HaHafeng
b64896a307
Summary: - PostgreSQL database migration to RDS completed (90MB SQL, 11 schemas) - Frontend Nginx Docker image built and pushed to ACR (v1.0, ~50MB) - Python microservice Docker image built and pushed to ACR (v1.0, 1.12GB) - Created 3 deployment documentation files Docker Configuration Files: - frontend-v2/Dockerfile: Multi-stage build with nginx:alpine - frontend-v2/.dockerignore: Optimize build context - frontend-v2/nginx.conf: SPA routing and API proxy - frontend-v2/docker-entrypoint.sh: Dynamic env injection - extraction_service/Dockerfile: Multi-stage build with Aliyun Debian mirror - extraction_service/.dockerignore: Optimize build context - extraction_service/requirements-prod.txt: Production dependencies (removed Nougat) Deployment Documentation: - docs/05-部署文档/00-部署进度总览.md: One-stop deployment status overview - docs/05-部署文档/07-前端Nginx-SAE部署操作手册.md: Frontend deployment guide - docs/05-部署文档/08-PostgreSQL数据库部署操作手册.md: Database deployment guide - docs/00-系统总体设计/00-系统当前状态与开发指南.md: Updated with deployment status Database Migration: - RDS instance: pgm-2zex1m2y3r23hdn5 (2C4G, PostgreSQL 15.0) - Database: ai_clinical_research - Schemas: 11 business schemas migrated successfully - Data: 3 users, 2 projects, 1204 literatures verified - Backup: rds_init_20251224_154529.sql (90MB) Docker Images: - Frontend: crpi-cd5ij4pjt65mweeo.cn-beijing.personal.cr.aliyuncs.com/ai-clinical/ai-clinical_frontend-nginx:v1.0 - Python: crpi-cd5ij4pjt65mweeo.cn-beijing.personal.cr.aliyuncs.com/ai-clinical/python-extraction:v1.0 Key Achievements: - Resolved Docker Hub network issues (using generic tags) - Fixed 30 TypeScript compilation errors - Removed Nougat OCR to reduce image size by 1.5GB - Used Aliyun Debian mirror to resolve apt-get network issues - Implemented multi-stage builds for optimization Next Steps: - Deploy Python microservice to SAE - Build Node.js backend Docker image - Deploy Node.js backend to SAE - Deploy frontend Nginx to SAE - End-to-end verification testing Status: Docker images ready, SAE deployment pending
50 lines
874 B
Python
50 lines
874 B
Python
"""测试dc_executor模块"""
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print("测试dc_executor模块导入...")
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try:
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from services.dc_executor import validate_code, execute_pandas_code
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print("✅ 模块导入成功")
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# 测试验证功能
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print("\n测试validate_code...")
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result = validate_code("df['x'] = 1")
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print(f"✅ validate_code成功: {result}")
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# 测试执行功能
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print("\n测试execute_pandas_code...")
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test_data = [{"age": 25}, {"age": 65}]
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result = execute_pandas_code(test_data, "df['old'] = df['age'] > 60")
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print(f"✅ execute_pandas_code成功: success={result['success']}")
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if result['success']:
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print(f" 结果: {result['result_data']}")
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print("\n🎉 所有模块测试通过！")
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except Exception as e:
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print(f"❌ 测试失败: {e}")
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import traceback
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traceback.print_exc()
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