Summary: - Complete IIT Manager Agent MVP Day 1 (12.5% progress) - Database: Create iit_schema with 5 tables (IitProject, IitPendingAction, IitTaskRun, IitUserMapping, IitAuditLog) - Backend: Add module structure (577 lines) and types (223 lines) - WeChat: Configure Enterprise WeChat app (CorpID, AgentID, Secret) - WeChat: Obtain web authorization and JS-SDK authorization - WeChat: Configure trusted domain (iit.xunzhengyixue.com) - Frontend: Deploy v1.2 with WeChat domain verification file - Frontend: Fix CRLF issue in docker-entrypoint.sh (CRLF -> LF) - Testing: 11/11 database CRUD tests passed - Testing: Access Token retrieval test passed - Docs: Create module status and development guide - Docs: Update MVP task list with Day 1 completion - Docs: Rename deployment doc to SAE real-time status record - Deployment: Update frontend internal IP to 172.17.173.80 Technical Details: - Prisma: Multi-schema support (iit_schema) - pg-boss: Job queue integration prepared - Taro 4.x: Framework selected for WeChat Mini Program - Shadow State: Architecture foundation laid - Docker: Fix entrypoint script line endings for Linux container Status: Day 1/14 complete, ready for Day 2 REDCap integration
60 lines
884 B
Python
60 lines
884 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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