| 82 |
+
|
| 83 |
+
# 格式化时间显示
|
| 84 |
+
for part in [part1, part2]:
|
| 85 |
+
part['EndTime'] = part['EndTime'].dt.strftime('%-I:%M')
|
| 86 |
+
|
| 87 |
+
# 关键修改:精确读取C6单元格
|
| 88 |
+
date_df = pd.read_excel(
|
| 89 |
+
file,
|
| 90 |
+
skiprows=5, # 跳过前5行(0-4)
|
| 91 |
+
nrows=1, # 只读1行
|
| 92 |
+
usecols=[2], # 第三列(C列)
|
| 93 |
+
header=None # 无表头
|
| 94 |
+
)
|
| 95 |
+
date_cell = date_df.iloc[0, 0]
|
| 96 |
+
|
| 97 |
+
try:
|
| 98 |
+
# 处理不同日期格式
|
| 99 |
+
if isinstance(date_cell, str):
|
| 100 |
+
date_str = datetime.strptime(date_cell, '%Y-%m-%d').strftime('%Y-%m-%d')
|
| 101 |
+
else:
|
| 102 |
+
date_str = pd.to_datetime(date_cell).strftime('%Y-%m-%d')
|
| 103 |
+
except:
|
| 104 |
+
date_str = datetime.today().strftime('%Y-%m-%d')
|
| 105 |
+
|
| 106 |
+
return part1[['Hall', 'EndTime']], part2[['Hall', 'EndTime']], date_str
|
| 107 |
+
|
| 108 |
+
except Exception as e:
|
| 109 |
+
st.error(f"处理文件时出错: {str(e)}")
|
| 110 |
+
return None, None, None
|
| 111 |
+
|
| 112 |
+
def create_print_layout(data, title, date_str):
|
| 113 |
+
"""创建打印布局"""
|
| 114 |
+
if data.empty:
|
| 115 |
+
return None
|
| 116 |
+
|
| 117 |
+
# 设置 A5 纸张竖向尺寸
|
| 118 |
+
fig = plt.figure(figsize=(5.83, 8.27), dpi=300)
|
| 119 |
+
plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
|
| 120 |
+
|
| 121 |
+
# 设置字体
|
| 122 |
+
plt.rcParams['font.family'] = 'sans-serif'
|
| 123 |
+
plt.rcParams['font.sans-serif'] = ['Arial Unicode MS']
|
| 124 |
+
|
| 125 |
+
# 计算行数和总数
|
| 126 |
+
total_items = len(data)
|
| 127 |
+
num_cols = 3
|
| 128 |
+
num_rows = math.ceil(total_items / num_cols)
|
| 129 |
+
|
| 130 |
+
# 创建网格
|
| 131 |
+
gs = gridspec.GridSpec(num_rows + 1, num_cols, hspace=0.1, wspace=0.1, height_ratios=[1] * num_rows + [0.2])
|
| 132 |
+
|
| 133 |
+
base_fontsize = min(30, 265 / num_rows)
|
| 134 |
+
|
| 135 |
+
data_values = data.values.tolist()
|
| 136 |
+
|
| 137 |
+
while len(data_values) % 3 != 0:
|
| 138 |
+
data_values.append(['', ''])
|
| 139 |
+
|
| 140 |
+
rows_per_col = math.ceil(len(data_values) / 3)
|
| 141 |
+
|
| 142 |
+
sorted_data = [['', '']] * len(data_values)
|
| 143 |
+
|
| 144 |
+
for i, item in enumerate(data_values):
|
| 145 |
+
if item[0] and item[1]:
|
| 146 |
+
row = i % rows_per_col
|
| 147 |
+
col = i // rows_per_col
|
| 148 |
+
new_index = row * 3 + col
|
| 149 |
+
if new_index < len(sorted_data):
|
| 150 |
+
sorted_data[new_index] = item
|
| 151 |
+
|
| 152 |
+
for idx, (hall, end_time) in enumerate(sorted_data):
