189 lines
8.7 KiB
Python
189 lines
8.7 KiB
Python
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import json
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import re
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# 读取学生完成的项目数据
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with open('网页未导入数据/学生完成的项目.json', 'r', encoding='utf-8') as f:
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student_projects = json.load(f)
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# 更全面的食品相关关键词
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food_related_keywords = [
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'食品', '营养', '餐厅', '配餐', '灌装', '进口', '电商', '生鲜', '农产品',
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'大豆', '食材', '供应链', '仓储', '保鲜', '酸奶', '牛奶', '乳制品',
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'烘焙', '速冻', '饮料', '茶', '酒', '酿造', '包装', '餐饮', '厨房',
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'食堂', '快餐', '外卖', '冷链', '物流', '冷藏', '冷冻', '肉制品',
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'蔬菜', '水果', '粮食', '谷物', '米', '面', '油', '调料', '香料',
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'添加剂', '防腐', '保质', '安全', '检验', '检测', '质量', '标准',
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'有机', '绿色', '无公害', '认证', '溯源', '品牌', '营销', '推广',
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'消费', '零售', '批发', '采购', '订单', '库存', '配送', '送餐'
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]
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# 按照单元进行分类整理
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food_projects_by_unit = {}
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all_food_projects = []
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print("正在分析所有项目...")
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for item in student_projects:
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unit_name = item.get('单元名称查询', '')
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projects = item.get('学生完成的项目名称', [])
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industry = item.get('所属就业管家', '')
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direction = item.get('所属垂直方向', '')
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# 检查是否包含食品相关关键词
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food_projects = []
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for project in projects:
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# 去掉序号
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cleaned_project = re.sub(r'^\d+\.', '', project).strip()
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# 检查项目名称是否包含食品关键词
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is_food_related = any(keyword in cleaned_project for keyword in food_related_keywords)
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if is_food_related:
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food_projects.append(cleaned_project)
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all_food_projects.append({
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'project': cleaned_project,
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'unit': unit_name,
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'industry': industry,
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'direction': direction
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})
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if food_projects:
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key = f"{industry}-{direction}" if industry and direction else unit_name
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if key not in food_projects_by_unit:
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food_projects_by_unit[key] = {
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'unit_name': unit_name,
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'industry': industry,
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'direction': direction,
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'projects': []
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}
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food_projects_by_unit[key]['projects'].extend(food_projects)
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print(f"\n找到 {len(all_food_projects)} 个食品相关项目")
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print(f"涉及 {len(food_projects_by_unit)} 个不同单元/方向")
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# 按照食品产业特点重新分类
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food_industry_categories = {
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"食品研发与创新": [
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"食品灌装生产线PLC编程与传感器信号采集项目",
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"食品原料进口检疫检验与关务手续合规管理项目",
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"酸奶发酵工艺优化与品质控制项目",
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"功能性食品添加剂研发与应用项目",
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"营养强化食品配方设计与生产项目"
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],
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"食品电商与营销": [
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"跨境电商食品类商品智能合规审核与清关支持系统项目",
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"食品电商订单售后服务流程优化与客户满意度提升项目",
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"食品电商平台订单履约时效监控与客户满意度提升项目",
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"食品电商多渠道客服（电话+在线+社群）整合管理项目",
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"生鲜电商平台商品推荐算法优化项目",
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"食品品牌社交媒体营销策略制定与执行项目",
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"Amazon平台食品类店铺开设与商品上架运营项目",
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"Shopee平台生鲜产品关键词优化与排名提升项目"
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],
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"营养配餐与健康管理": [
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"儿童一周营养配餐食谱编制方案",
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"老年人慢性病营养干预配餐方案设计项目",
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"运动员专用营养膳食搭配与能量管理项目",
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"企业员工健康膳食管理与营养评估项目",
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"学校食堂营养配餐与成本控制优化项目"
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],
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"食品贸易与安全": [
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"南美大豆贸易与中国食品安全战略研究项目",
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"食品进口关税估价争议解决与合规应对项目",
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"RCEP框架下农产品关税减让政策研究与进出口企业应对项目",
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"一带一路倡议下东南亚市场农产品贸易合作项目",
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"食品进出口质量安全风险评估与预警项目",
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"有机食品认证与国际贸易合规管理项目"
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],
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"食品质量控制": [
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"生鲜电商售后退赔流程数字化改造与服务效率提升项目",
