Files
AIclinicalresearch/extraction_service/test_module.py
HaHafeng decff0bb1f docs(deploy): Complete full system deployment to Aliyun SAE
Summary:
- Successfully deployed complete system to Aliyun SAE (2025-12-25)
- All services running: Python microservice + Node.js backend + Frontend Nginx + CLB
- Public access available at http://8.140.53.236/

Major Achievements:
1. Python microservice deployed (v1.0, internal IP: 172.17.173.66:8000)
2. Node.js backend deployed (v1.3, internal IP: 172.17.173.73:3001)
   - Fixed 4 critical issues: bash path, config directory, pino-pretty, ES Module
3. Frontend Nginx deployed (v1.0, internal IP: 172.17.173.72:80)
4. CLB load balancer configured (public IP: 8.140.53.236)

New Documentation (9 docs):
- 11-Node.js backend SAE deployment config checklist (21 env vars)
- 12-Node.js backend SAE deployment operation manual
- 13-Node.js backend image fix record (config directory)
- 14-Node.js backend pino-pretty fix
- 15-Node.js backend deployment success summary
- 16-Frontend Nginx deployment success summary
- 17-Complete deployment practical manual 2025 edition (1800 lines)
- 18-Deployment documentation usage guide
- 19-Daily update quick operation manual (670 lines)

Key Fixes:
- Environment variable name correction: EXTRACTION_SERVICE_URL (not PYTHON_SERVICE_URL)
- Dockerfile fix: added COPY config ./config
- Logger configuration: conditional pino-pretty for dev only
- Health check fix: ES Module compatibility (require -> import)

Updated Files:
- System status document updated with full deployment info
- Deployment progress overview updated with latest IPs
- All 3 Docker services' Dockerfiles and configs refined

Verification:
- All health checks passed
- Tool C 7 features working correctly
- Literature screening module functional
- Response time < 1 second

BREAKING CHANGE: Node.js backend internal IP changed from 172.17.173.71 to 172.17.173.73

Closes #deployment-milestone
2025-12-25 21:24:37 +08:00

53 lines
877 B
Python

"""测试dc_executor模块"""
print("测试dc_executor模块导入...")
try:
from services.dc_executor import validate_code, execute_pandas_code
print("✅ 模块导入成功")
# 测试验证功能
print("\n测试validate_code...")
result = validate_code("df['x'] = 1")
print(f"✅ validate_code成功: {result}")
# 测试执行功能
print("\n测试execute_pandas_code...")
test_data = [{"age": 25}, {"age": 65}]
result = execute_pandas_code(test_data, "df['old'] = df['age'] > 60")
print(f"✅ execute_pandas_code成功: success={result['success']}")
if result['success']:
print(f" 结果: {result['result_data']}")
print("\n🎉 所有模块测试通过!")
except Exception as e:
print(f"❌ 测试失败: {e}")
import traceback
traceback.print_exc()