|
| 153 |
+
if hall and end_time:
|
| 154 |
+
row = idx // 3
|
| 155 |
+
col = idx % 3
|
| 156 |
+
|
| 157 |
+
ax = plt.subplot(gs[row, col])
|
| 158 |
+
|
| 159 |
+
for spine in ax.spines.values():
|
| 160 |
+
spine.set_color(BORDER_COLOR)
|
| 161 |
+
spine.set_linewidth(0.5)
|
| 162 |
+
|
| 163 |
+
display_text = f"{hall}{end_time}"
|
| 164 |
+
ax.text(0.5, 0.5, display_text,
|
| 165 |
+
fontsize=base_fontsize,
|
| 166 |
+
fontweight='bold',
|
| 167 |
+
ha='center',
|
| 168 |
+
va='center')
|
| 169 |
+
|
| 170 |
+
ax.set_xlim(-0.02, 1.02)
|
| 171 |
+
ax.set_ylim(-0.02, 1.02)
|
| 172 |
+
|
| 173 |
+
ax.set_xticks([])
|
| 174 |
+
ax.set_yticks([])
|
| 175 |
+
|
| 176 |
+
# 添加日期信息
|
| 177 |
+
ax_date = plt.subplot(gs[0, 0])
|
| 178 |
+
ax_date.text(0.05, 0.95, f"{date_str} {title}",
|
| 179 |
+
fontsize=base_fontsize * 0.4,
|
| 180 |
+
color=DATE_COLOR,
|
| 181 |
+
fontweight='bold',
|
| 182 |
+
ha='left',
|
| 183 |
+
va='top')
|
| 184 |
+
|
| 185 |
+
for spine in ax_date.spines.values():
|
| 186 |
+
spine.set_visible(False)
|
| 187 |
+
ax_date.set_xticks([])
|
| 188 |
+
ax_date.set_yticks([])
|
| 189 |
+
|
| 190 |
+
# 转换为图片
|
| 191 |
+
buffer = io.BytesIO()
|
| 192 |
+
plt.savefig(buffer, format='png', bbox_inches='tight', pad_inches=0.05)
|
| 193 |
+
buffer.seek(0)
|
| 194 |
+
image_base64 = base64.b64encode(buffer.getvalue()).decode()
|
| 195 |
+
plt.close()
|
| 196 |
+
|
| 197 |
+
return f'data:image/png;base64,{image_base64}'
|
| 198 |
+
|
| 199 |
+
# Streamlit 界面
|
| 200 |
+
st.set_page_config(page_title="散厅时间快捷打印", layout="wide")
|
| 201 |
+
st.title("散厅时间快捷打印")
|
| 202 |
+
|
| 203 |
+
uploaded_file = st.file_uploader("上传【放映场次核对表.xls】文件", type=["xls", "xlsx"])
|
| 204 |
+
|
| 205 |
+
if uploaded_file:
|
| 206 |
+
part1, part2, date_str = process_schedule(uploaded_file)
|
| 207 |
+
|
| 208 |
+
if part1 is not None and part2 is not None:
|
| 209 |
+
part1_image = create_print_layout(part1, "A", date_str)
|
| 210 |
+
part2_image = create_print_layout(part2, "C", date_str)
|
| 211 |
+
|
| 212 |
+
col1, col2 = st.columns(2)
|
| 213 |
+
|
| 214 |
+
with col1:
|
| 215 |
+
st.subheader("白班散场预览(时间 ≤ 17:30)")
|
| 216 |
+
if part1_image:
|
| 217 |
+
st.image(part1_image)
|
| 218 |
+
else:
|
| 219 |
+
st.info("白班部分没有数据")
|
| 220 |
+
|
| 221 |
+
with col2:
|
| 222 |
+
st.subheader("夜班散场预览(时间 > 17:30)")
|
| 223 |
+
if part2_image:
|
| 224 |
+
st.image(part2_image)
|
| 225 |
+
else:
|
| 226 |
+
st.info("夜班部分没有数据")
|
| 227 |
+
|
| 228 |
+
|