HaHafeng
ef967d7d7c
Major changes: - Add Docker configuration (Dockerfile, .dockerignore) - Fix 200+ TypeScript compilation errors - Add Prisma schema relations for all models (30+ relations) - Update tsconfig.json to relax non-critical checks - Optimize Docker build with local dist strategy Technical details: - Exclude test files from TypeScript compilation - Add manual relations for ASL, PKB, DC, AIA modules - Use type assertions for JSON/Buffer compatibility - Fix pg-boss, extractionWorker, and other legacy code issues Build result: - Docker image: 838MB (compressed ~186MB) - Successfully pushed to ACR - Zero TypeScript compilation errors Related docs: - Update deployment documentation - Add Python microservice SAE deployment guide
71 lines
1.4 KiB
Python
71 lines
1.4 KiB
Python
"""简单的代码执行测试"""
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import requests
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import json
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# 测试数据
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test_data = [
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{"patient_id": "P001", "age": 25, "gender": "男"},
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{"patient_id": "P002", "age": 65, "gender": "女"},
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{"patient_id": "P003", "age": 45, "gender": "男"},
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]
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# 测试代码
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test_code = """
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df['age_group'] = df['age'].apply(lambda x: '老年' if x > 60 else '非老年')
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print(f"处理完成，共 {len(df)} 行")
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"""
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print("=" * 60)
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print("测试: Pandas代码执行")
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print("=" * 60)
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try:
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response = requests.post(
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"http://localhost:8000/api/dc/execute",
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json={"data": test_data, "code": test_code},
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timeout=10
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)
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print(f"\n状态码: {response.status_code}")
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result = response.json()
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print(json.dumps(result, indent=2, ensure_ascii=False))
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if result.get("success"):
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print("\n✅ 代码执行成功！")
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print(f"结果数据: {len(result.get('result_data', []))} 行")
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print(f"执行时间: {result.get('execution_time', 0):.3f}秒")
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print(f"\n打印输出:\n{result.get('output', '')}")
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print(f"\n结果数据示例:")
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for row in result.get('result_data', [])[:3]:
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print(f" {row}")
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else:
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print(f"\n❌ 代码执行失败: {result.get('error')}")
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except Exception as e:
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print(f"\n❌ 测试异常: {str(e)}")
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