commit 672760bb2533ad189659b09812cefc1a6a29bef1 Author: yovinchen Date: Mon Jun 30 10:36:41 2025 +0800 项目基本完成 diff --git a/.idea/TableSynthesis.iml b/.idea/TableSynthesis.iml new file mode 100644 index 0000000..f0c4c3e --- /dev/null +++ b/.idea/TableSynthesis.iml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml new file mode 100644 index 0000000..ac21435 --- /dev/null +++ b/.idea/inspectionProfiles/Project_Default.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 0000000..105ce2d --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000..35f11bb --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,6 @@ + + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 0000000..aace106 --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..f5a2588 --- /dev/null +++ b/README.md @@ -0,0 +1,146 @@ +# 座位分配系统 + +智能座位分配工具，支持1-10人连坐需求，能够处理不连续座位的复杂情况。 + +## 🎯 功能特点 + +- ✅ **智能分配**: 支持1-10人的各种连坐需求 +- ✅ **数据校验**: 完整的文件格式和逻辑校验 +- ✅ **不连续座位**: 自动处理座位号间隙 +- ✅ **详细日志**: 完整的操作记录和结果验证 +- ✅ **跨平台**: 支持Windows、macOS、Linux + +## 📋 使用方法 + +### 准备Excel文件 + +1. **人员信息.xlsx** - 包含以下列： + - 姓名、证件类型、证件号、手机号、备注 + - 备注数字表示连坐人数（如：备注4表示当前行+后3行共4人连坐） + +2. **座位信息.xlsx** - 包含以下列： + - 区域、楼层、排号、座位号 + +### 运行程序 + +#### Python环境运行 +```bash +# 安装依赖 +pip install pandas openpyxl + +# 运行程序 +python seat_allocation_system.py +``` + +#### 构建可执行文件 +```bash +# 在当前平台构建 +python simple_build.py + +# 跨平台构建（macOS构建Windows版本） +python cross_platform_build.py +``` + +### 查看结果 + +程序运行后会生成： +- `座位信息_最终分配.xlsx` - 最终分配结果 +- `最终座位分配日志.xlsx` - 详细分配记录 +- `seat_allocation_log.txt` - 完整运行日志 + +## 🔧 构建选项 + +### 本地构建 +```bash +# 简单构建（推荐） +python simple_build.py +``` + +### 跨平台构建 +```bash +# 在macOS上构建Windows版本 +python cross_platform_build.py +``` + +### 自动化构建 +使用GitHub Actions自动构建多平台版本： +1. 将 `build_workflow.yml` 放入 `.github/workflows/` 目录 +2. 推送到GitHub仓库 +3. 自动构建Windows x86/x64和macOS版本 + +## 📁 文件说明 + +### 核心文件 +- `seat_allocation_system.py` - 主程序 +- `simple_build.py` - 简化构建脚本 +- `cross_platform_build.py` - 跨平台构建脚本 +- `requirements.txt` - Python依赖 + +### 配置文件 +- `build_workflow.yml` - GitHub Actions工作流 +- `人员信息.xlsx` - 示例人员数据 +- `座位信息.xlsx` - 示例座位数据 + +## 🎯 支持的平台 + +### 直接运行 +- Windows 7/8/10/11 (x86/x64/ARM64) +- macOS 10.14+ (Intel/Apple Silicon) +- Linux (x86_64/ARM64) + +### 构建目标 +- **Windows x86** - 32位兼容版本 +- **Windows x64** - 64位主流版本 +- **macOS** - Intel和Apple Silicon +- **Linux** - 主流发行版 + +## 📊 数据格式要求 + +### 人员信息格式 +``` +姓名 | 证件类型 | 证件号 | 手机号 | 备注 +张三 | 身份证 | 123456789012345678 | 13800138000 | 2 +李四 | 身份证 | 123456789012345679 | 13800138001 | +王五 | 身份证 | 12345678901234567X | 13800138002 | 3 +赵六 | 身份证 | 123456789012345680 | 13800138003 | +钱七 | 身份证 | 123456789012345681 | 13800138004 | +``` + +### 座位信息格式 +``` +区域 | 楼层 | 排号 | 座位号 +A区通道 | 一层 | 1排 | 1号 +A区通道 | 一层 | 1排 | 2号 +A区通道 | 一层 | 1排 | 3号 +``` + +## ⚠️ 注意事项 + +1. **备注逻辑**: 备注数字表示连坐人数，只有组长填写备注，成员留空 +2. **证件号格式**: 支持包含X的身份证号，自动处理为字符串格式 +3. **文字清理**: 自动清除姓名等字段的多余空格 +4. **座位连续性**: 支持不连续座位号，算法会自动寻找合适的连续段 + +## 🔍 故障排除 + +### 常见问题 +1. **文件格式错误**: 确保Excel文件包含必需的列 +2. **编码问题**: 确保Excel文件使用UTF-8编码 +3. **权限问题**: 确保有读写Excel文件的权限 +4. **内存不足**: 处理大量数据时可能需要更多内存 + +### 技术支持 +如遇问题，请查看生成的日志文件： +- `seat_allocation_log.txt` - 详细的运行日志 +- 控制台输出 - 实时处理信息 + +## 📈 版本历史 + +- **v1.0** - 初始版本，支持基本座位分配 +- **v1.1** - 添加数据校验和错误处理 +- **v1.2** - 支持不连续座位处理 +- **v1.3** - 优化数据类型处理，支持跨平台构建 + +## 📄 许可证 + +本项目采用MIT许可证，详见LICENSE文件。 diff --git a/build_workflow.yml b/build_workflow.yml new file mode 100644 index 0000000..b2cfde3 --- /dev/null +++ b/build_workflow.yml @@ -0,0 +1,89 @@ +# GitHub Actions工作流 - 多平台构建 +# 将此文件放在 .github/workflows/ 目录下 + +name: Build Multi-Platform Executables + +on: + push: + branches: [ main ] + pull_request: + branches: [ main ] + workflow_dispatch: + +jobs: + build-windows: + runs-on: windows-latest + strategy: + matrix: + arch: [x64, x86] + + steps: + - uses: actions/checkout@v3 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + architecture: ${{ matrix.arch }} + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install pandas openpyxl pyinstaller + + - name: Build executable + run: | + pyinstaller --onefile --console --name "座位分配系统_${{ matrix.arch }}" seat_allocation_system.py + + - name: Upload artifacts + uses: actions/upload-artifact@v3 + with: + name: windows-${{ matrix.arch }} + path: dist/座位分配系统_${{ matrix.arch }}.exe + + build-macos: + runs-on: macos-latest + + steps: + - uses: actions/checkout@v3 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install pandas openpyxl pyinstaller + + - name: Build executable + run: | + pyinstaller --onefile --console --name "座位分配系统_macos" seat_allocation_system.py + + - name: Upload artifacts + uses: actions/upload-artifact@v3 + with: + name: macos + path: dist/座位分配系统_macos + + create-release: + needs: [build-windows, build-macos] + runs-on: ubuntu-latest + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + + steps: + - name: Download all artifacts + uses: actions/download-artifact@v3 + + - name: Create Release + uses: softprops/action-gh-release@v1 + with: + tag_name: v${{ github.run_number }} + name: Release v${{ github.run_number }} + files: | + windows-x64/座位分配系统_x64.exe + windows-x86/座位分配系统_x86.exe + macos/座位分配系统_macos + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} diff --git a/cross_platform_build.py b/cross_platform_build.py new file mode 100644 index 0000000..5a660a5 --- /dev/null +++ b/cross_platform_build.py @@ -0,0 +1,326 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +跨平台构建脚本 +在macOS上构建Windows x86/x64版本的exe文件 +使用Wine和PyInstaller实现跨平台编译 +""" + +import os +import sys +import subprocess +import platform +import shutil +from pathlib import Path + +def check_dependencies(): + """检查必要的依赖""" + print("检查构建依赖...") + + # 检查是否在macOS上 + if platform.system() != 'Darwin': + print(f"当前系统: {platform.system()}") + print("此脚本专为macOS设计，用于构建Windows版本") + return False + + # 检查Python包 + required_packages = ['pandas', 'openpyxl', 'pyinstaller'] + missing_packages = [] + + for package in required_packages: + try: + __import__(package) + print(f"✅ {package} 已安装") + except ImportError: + missing_packages.append(package) + print(f"❌ {package} 未安装") + + if missing_packages: + print(f"\n安装缺失的包...") + for package in missing_packages: + try: + subprocess.check_call([sys.executable, '-m', 'pip', 'install', package]) + print(f"✅ {package} 安装成功") + except subprocess.CalledProcessError: + print(f"❌ {package} 安装失败") + return False + + return True + +def install_wine(): + """安装Wine（如果需要）""" + print("\n检查Wine环境...") + + # 检查是否已安装Wine + try: + result = subprocess.run(['wine', '--version'], capture_output=True, text=True) + if result.returncode == 0: + print(f"✅ Wine已安装: {result.stdout.strip()}") + return True + except FileNotFoundError: + pass + + print("Wine未安装，开始安装...") + print("请按照以下步骤手动安装Wine:") + print("1. 安装Homebrew (如果未安装): /bin/bash -c \"$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)\"") + print("2. 安装Wine: brew install --cask wine-stable") + print("3. 配置Wine: winecfg") + + response = input("是否已完成Wine安装? (y/N): ") + return response.lower() == 'y' + +def setup_wine_python(): + """在Wine中设置Python环境""" + print("\n设置Wine Python环境...") + + # 检查Wine中是否已安装Python + try: + result = subprocess.run(['wine', 'python', '--version'], capture_output=True, text=True) + if result.returncode == 0: + print(f"✅ Wine Python已安装: {result.stdout.strip()}") + return True + except: + pass + + print("需要在Wine中安装Python...") + print("请按照以下步骤:") + print("1. 下载Windows版Python: https://www.python.org/downloads/windows/") + print("2. 使用Wine安装: wine python-3.10.x-amd64.exe") + print("3. 安装pip包: wine python -m pip install pandas openpyxl pyinstaller") + + response = input("是否已完成Wine Python安装? (y/N): ") + return response.lower() == 'y' + +def create_build_spec(target_arch='x64'): + """创建构建规格文件""" + exe_name = f"座位分配系统_{target_arch}" + + spec_content = f'''# -*- mode: python ; coding: utf-8 -*- + +block_cipher = None + +a = Analysis( + ['seat_allocation_system.py'], + pathex=[], + binaries=[], + datas=[], + hiddenimports=[ + 'pandas', + 'openpyxl', + 'numpy', + 'xlsxwriter', + 'xlrd', + 'datetime', + 'pathlib' + ], + hookspath=[], + hooksconfig={{}}, + runtime_hooks=[], + excludes=[ + 'matplotlib', + 'scipy', + 'IPython', + 'jupyter', + 'notebook', + 'tkinter' + ], + win_no_prefer_redirects=False, + win_private_assemblies=False, + cipher=block_cipher, + noarchive=False, +) + +pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher) + +exe = EXE( + pyz, + a.scripts, + a.binaries, + a.zipfiles, + a.datas, + [], + name='{exe_name}', + debug=False, + bootloader_ignore_signals=False, + strip=False, + upx=True, + upx_exclude=[], + runtime_tmpdir=None, + console=True, + disable_windowed_traceback=False, + argv_emulation=False, + target_arch=None, + codesign_identity=None, + entitlements_file=None, + icon=None, +) +''' + + spec_file = f'{exe_name}.spec' + with open(spec_file, 'w', encoding='utf-8') as f: + f.write(spec_content) + + return spec_file, exe_name + +def build_with_docker(): + """使用Docker构建Windows版本""" + print("\n使用Docker构建Windows版本...") + + # 创建Dockerfile + dockerfile_content = '''FROM python:3.10-windowsservercore + +# 设置工作目录 +WORKDIR /app + +# 复制文件 +COPY requirements.txt . +COPY seat_allocation_system.py . + +# 安装依赖 +RUN pip install -r requirements.txt + +# 构建exe +RUN pyinstaller --onefile --console --name "座位分配系统_x64" seat_allocation_system.py + +# 输出目录 +VOLUME ["/app/dist"] +''' + + with open('Dockerfile.windows', 'w') as f: + f.write(dockerfile_content) + + print("Docker方法需要Docker Desktop和Windows容器支持") + print("这是一个高级选项，建议使用其他方法") + return False + +def build_native_macos(): + """在macOS上直接构建（生成macOS版本）""" + print("\n在macOS上构建本地版本...") + + # 清理之前的构建 + if os.path.exists('dist'): + shutil.rmtree('dist') + if os.path.exists('build'): + shutil.rmtree('build') + + # 构建命令 + cmd = [ + sys.executable, '-m', 'PyInstaller', + '--onefile', + '--console', + '--clean', + '--name', '座位分配系统_macos', + 'seat_allocation_system.py' + ] + + try: + print(f"执行命令: {' '.join(cmd)}") + result = subprocess.run(cmd, capture_output=True, text=True) + + if result.returncode == 0: + print("✅ macOS版本构建成功!") + + # 检查生成的文件 + app_path = Path('dist') / '座位分配系统_macos' + if app_path.exists(): + file_size = app_path.stat().st_size / (1024 * 1024) # MB + print(f"生成文件: {app_path}") + print(f"文件大小: {file_size:.1f} MB") + return True, app_path + else: + print("❌ 构建失败!") + print("错误输出:") + print(result.stderr) + return False, None + + except Exception as e: + print(f"❌ 构建过程中出现错误: {e}") + return False, None + +def create_cross_compile_script(): + """创建跨编译脚本""" + script_content = '''#!