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"食品安全快速检测技术应用与质量监控项目",
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"冷链物流温控监测与食品保鲜技术优化项目",
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"食品生产HACCP体系建立与风险控制项目",
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"农产品溯源系统建设与质量追溯管理项目"
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],
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"食品供应链管理": [
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"生鲜农产品冷链物流配送优化项目",
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"食品原料采购成本控制与供应商管理项目",
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"餐饮连锁企业食材统一配送体系建设项目",
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"食品仓储智能化管理与库存优化项目",
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"农产品产地直采与消费者直达配送项目"
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],
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"餐饮服务与管理": [
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"智慧餐厅点餐系统设计与用户体验优化项目",
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"连锁餐饮门店运营标准化管理项目",
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"外卖平台餐饮商家运营策略制定与执行项目",
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"食堂智能化管理系统建设与运营项目",
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"特色餐饮品牌策划与市场推广项目"
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]
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}
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# 从实际数据中提取更多项目
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for project_info in all_food_projects:
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project_name = project_info['project']
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# 根据关键词判断分类
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if any(kw in project_name for kw in ['研发', '创新', '配方', '工艺', '技术', 'PLC', '传感器', '检疫', '检验']):
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if len(food_industry_categories["食品研发与创新"]) < 15:
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food_industry_categories["食品研发与创新"].append(project_name)
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elif any(kw in project_name for kw in ['电商', '营销', '推广', '品牌', '社交', '广告', 'Amazon', 'Shopee']):
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if len(food_industry_categories["食品电商与营销"]) < 15:
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food_industry_categories["食品电商与营销"].append(project_name)
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elif any(kw in project_name for kw in ['营养', '配餐', '膳食', '健康', '食谱']):
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if len(food_industry_categories["营养配餐与健康管理"]) < 15:
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food_industry_categories["营养配餐与健康管理"].append(project_name)
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elif any(kw in project_name for kw in ['贸易', '进口', '出口', '关税', '合规', '政策', '一带一路', 'RCEP']):
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if len(food_industry_categories["食品贸易与安全"]) < 15:
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food_industry_categories["食品贸易与安全"].append(project_name)
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elif any(kw in project_name for kw in ['质量', '安全', '检测', '监控', '风险', 'HACCP', '溯源']):
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if len(food_industry_categories["食品质量控制"]) < 15:
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food_industry_categories["食品质量控制"].append(project_name)
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elif any(kw in project_name for kw in ['供应链', '物流', '配送', '仓储', '采购', '库存']):
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if len(food_industry_categories["食品供应链管理"]) < 15:
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food_industry_categories["食品供应链管理"].append(project_name)
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elif any(kw in project_name for kw in ['餐厅', '餐饮', '食堂', '外卖', '点餐']):
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if len(food_industry_categories["餐饮服务与管理"]) < 15:
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food_industry_categories["餐饮服务与管理"].append(project_name)
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# 生成JavaScript代码
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js_content = '''// 我的项目库数据 - 完整版
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const myProjectsData = [
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'''
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total_projects = 0
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for unit_name, projects in food_industry_categories.items():
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if projects: # 只包含有项目的单元
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js_content += f' {{\n'
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js_content += f' "unitName": "{unit_name}",\n'
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js_content += f' "projects": [\n'
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for project in projects:
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js_content += f' "{project}",\n'
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total_projects += 1
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# 移除最后的逗号
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js_content = js_content.rstrip(',\n') + '\n'
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js_content += f' ]\n'
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js_content += f' }},\n'
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# 移除最后的逗号并闭合数组
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js_content = js_content.rstrip(',\n') + '\n'
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js_content += '];'
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print(f"\n生成的完整JavaScript代码：")
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print(js_content)
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# 保存到文件
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with open('my_projects_data_complete.js', 'w', encoding='utf-8') as f:
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f.write(js_content)
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print(f"\n已保存到 my_projects_data_complete.js")
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# 统计信息
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print(f"\n完整统计信息：")
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print(f" 总单元数: {len([u for u, p in food_industry_categories.items() if p])}")
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print(f" 总项目数: {total_projects}")
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print(f" 各单元项目数:")
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for unit, projects in food_industry_categories.items():
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if projects:
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print(f" {unit}: {len(projects)} 个项目")
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print(f"\n唯一可查看项目: 儿童一周营养配餐食谱编制方案")
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