Spaces:
Running
Running
File size: 11,822 Bytes
e522499 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 |
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 FancyBboxPatch
SPLIT_TIME = "17:30"
BUSINESS_START = "09:30"
BUSINESS_END = "01:30"
BORDER_COLOR = '#A9A9A9'
DATE_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.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')
# 关键修改: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):
"""创建打印布局 (PNG 和 PDF),动态调整字体大小"""
if data.empty:
return None
# --- 创建 PNG 图形 ---
png_fig = plt.figure(figsize=(5.83, 8.27), dpi=300) # A5 竖向
png_ax_container = png_fig.add_subplot(111)
png_ax_container.set_axis_off()
png_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
# --- 创建 PDF 图形 ---
pdf_fig = plt.figure(figsize=(5.83, 8.27), dpi=300) # A5 竖向
pdf_ax_container = pdf_fig.add_subplot(111)
pdf_ax_container.set_axis_off()
pdf_fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
# --- 内部绘图函数 ---
def process_figure(fig, is_pdf=False):
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Arial Unicode MS', 'Heiti TC', 'SimHei'] # 添加备用中文字体
total_items = len(data)
num_cols = 3
num_rows = math.ceil(total_items / num_cols)
gs = gridspec.GridSpec(num_rows + 1, num_cols, hspace=0.05, wspace=0.05, height_ratios=[0.1] + [1] * num_rows, figure=fig)
# --- 新增:预先计算单元格的目标宽度(以像素为单位)---
target_width_px = 1
if total_items > 0:
# 创建一个临时坐标轴来测量其像素宽度
ax_temp = fig.add_subplot(gs[1, 0])
# 必须绘制画布才能使用渲染器并获得几何属性
fig.canvas.draw()
# 获取像素宽度并计算目标宽度(90%)
target_width_px = ax_temp.get_window_extent().width * 0.90
# 移除临时坐标轴
ax_temp.remove()
# --- 预计算结束 ---
# 此字体大小计算仅用于顶部的日期
available_height_per_row = (8.27 * 0.9 * (1 / 1.2)) / num_rows if num_rows > 0 else 1
date_fontsize = min(40, max(10, available_height_per_row * 72 * 0.5))
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
# 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
col_grid = idx % num_cols
if row_grid < num_rows + 1:
ax = fig.add_subplot(gs[row_grid, col_grid])
for spine in ax.spines.values():
spine.set_visible(False)
bbox = FancyBboxPatch(
(0.01, 0.01), 0.98, 0.98,
boxstyle="round,pad=0,rounding_size=0.02",
edgecolor=BORDER_COLOR, facecolor='none',
linewidth=0.5, transform=ax.transAxes, clip_on=False
)
ax.add_patch(bbox)
display_text = f"{hall}{end_time}"
# --- 修改部分:动态字体大小调整逻辑 ---
# 创建一个文本对象
t = ax.text(0.5, 0.5, display_text,
fontweight='bold', ha='center', va='center',
transform=ax.transAxes)
# 从一个较大的字号开始,迭代查找最佳字号
current_size = 120 # 从更大的字号开始
while current_size > 1:
t.set_fontsize(current_size)
# 获取渲染后的文本边界框
text_bbox = t.get_window_extent(renderer=fig.canvas.get_renderer())
# 如果文本宽度小于等于目标宽度,则此字号适用
if text_bbox.width <= target_width_px:
break
current_size -= 2 # 步长可以大一点以提高速度
# --- 修改结束 ---
ax.set_xticks([])
ax.set_yticks([])
else:
print(f"Warning: Index out of bounds - idx={idx}, row_grid={row_grid}, col_grid={col_grid}")
# 添加日期信息
ax_date = fig.add_subplot(gs[0, :])
ax_date.text(0.01, 0.5, f"{date_str} {title}",
fontsize=date_fontsize * 0.5, # 日期使用之前计算的字号
color=DATE_COLOR, fontweight='bold',
ha='left', va='center', transform=ax_date.transAxes)
for spine in ax_date.spines.values():
spine.set_visible(False)
ax_date.set_xticks([])
ax_date.set_yticks([])
ax_date.set_facecolor('none')
# --- 处理图形 ---
process_figure(png_fig)
process_figure(pdf_fig, is_pdf=True)
# --- 保存 PNG ---
png_buffer = io.BytesIO()
png_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()
plt.close(png_fig)
# --- 保存 PDF ---
pdf_buffer = io.BytesIO()
with PdfPages(pdf_buffer) as pdf:
pdf.savefig(pdf_fig, bbox_inches='tight', pad_inches=0.02)
pdf_buffer.seek(0)
pdf_base64 = base64.b64encode(pdf_buffer.getvalue()).decode()
plt.close(pdf_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'<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:
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") |