/bin/bash +# Windows交叉编译脚本 + +echo "座位分配系统 - Windows交叉编译" +echo "================================" + +# 检查是否安装了mingw-w64 +if ! command -v x86_64-w64-mingw32-gcc &> /dev/null; then + echo "安装mingw-w64..." + brew install mingw-w64 +fi + +# 设置交叉编译环境 +export CC=x86_64-w64-mingw32-gcc +export CXX=x86_64-w64-mingw32-g++ + +# 构建Windows版本 +echo "开始构建Windows x64版本..." +python -m PyInstaller \\ + --onefile \\ + --console \\ + --clean \\ + --name "座位分配系统_x64" \\ + --target-arch x86_64 \\ + seat_allocation_system.py + +echo "构建完成!" +''' + + with open('cross_compile.sh', 'w') as f: + f.write(script_content) + + # 设置执行权限 + os.chmod('cross_compile.sh', 0o755) + print("✅ 已创建交叉编译脚本: cross_compile.sh") + +def main(): + """主函数""" + print("座位分配系统 - 跨平台构建工具") + print("=" * 50) + print("在macOS上构建Windows版本") + + # 检查依赖 + if not check_dependencies(): + return + + print("\n选择构建方法:") + print("1. 构建macOS版本（推荐）") + print("2. 使用Wine构建Windows版本（复杂）") + print("3. 创建交叉编译脚本（实验性）") + print("4. 生成Docker构建文件（高级）") + + choice = input("\n请选择 (1-4): ").strip() + + if choice == '1': + print("\n构建macOS版本...") + success, app_path = build_native_macos() + if success: + print(f"\n🎉 构建完成!") + print(f"生成文件: {app_path}") + print("\n注意: 这是macOS版本，不能在Windows上运行") + print("如需Windows版本，请在Windows系统上运行构建脚本") + + elif choice == '2': + print("\n使用Wine构建Windows版本...") + if install_wine() and setup_wine_python(): + print("Wine环境已准备就绪") + print("请手动在Wine中运行: wine python windows_build.py") + else: + print("Wine环境设置失败") + + elif choice == '3': + print("\n创建交叉编译脚本...") + create_cross_compile_script() + print("请运行: ./cross_compile.sh") + + elif choice == '4': + print("\n生成Docker构建文件...") + build_with_docker() + + else: + print("无效选择") + +if __name__ == "__main__": + main() diff --git a/seat_allocation_system.py b/seat_allocation_system.py new file mode 100644 index 0000000..fad598b --- /dev/null +++ b/seat_allocation_system.py @@ -0,0 +1,898 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +完整的座位分配系统 +包含文件校验、智能分配算法和日志输出功能 +支持1-10人连坐需求，能够处理不连续座位 +""" + +import pandas as pd +import numpy as np +from pathlib import Path +import datetime +import sys + +class Logger: + """日志记录器""" + def __init__(self, log_file='seat_allocation_log.txt'): + self.log_file = log_file + self.logs = [] + + def log(self, message, print_to_console=True): + """记录日志""" + timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") + log_entry = f"[{timestamp}] {message}" + self.logs.append(log_entry) + + if print_to_console: + print(message) + + def save_logs(self): + """保存日志到文件""" + try: + with open(self.log_file, 'w', encoding='utf-8') as f: + f.write('\n'.join(self.logs)) + self.log(f"日志已保存到: {self.log_file}") + return True + except Exception as e: + print(f"保存日志失败: {e}") + return False + +class SeatAllocationSystem: + """座位分配系统""" + + def __init__(self): + self.logger = Logger() + self.personnel_df = None + self.seat_df = None + self.seating_groups = [] + self.row_analysis = {} + + def load_data(self): + """加载人员信息和座位信息数据""" + self.logger.log("=== 开始加载数据 ===") + + # 检查文件是否存在 + personnel_file = '人员信息.xlsx' + seat_file = '座位信息.xlsx' + + if not Path(personnel_file).exists(): + self.logger.log(f"❌ 错误: {personnel_file} 文件不存在") + return False + + if not Path(seat_file).exists(): + self.logger.log(f"❌ 错误: {seat_file} 文件不存在") + return False + + try: + # 读取人员信息，指定数据类型 + self.personnel_df = pd.read_excel(personnel_file, dtype={ + '姓名': 'str', + '证件类型': 'str', + '证件号': 'str', # 证件号作为字符串读取，避免X被转换 + '手机号': 'str' + }) + + # 读取座位信息，指定数据类型 + self.seat_df = pd.read_excel(seat_file, dtype={ + '区域': 'str', + '楼层': 'str', + '排号': 'str', + '座位号': 'str', + '姓名': 'str', + '证件类型': 'str', + '证件号': 'str', + '手机号': 'str', + '签发地/国籍': 'str' + }) + + # 清理文字信息中的空格 + self.clean_text_data() + + self.logger.log(f"✅ 文件加载成功") + self.logger.log(f" 人员信息: {self.personnel_df.shape[0]} 行 × {self.personnel_df.shape[1]} 列") + self.logger.log(f" 座位信息: {self.seat_df.shape[0]} 行 × {self.seat_df.shape[1]} 列") + return True + except Exception as e: + self.logger.log(f"❌ 文件加载失败: {e}") + return False + + def clean_text_data(self): + """清理文字数据中的空格""" + self.logger.log("清理文字数据中的空格...") + + # 清理人员信息中的空格 + text_columns_personnel = ['姓名', '证件类型', '证件号'] + for col in text_columns_personnel: + if col in self.personnel_df.columns: + self.personnel_df[col] = self.personnel_df[col].astype(str).str.strip() + + # 清理座位信息中的空格 + text_columns_seat = ['区域', '楼层', '排号', '座位号', '姓名', '证件类型', '证件号', '签发地/国籍'] + for col in text_columns_seat: + if col in self.seat_df.columns: + # 只对非空值进行清理 + mask = self.seat_df[col].notna() + self.seat_df.loc[mask, col] = self.seat_df.loc[mask, col].astype(str).str.strip() + + self.logger.log("✅ 文字数据清理完成") + + def validate_personnel_structure(self): + """校验人员信息文件结构""" + self.logger.log("\n=== 人员信息结构校验 ===") + + required_columns = ['姓名', '证件类型', '证件号', '手机号', '备注'] + validation_results = [] + + # 检查必需列 + missing_columns = [] + for col in required_columns: + if col not in self.personnel_df.columns: + missing_columns.append(col) + + if