Files
AIclinicalresearch/extraction_service/test_execute_simple.py
HaHafeng 691dc2bc98 docs(deploy): Update deployment documentation for Node.js backend
Summary:
- Created Node.js backend Docker image build guide
- Updated deployment progress overview with backend status
- Updated system status documentation

Backend build achievements:
- Fixed 200+ TypeScript compilation errors (200+ to 0)
- Completed Prisma reverse sync (32 models from RDS)
- Manually added 30+ Prisma relation fields
- Successfully built Docker image (838MB)
- Pushed image to ACR (v1.0 + latest tags)

Documentation updates:
- Added 10-Node.js后端-Docker镜像构建手册.md
- Updated 00-部署进度总览.md with backend deployment status
- Updated 00-系统当前状态与开发指南.md with latest progress
- Fixed date format (2024 -> 2025)

Next steps:
- Deploy Node.js backend to SAE
- Configure environment variables
- Test end-to-end functionality

Status: Backend Docker image ready for SAE deployment
2025-12-25 08:21:21 +08:00

72 lines
1.4 KiB
Python

"""简单的代码执行测试"""
import requests
import json
# 测试数据
test_data = [
{"patient_id": "P001", "age": 25, "gender": ""},
{"patient_id": "P002", "age": 65, "gender": ""},
{"patient_id": "P003", "age": 45, "gender": ""},
]
# 测试代码
test_code = """
df['age_group'] = df['age'].apply(lambda x: '老年' if x > 60 else '非老年')
print(f"处理完成,共 {len(df)} 行")
"""
print("=" * 60)
print("测试: Pandas代码执行")
print("=" * 60)
try:
response = requests.post(
"http://localhost:8000/api/dc/execute",
json={"data": test_data, "code": test_code},
timeout=10
)
print(f"\n状态码: {response.status_code}")
result = response.json()
print(json.dumps(result, indent=2, ensure_ascii=False))
if result.get("success"):
print("\n✅ 代码执行成功!")
print(f"结果数据: {len(result.get('result_data', []))}")
print(f"执行时间: {result.get('execution_time', 0):.3f}")
print(f"\n打印输出:\n{result.get('output', '')}")
print(f"\n结果数据示例:")
for row in result.get('result_data', [])[:3]:
print(f" {row}")
else:
print(f"\n❌ 代码执行失败: {result.get('error')}")
except Exception as e:
print(f"\n❌ 测试异常: {str(e)}")