missing_columns: + self.logger.log(f"❌ 缺少必需列: {missing_columns}") + validation_results.append(False) + else: + self.logger.log("✅ 所有必需列都存在") + validation_results.append(True) + + # 检查数据完整性 + self.logger.log("\n数据完整性检查:") + for col in ['姓名', '证件类型', '证件号', '手机号']: + if col in self.personnel_df.columns: + null_count = self.personnel_df[col].isnull().sum() + if null_count > 0: + self.logger.log(f"⚠️ {col} 列有 {null_count} 个空值") + validation_results.append(False) + else: + self.logger.log(f"✅ {col} 列数据完整") + validation_results.append(True) + + # 检查重复姓名 + duplicate_names = self.personnel_df[self.personnel_df['姓名'].duplicated()] + if not duplicate_names.empty: + self.logger.log(f"⚠️ 发现重复姓名: {duplicate_names['姓名'].tolist()}") + validation_results.append(False) + else: + self.logger.log("✅ 姓名无重复") + validation_results.append(True) + + return all(validation_results) + + def validate_seating_groups(self): + """校验连坐组的完整性和正确性""" + self.logger.log("\n=== 连坐组校验 ===") + + validation_results = [] + issues = [] + + i = 0 + group_num = 1 + + while i < len(self.personnel_df): + person = self.personnel_df.iloc[i] + remark = person['备注'] + + if pd.isna(remark): + # 无备注，单独坐 + self.logger.log(f"✅ 第 {group_num} 组: {person['姓名']} (单独)") + i += 1 + else: + # 有备注，检查连坐组 + try: + group_size = int(remark) + + if group_size < 1 or group_size > 10: + issue = f"❌ 第 {group_num} 组: {person['姓名']} 的备注 {group_size} 超出范围 (1-10)" + self.logger.log(issue) + issues.append(issue) + validation_results.append(False) + i += 1 + continue + + # 检查后续人员是否足够 + if i + group_size > len(self.personnel_df): + issue = f"❌ 第 {group_num} 组: {person['姓名']} 需要 {group_size} 人连坐，但后续人员不足" + self.logger.log(issue) + issues.append(issue) + validation_results.append(False) + i += 1 + continue + + # 检查后续人员的备注是否为空 + group_members = [] + valid_group = True + + for j in range(group_size): + member = self.personnel_df.iloc[i + j] + group_members.append(member['姓名']) + + if j == 0: + # 第一个人应该有备注 + if pd.isna(member['备注']) or int(member['备注']) != group_size: + issue = f"❌ 第 {group_num} 组: 组长 {member['姓名']} 的备注应该是 {group_size}" + self.logger.log(issue) + issues.append(issue) + valid_group = False + else: + # 后续人员应该没有备注 + if not pd.isna(member['备注']): + issue = f"❌ 第 {group_num} 组: {member['姓名']} 应该没有备注（当前备注: {member['备注']}）" + self.logger.log(issue) + issues.append(issue) + valid_group = False + + if valid_group: + self.logger.log(f"✅ 第 {group_num} 组: {', '.join(group_members)} ({group_size}人连坐)") + validation_results.append(True) + else: + validation_results.append(False) + + i += group_size + + except ValueError: + issue = f"❌ 第 {group_num} 组: {person['姓名']} 的备注 '{remark}' 不是有效数字" + self.logger.log(issue) + issues.append(issue) + validation_results.append(False) + i += 1 + + group_num += 1 + + return all(validation_results), issues + + def validate_seat_structure(self): + """校验座位信息结构和连续性""" + self.logger.log("\n=== 座位信息结构校验 ===") + + required_columns = ['区域', '楼层', '排号', '座位号'] + validation_results = [] + + # 检查必需列 + missing_columns = [] + for col in required_columns: + if col not in self.seat_df.columns: + missing_columns.append(col) + + if missing_columns: + self.logger.log(f"❌ 缺少必需列: {missing_columns}") + return False, {} + + self.logger.log("✅ 所有必需列都存在") + + # 检查数据完整性 + for col in required_columns: + null_count = self.seat_df[col].isnull().sum() + if null_count > 0: + self.logger.log(f"❌ {col} 列有 {null_count} 个空值") + validation_results.append(False) + else: + self.logger.log(f"✅ {col} 列数据完整") + validation_results.append(True) + + # 分析座位结构 + self.logger.log("\n座位结构分析:") + seat_groups = {} + for _, row in self.seat_df.iterrows(): + key = (row['区域'], row['楼层'], row['排号']) + if key not in seat_groups: + seat_groups[key] = [] + seat_groups[key].append(row['座位号']) + + # 检查每排的座位结构和可用连续段 + self.logger.log("\n座位结构分析:") + for (area, floor, row_num), seats in seat_groups.items(): + # 提取座位号数字 + seat_numbers = [] + for seat in seats: + try: + seat_numbers.append(int(str(seat).replace('号', ''))) + except: + self.logger.log(f"❌ {area}-{floor}-{row_num}: 座位号格式异常 '{seat}'") + validation_results.append(False) + continue + + seat_numbers.sort() + + # 分析连续段 + consecutive_segments = [] + if seat_numbers: + current_segment = [seat_numbers[0]] + + for i in range(1, len(seat_numbers)): + if seat_numbers[i] - seat_numbers[i-1] == 1: + # 连续 + current_segment.append(seat_numbers[i]) + else: + # 不连续，保存当前段，开始新段 + consecutive_segments.append(current_segment) + current_segment = [seat_numbers[i]] + + # 添加最后一段 + consecutive_segments.append(current_segment) + + # 显示分析结果 + if len(consecutive_segments) == 1 and len(consecutive_segments[0]) == len(seat_numbers): + self.logger.log(f"✅ {area}-{floor}-{row_num}: {len(seats)} 个座位完全连续 ({min(seat_numbers)}-{max(seat_numbers)})") + else: + segments_info = [] + max_segment_size = 0 + for segment in consecutive_segments: + if len(segment) == 1: + segments_info.append(f"{segment[0]}") + else: + segments_info.append(f"{segment[0]}-{segment[-1]}") + max_segment_size = max(max_segment_size, len(segment)) + + self.logger.log(f"📊 {area}-{floor}-{row_num}: {len(seats)} 个座位，{len(consecutive_segments)} 个连续段: {', '.join(segments_info)}") + self.logger.log(f" 最大连续段: {max_segment_size} 个座位") + + validation_results.append(True) # 座位不连续不算错误，只是需要特殊处理 + + return all(validation_results), seat_groups + + def validate_capacity_feasibility(self, seat_groups): + """校验座位容量和分配可行性""" + self.logger.log("\n=== 容量和可行性校验 ===") + + # 统计人员总数 + total_people = len(self.personnel_df) + total_seats = sum(len(seats) for seats in seat_groups.values()) + + self.logger.log(f"总人数: {total_people}") + self.logger.log(f"总座位数: {total_seats}") + + if total_people > total_seats: + self.logger.log(f"❌ 座位不足: 需要 {total_people} 个座位，只有 {total_seats} 个") + return False + else: + self.logger.log(f"✅ 座位充足: 剩余 {total_seats - total_people} 个座位") + + # 分析连坐组需求 + self.logger.log("\n连坐组需求分析:") + group_sizes = [] + i = 0 + + while i < len(self.personnel_df): + person = self.personnel_df.iloc[i] + remark = person['备注'] + + if pd.isna(remark): + group_sizes.append(1) + i += 1 + else: + try: + group_size = int(remark) + group_sizes.append(group_size) + i += group_size + except: + group_sizes.append(1) + i += 1 + + max_group_size = max(group_sizes) + self.logger.log(f"最大连坐组: {max_group_size} 人") + + # 检查是否有足够的连续座位来容纳最大连坐组 + self.logger.log(f"\n连续座位可行性分析:") + max_consecutive_available = 0 + feasible_rows = [] + + for (area, floor, row_num), seats in seat_groups.items(): + # 分析每排的连续座位段 + seat_numbers = [] + for seat in seats: + try: + seat_numbers.append(int(str(seat).replace('号', ''))) + except: + continue + + seat_numbers.sort() + + # 找出最大连续段 + max_consecutive_in_row = 0 + if seat_numbers: + current_consecutive = 1 + for i in range(1, len(seat_numbers)): + if seat_numbers[i] - seat_numbers[i-1] == 1: + current_consecutive += 1 + else: + max_consecutive_in_row = max(max_consecutive_in_row, current_consecutive) + current_consecutive = 1 + max_consecutive_in_row = max(max_consecutive_in_row, current_consecutive) + + if max_consecutive_in_row >= max_group_size: + feasible_rows.append((area, floor, row_num, max_consecutive_in_row)) + + max_consecutive_available = max(max_consecutive_available, max_consecutive_in_row) + self.logger.log(f" {area}-{floor}-{row_num}: 最大连续 {max_consecutive_in_row} 个座位") + + self.logger.log(f"\n全场最大连续座位: {max_consecutive_available} 个") + + if max_group_size > max_consecutive_available: + self.logger.log(f"❌ 无法容纳最大连坐组: 需要 {max_group_size} 个连续座位，最大连续段只有 {max_consecutive_available} 个") + return False + else: + self.logger.log(f"✅ 可以容纳最大连坐组") + self.logger.log(f"可容纳最大连坐组的排数: {len(feasible_rows)} 个") + + # 统计各种大小的连坐组 + size_counts = {} + for size in group_sizes: + size_counts[size] = size_counts.get(size, 0) + 1 + + self.logger.log("\n连坐组分布:") + for size in sorted(size_counts.keys()): + count = size_counts[size] + if size == 1: + self.logger.log(f" 单人组: {count} 个") + else: + self.logger.log(f" {size}人连坐组: {count} 个") + + return True + + def analyze_seating_requirements(self): + """分析人员连坐需求""" + self.logger.log("\n=== 人员连坐需求分析 ===") + + self.seating_groups = [] + i = 0 + + while i < len(self.personnel_df): + person = self.personnel_df.iloc[i] + remark = person['备注'] + + if pd.isna(remark): + # 无备注，单独坐 + self.seating_groups.append({ + 'type': 'single', + 'size': 1, + 'members': [person], + 'leader': person['姓名'] + }) + i += 1 + else: + # 有备注，按备注数量连坐 + group_size = int(remark) + group_members = [] + + # 收集连坐组成员 + for j in range(group_size): + if i + j < len(self.personnel_df): + group_members.append(self.personnel_df.iloc[i + j]) + + self.seating_groups.append({ + 'type': 'group' if group_size > 1 else 'single', + 'size': len(group_members), + 'members': group_members, + 'leader': person['姓名'] + }) + + i += group_size + + # 统计 + size_stats = {} + for group in self.seating_groups: + size = group['size'] + size_stats[size] = size_stats.get(size, 0) + 1 + + self.logger.log(f"总共识别出 {len(self.seating_groups)} 个座位组:") + for size in sorted(size_stats.keys()): + count = size_stats[size] + if size == 1: + self.logger.log(f" 单人组: {count} 个") + else: + self.logger.log(f" {size}人连坐组: {count} 个") + + return True + + def analyze_seat_structure_advanced(self): + """高级座位结构分析，识别连续段""" + self.logger.log("\n=== 高级座位结构分析 ===") + + seat_groups = {} + for _, row in self.seat_df.iterrows(): + key = (row['区域'], row['楼层'], row['排号']) + if key not in seat_groups: + seat_groups[key] = [] + seat_groups[key].append({ + 'index': row.name, + '座位号': row['座位号'], + 'row_data': row + }) + + # 分析每排的连续段 + self.row_analysis = {} + for key, seats in seat_groups.items(): + area, floor, row_num = key + + # 按座位号排序 + def get_seat_number(seat_info): + try: + return int(seat_info['座位号'].replace('号', '')) + except: + return 0 + + seats.sort(key=get_seat_number) + seat_numbers = [get_seat_number(seat) for seat in seats] + + # 找出所有连续段 + consecutive_segments = [] + if seat_numbers: + current_segment_start = 0 + + for i in range(1, len(seat_numbers)): + if seat_numbers[i] - seat_numbers[i-1] != 1: + # 发现间隙，结束当前段 + consecutive_segments.append({ + 'start_idx': current_segment_start, + 'end_idx': i - 1, + 'size': i - current_segment_start, + 'seat_numbers': seat_numbers[current_segment_start:i], + 'seats': seats[current_segment_start:i] + }) + current_segment_start = i + + # 添加最后一段 + consecutive_segments.append({ + 'start_idx': current_segment_start, + 'end_idx': len(seat_numbers) - 1, + 'size': len(seat_numbers) - current_segment_start, + 'seat_numbers': seat_numbers[current_segment_start:], + 'seats': seats[current_segment_start:] + }) + + self.row_analysis[key] = { + 'total_seats': len(seats), + 'all_seats': seats, + 'consecutive_segments': consecutive_segments, + 'max_consecutive': max(seg['size'] for seg in consecutive_segments) if consecutive_segments else 0 + } + + # 显示分析结果 + if len(consecutive_segments) == 1: + self.logger.log(f"✅ {area}-{floor}-{row_num}: {len(seats)} 个座位完全连续") + else: + segments_info = [] + for seg in consecutive_segments: + if seg['size'] == 1: + segments_info.append(f"{seg['seat_numbers'][0]}") + else: + segments_info.append(f"{seg['seat_numbers'][0]}-{seg['seat_numbers'][-1]}") + self.logger.log(f"📊 {area}-{floor}-{row_num}: {len(seats)} 个座位，{len(consecutive_segments)} 段: {', '.join(segments_info)}") + self.logger.log(f" 最大连续段: {self.row_analysis[key]['max_consecutive']} 个座位") + + return True + + def smart_seat_assignment(self): + """智能座位分配算法""" + self.logger.log("\n=== 开始智能座位分配 ===") + + # 按组大小排序，大组优先分配 + sorted_groups = sorted(self.seating_groups, key=lambda x: x['size'], reverse=True) + + # 创建座位分配结果 + seat_df_copy = self.seat_df.copy() + + # 记录已使用的座位 + used_seats = set() + + assignment_log = [] + unassigned_groups = [] + + self.logger.log(f"需要分配 {len(sorted_groups)} 个组") + + for group_idx, seating_group in enumerate(sorted_groups): + group_size = seating_group['size'] + group_type = seating_group['type'] + leader = seating_group['leader'] + + self.logger.log(f"\n处理第 {group_idx + 1} 组: {leader} ({group_type}, {group_size} 人)") + + if group_size == 1: + # 单人组，找任意可用座位 + assigned = False + for (area, floor, row_num), analysis in self.row_analysis.items(): + for seat_info in analysis['all_seats']: + if seat_info['index'] not in used_seats: + # 分配座位 + person_info = seating_group['members'][0] + seat_index = seat_info['index'] + + # 更新座位信息，确保数据类型正确 + seat_df_copy.loc[seat_index, '姓名'] = str(person_info['姓名']).strip() + seat_df_copy.loc[seat_index, '证件类型'] = str(person_info['证件类型']).strip() + seat_df_copy.loc[seat_index, '证件号'] = str(person_info['证件号']).strip() + seat_df_copy.loc[seat_index, '手机国家号'] = person_info.get('Unnamed: 3', 86) + seat_df_copy.loc[seat_index, '手机号'] = str(person_info['手机号']).strip() + seat_df_copy.loc[seat_index, '签发地/国籍'] = str(person_info.get('备注', '')).strip() + + assignment_log.append({ + '组号': group_idx + 1, + '组类型': group_type, + '组大小': group_size, + '组长': leader, + '姓名': person_info['姓名'], + '区域': area, + '楼层': floor, + '排号': row_num, + '座位号': seat_info['座位号'] + }) + + used_seats.add(seat_index) + self.logger.log(f" 分配到 {area}-{floor}-{row_num}: {person_info['姓名']} -> {seat_info['座位号']}") + assigned = True + break + if assigned: + break + else: + # 多人组，需要连续座位 + # 更新可用座位分析（排除已使用的座位） + current_row_analysis = {} + for key, analysis in self.row_analysis.items(): + available_seats = [seat for seat in analysis['all_seats'] if seat['index'] not in used_seats] + if available_seats: + # 重新分析连续段 + available_seats.sort(key=lambda x: int(x['座位号'].replace('号', ''))) + seat_numbers = [int(seat['座位号'].replace('号', '')) for seat in available_seats] + + # 找出连续段 + consecutive_segments = [] + if seat_numbers: + current_segment_start = 0 + + for i in range(1, len(seat_numbers)): + if seat_numbers[i] - seat_numbers[i-1] != 1: + consecutive_segments.append({ + 'start_idx': current_segment_start, + 'end_idx': i - 1, + 'size': i - current_segment_start, + 'seats': available_seats[current_segment_start:i] + }) + current_segment_start = i + + consecutive_segments.append({ + 'start_idx': current_segment_start, + 'end_idx': len(seat_numbers) - 1, + 'size': len(seat_numbers) - current_segment_start, + 'seats': available_seats[current_segment_start:] + }) + + current_row_analysis[key] = { + 'consecutive_segments': consecutive_segments + } + + # 寻找合适的连续座位 + assigned = False + for (area, floor, row_num), analysis in current_row_analysis.items(): + for segment in analysis['consecutive_segments']: + if segment['size'] >= group_size: + # 找到合适的连续座位 + seats_to_use = segment['seats'][:group_size] + seat_numbers = [int(seat['座位号'].replace('号', '')) for seat in seats_to_use] + + self.logger.log(f" 分配到 {area}-{floor}-{row_num} (连续座位: {min(seat_numbers)}-{max(seat_numbers)})") + + # 分配座位 + for i, seat_info in enumerate(seats_to_use): + person_info = seating_group['members'][i] + seat_index = seat_info['index'] + + seat_df_copy.loc[seat_index, '姓名'] = str(person_info['姓名']).strip() + seat_df_copy.loc[seat_index, '证件类型'] = str(person_info['证件类型']).strip() + seat_df_copy.loc[seat_index, '证件号'] = str(person_info['证件号']).strip() + seat_df_copy.loc[seat_index, '手机国家号'] = person_info.get('Unnamed: 3', 86) + seat_df_copy.loc[seat_index, '手机号'] = str(person_info['手机号']).strip() + seat_df_copy.loc[seat_index, '签发地/国籍'] = str(person_info.get('备注', '')).strip() + + assignment_log.append({ + '组号': group_idx + 1, + '组类型': group_type, + '组大小': group_size, + '组长': leader, + '姓名': person_info['姓名'], + '区域': area, + '楼层': floor, + '排号': row_num, + '座位号': seat_info['座位号'] + }) + + used_seats.add(seat_index) + self.logger.log(f" {person_info['姓名']} -> {seat_info['座位号']}") + + assigned = True + break + if assigned: + break + + if not assigned: + self.logger.log(f" ❌ 无法为第 {group_idx + 1} 组分配座位") + unassigned_groups.append(seating_group) + + # 显示未分配的组 + if unassigned_groups: + self.logger.log(f"\n⚠️ 有 {len(unassigned_groups)} 个组未能分配座位") + for group in unassigned_groups: + if group['type'] == 'single': + self.logger.log(f" 未分配: {group['leader']}") + else: + member_names = [member['姓名'] for member in group['members']] + self.logger.log(f" 未分配: {', '.join(member_names)} (连坐 {group['size']} 人)") + + return seat_df_copy, assignment_log + + def save_results(self, seat_df_result, assignment_log): + """保存分配结果""" + try: + # 保存更新后的座位信息 + output_file = '座位信息_最终分配.xlsx' + seat_df_result.to_excel(output_file, index=False) + self.logger.log(f"\n座位分配结果已保存到: {output_file}") + + # 保存分配日志 + if assignment_log: + log_df = pd.DataFrame(assignment_log) + log_file = '最终座位分配日志.xlsx' + log_df.to_excel(log_file, index=False) + self.logger.log(f"分配日志已保存到: {log_file}") + + # 显示分配统计 + self.logger.log(f"\n=== 分配统计 ===") + self.logger.log(f"总共分配了 {len(assignment_log)} 个座位") + + # 按组大小统计 + size_stats = log_df.groupby('组大小').agg({ + '姓名': 'count', + '组号': 'nunique' + }).rename(columns={'姓名': '总人数', '组号': '组数'}) + + self.logger.log("\n按组大小统计:") + for size, row in size_stats.iterrows(): + if size == 1: + self.logger.log(f" 单人组: {row['组数']} 个组, {row['总人数']} 人") + else: + self.logger.log(f" {size}人连坐组: {row['组数']} 个组, {row['总人数']} 人") + + # 验证连续性 + self.logger.log("\n=== 连续性验证 ===") + consecutive_check = [] + + for group_num in sorted(log_df['组号'].unique()): + group_data = log_df[log_df['组号'] == group_num] + group_size = group_data.iloc[0]['组大小'] + group_leader = group_data.iloc[0]['组长'] + + if group_size > 1: # 多人组 + # 检查是否在同一排 + areas = group_data['区域'].unique() + floors = group_data['楼层'].unique() + rows = group_data['排号'].unique() + + if len(areas) == 1 and len(floors) == 1 and len(rows) == 1: + # 在同一排，检查座位号是否连续 + seats = group_data['座位号'].tolist() + seat_numbers = [] + for seat in seats: + try: + seat_numbers.append(int(seat.replace('号', ''))) + except: + seat_numbers.append(0) + + seat_numbers.sort() + is_consecutive = all(seat_numbers[i] + 1 == seat_numbers[i+1] for i in range(len(seat_numbers)-1)) + + if is_consecutive: + consecutive_check.append(True) + self.logger.log(f"✅ 组 {group_num} ({group_leader}): {group_size}人连坐，座位连续 {seat_numbers}") + else: + consecutive_check.append(False) + self.logger.log(f"❌ 组 {group_num} ({group_leader}): {group_size}人连坐，座位不连续 {seat_numbers}") + else: + consecutive_check.append(False) + self.logger.log(f"❌ 组 {group_num} ({group_leader}): 不在同一排") + + success_rate = sum(consecutive_check) / len(consecutive_check) * 100 if consecutive_check else 100 + self.logger.log(f"\n连续性检查结果: {sum(consecutive_check)}/{len(consecutive_check)} 个多人组座位连续 ({success_rate:.1f}%)") + + return True + except Exception as e: + self.logger.log(f"保存结果时出错: {e}") + return False + + def run_validation(self): + """运行完整的文件校验""" + self.logger.log("=" * 60) + self.logger.log("座位分配系统 - 文件校验") + self.logger.log("=" * 60) + + # 加载数据 + if not self.load_data(): + return False + + # 人员信息结构校验 + personnel_structure_valid = self.validate_personnel_structure() + + # 连坐组校验 + seating_groups_valid, group_issues = self.validate_seating_groups() + + # 座位信息校验 + seat_structure_valid, seat_groups = self.validate_seat_structure() + + # 容量可行性校验 + capacity_valid = self.validate_capacity_feasibility(seat_groups) + + # 总结 + self.logger.log("\n" + "=" * 60) + self.logger.log("校验结果总结") + self.logger.log("=" * 60) + + all_valid = all([ + personnel_structure_valid, + seating_groups_valid, + seat_structure_valid, + capacity_valid + ]) + + self.logger.log(f"人员信息结构: {'✅ 通过' if personnel_structure_valid else '❌ 失败'}") + self.logger.log(f"连坐组完整性: {'✅ 通过' if seating_groups_valid else '❌ 失败'}") + self.logger.log(f"座位信息结构: {'✅ 通过' if seat_structure_valid else '❌ 失败'}") + self.logger.log(f"容量可行性: {'✅ 通过' if capacity_valid else '❌ 失败'}") + + self.logger.log(f"\n总体校验结果: {'✅ 全部通过' if all_valid else '❌ 存在问题'}") + + if group_issues: + self.logger.log(f"\n发现的问题:") + for issue in group_issues: + self.logger.log(f" {issue}") + + if all_valid: + self.logger.log("\n🎉 文件校验通过，可以进行座位分配！") + else: + self.logger.log("\n⚠️ 请修复上述问题后再进行座位分配。") + + return all_valid + + def run_allocation(self): + """运行完整的座位分配""" + self.logger.log("\n" + "=" * 60) + self.logger.log("开始座位分配") + self.logger.log("=" * 60) + + # 分析人员连坐需求 + if not self.analyze_seating_requirements(): + return False + + # 高级座位结构分析 + if not self.analyze_seat_structure_advanced(): + return False + + # 执行智能座位分配 + seat_df_result, assignment_log = self.smart_seat_assignment() + + # 保存结果 + if self.save_results(seat_df_result, assignment_log): + self.logger.log("\n🎉 座位分配完成！") + return True + else: + self.logger.log("\n❌ 座位分配失败！") + return False + +def main(): + """主函数""" + system = SeatAllocationSystem() + + try: + # 运行校验 + if system.run_validation(): + # 校验通过，运行分配 + system.run_allocation() + + # 保存日志 + system.logger.save_logs() + + except Exception as e: + system.logger.log(f"系统运行出错: {e}") + system.logger.save_logs() + +if __name__ == "__main__": + main() diff --git a/simple_build.py b/simple_build.py new file mode 100644 index 0000000..91497e1 --- /dev/null +++ b/simple_build.py @@ -0,0 +1,232 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +简化构建脚本 +在当前平台构建可执行文件 +""" + +import os +import sys +import subprocess +import platform +import shutil +from pathlib import Path + +def get_platform_info(): + """获取平台信息""" + system = platform.system() + machine = platform.machine().lower() + + if system == 'Windows': + if machine in ['amd64', 'x86_64']: + return 'windows_x64' + elif machine in ['i386', 'i686', 'x86']: + return 'windows_x86' + else: + return f'windows_{machine}' + elif system == 'Darwin': + if machine in ['arm64', 'aarch64']: + return 'macos_arm64' + else: + return 'macos_x64' + elif system == 'Linux': + return f'linux_{machine}' + else: + return f'{system.lower()}_{machine}' + +def install_dependencies(): + """安装依赖""" + print("安装依赖包...") + packages = ['pandas', 'openpyxl', 'pyinstaller'] + + for package in packages: + try: + __import__(package) + print(f"✅ {package} 已安装") + except ImportError: + print(f"📦 安装 {package}...") + try: + subprocess.check_call([sys.executable, '-m', 'pip', 'install', package]) + print(f"✅ {package} 安装成功") + except subprocess.CalledProcessError: + print(f"❌ {package} 安装失败") + return False + return True + +def build_executable(): + """构建可执行文件""" + print("\n开始构建可执行文件...") + + # 获取平台信息 + platform_name = get_platform_info() + exe_name = f"座位分配系统_{platform_name}" + + print(f"目标平台: {platform_name}") + print(f"输出文件: {exe_name}") + + # 清理之前的构建 + if os.path.exists('dist'): + shutil.rmtree('dist') + if os.path.exists('build'): + shutil.rmtree('build') + + # 构建命令 + cmd = [ + sys.executable, '-m', 'PyInstaller', + '--onefile', + '--console', + '--clean', + '--name', exe_name, + 'seat_allocation_system.py' + ] + + try: + print(f"执行命令: {' '.join(cmd)}") + result = subprocess.run(cmd, capture_output=True, text=True) + + if result.returncode == 0: + print("✅ 构建成功!") + + # 检查生成的文件 + if platform.system() == 'Windows': + exe_path = Path('dist') / f'{exe_name}.exe' + else: + exe_path = Path('dist') / exe_name + + if exe_path.exists(): + file_size = exe_path.stat().st_size / (1024 * 1024) # MB + print(f"生成文件: {exe_path}") + print(f"文件大小: {file_size:.1f} MB") + return True, exe_path + else: + print("❌ 未找到生成的文件") + return False, None + else: + print("❌ 构建失败!") + print("错误输出:") + print(result.stderr) + return False, None + + except Exception as e: + print(f"❌ 构建过程中出现错误: {e}") + return False, None + +def create_distribution(): + """创建分发包""" + print("\n创建分发包...") + + platform_name = get_platform_info() + package_name = f"座位分配系统_{platform_name}_分发包" + package_dir = Path(package_name) + + # 创建分发目录 + if package_dir.exists(): + shutil.rmtree(package_dir) + package_dir.mkdir() + + # 复制可执行文件 + dist_dir = Path('dist') + if dist_dir.exists(): + for file in dist_dir.iterdir(): + if file.is_file(): + shutil.copy2(file, package_dir) + print(f"复制文件: {file.name}") + + # 复制示例文件 + if Path('人员信息.xlsx').exists(): + shutil.copy2('人员信息.xlsx', package_dir / '人员信息_示例.xlsx') + print("复制示例文件: 人员信息_示例.xlsx") + + if Path('座位信息.xlsx').exists(): + shutil.copy2('座位信息.xlsx', package_dir / '座位信息_示例.xlsx') + print("复制示例文件: 座位信息_示例.xlsx") + + # 创建使用说明 + readme_content = f"""座位分配系统 使用说明 + +平台: {platform_name} +构建时间: {platform.platform()} + +使用方法: +1. 准备Excel文件 + - 人员信息.xlsx: 包含姓名、证件信息、备注等 + - 座位信息.xlsx: 包含区域、楼层、排号、座位号等 + +2. 运行程序 + - 将可执行文件放在Excel文件同一目录 + - 双击运行可执行文件 + - 等待处理完成 + +3. 查看结果 + - 座位信息_最终分配.xlsx: 分配结果 + - 最终座位分配日志.xlsx: 详细记录 + - seat_allocation_log.txt: 运行日志 + +功能特点: +- 支持1-10人连坐需求 +- 自动处理不连续座位 +- 完整的数据校验 +- 详细的分配日志 + +注意事项: +- 确保Excel文件格式正确 +- 备注数字表示连坐人数 +- 运行时会在同目录生成结果文件 +""" + + with open(package_dir / '使用说明.txt', 'w', encoding='utf-8') as f: + f.write(readme_content) + + print(f"✅ 分发包已创建: {package_dir}") + return package_dir + +def main(): + """主函数""" + print("座位分配系统 - 简化构建工具") + print("=" * 50) + + # 显示系统信息 + print(f"系统: {platform.system()} {platform.release()}") + print(f"架构: {platform.machine()}") + print(f"Python: {sys.version}") + + # 检查主程序文件 + if not os.path.exists('seat_allocation_system.py'): + print("❌ 未找到 seat_allocation_system.py 文件") + return + + # 安装依赖 + if not install_dependencies(): + print("❌ 依赖安装失败") + return + + # 构建可执行文件 + success, exe_path = build_executable() + if not success: + print("❌ 构建失败") + return + + # 创建分发包 + package_dir = create_distribution() + + print("\n🎉 构建完成!") + print(f"✅ 可执行文件: {exe_path}") + print(f"✅ 分发包: {package_dir}") + + # 平台特定说明 + if platform.system() == 'Windows': + print("\n📝 Windows使用说明:") + print("- 可以直接在Windows系统上运行") + print("- 确保安装了Visual C++ Redistributable") + elif platform.system() == 'Darwin': + print("\n📝 macOS使用说明:") + print("- 只能在macOS系统上运行") + print("- 如需Windows版本，请在Windows系统上构建") + print("- 或使用GitHub Actions自动构建") + else: + print(f"\n📝 {platform.system()}使用说明:") + print("- 只能在相同系统上运行") + print("- 如需其他平台版本，请在对应系统上构建") + +if __name__ == "__main__": + main() diff --git a/人员信息.xlsx b/人员信息.xlsx new file mode 100644 index 0000000..366820a Binary files /dev/null and b/人员信息.xlsx differ diff --git a/座位信息.xlsx b/座位信息.xlsx new file mode 100644 index 0000000..e09103c Binary files /dev/null and b/座位信息.xlsx differ