179 lines
7.0 KiB
Python
179 lines
7.0 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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测试完整的数据转换和 SQL Server 写入流程
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"""
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import json
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from convert_table_to_sqlserver_format import convert_temperature_table_to_sqlserver
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# 实际的脚本返回数据
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script_data = {
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"tables": [{
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"token": "scriptTable1",
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"startRow": 0,
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"startCol": 0,
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"cells": [
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{"row": 4, "col": 0, "value": "14.0"},
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{"row": 4, "col": 1, "value": "14.2"},
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{"row": 4, "col": 2, "value": "14.2"},
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{"row": 4, "col": 3, "value": "14.3"},
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{"row": 4, "col": 4, "value": "14.1"},
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{"row": 4, "col": 5, "value": "13.9"},
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{"row": 4, "col": 6, "value": ""},
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{"row": 5, "col": 0, "value": "13.7"},
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{"row": 5, "col": 1, "value": "13.9"},
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{"row": 5, "col": 2, "value": "13.9"},
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{"row": 5, "col": 3, "value": "13.9"},
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{"row": 5, "col": 4, "value": "13.7"},
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{"row": 5, "col": 5, "value": "13.6"},
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{"row": 5, "col": 6, "value": ""},
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{"row": 6, "col": 0, "value": "14.5"},
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{"row": 6, "col": 1, "value": "14.7"},
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{"row": 6, "col": 2, "value": "14.8"},
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{"row": 6, "col": 3, "value": "14.8"},
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{"row": 6, "col": 4, "value": "14.8"},
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{"row": 6, "col": 5, "value": "14.7"},
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{"row": 6, "col": 6, "value": ""},
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{"row": 7, "col": 0, "value": "13.9"},
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{"row": 7, "col": 1, "value": "14.1"},
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{"row": 7, "col": 2, "value": "14.2"},
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{"row": 7, "col": 3, "value": "14.3"},
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{"row": 7, "col": 4, "value": "14.2"},
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{"row": 7, "col": 5, "value": "14.1"},
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{"row": 7, "col": 6, "value": ""},
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{"row": 9, "col": 0, "value": "13.8"},
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{"row": 9, "col": 1, "value": "13.9"},
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{"row": 9, "col": 2, "value": "14.0"},
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{"row": 9, "col": 3, "value": "14.0"},
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{"row": 9, "col": 4, "value": "13.9"},
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{"row": 9, "col": 5, "value": "13.9"},
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{"row": 9, "col": 6, "value": ""},
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{"row": 10, "col": 0, "value": "13.8"},
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{"row": 10, "col": 1, "value": "14.0"},
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{"row": 10, "col": 2, "value": "14.1"},
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{"row": 10, "col": 3, "value": "14.2"},
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{"row": 10, "col": 4, "value": "14.1"},
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{"row": 10, "col": 5, "value": "14.0"},
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{"row": 10, "col": 6, "value": ""},
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{"row": 11, "col": 0, "value": "12.5"},
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{"row": 11, "col": 1, "value": "12.7"},
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{"row": 11, "col": 2, "value": "12.8"},
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{"row": 11, "col": 3, "value": "12.9"},
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{"row": 11, "col": 4, "value": "12.8"},
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{"row": 11, "col": 5, "value": "12.7"},
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{"row": 11, "col": 6, "value": ""},
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{"row": 12, "col": 0, "value": "14.0"},
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{"row": 12, "col": 1, "value": "14.2"},
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{"row": 12, "col": 2, "value": "14.3"},
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{"row": 12, "col": 3, "value": "14.4"},
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{"row": 12, "col": 4, "value": "14.3"},
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{"row": 12, "col": 5, "value": "14.2"},
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{"row": 12, "col": 6, "value": ""},
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{"row": 13, "col": 0, "value": "13.5"},
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{"row": 13, "col": 1, "value": "13.7"},
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{"row": 13, "col": 2, "value": "13.7"},
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{"row": 13, "col": 3, "value": "13.8"},
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{"row": 13, "col": 4, "value": "13.7"},
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{"row": 13, "col": 5, "value": "13.5"},
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{"row": 13, "col": 6, "value": ""},
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{"row": 14, "col": 0, "value": "13.4"},
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{"row": 14, "col": 1, "value": "13.5"},
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{"row": 14, "col": 2, "value": "13.5"},
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{"row": 14, "col": 3, "value": "13.6"},
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{"row": 14, "col": 4, "value": "13.5"},
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{"row": 14, "col": 5, "value": "13.4"},
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{"row": 14, "col": 6, "value": ""},
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{"row": 15, "col": 0, "value": "14.8"},
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{"row": 15, "col": 1, "value": "15.0"},
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{"row": 15, "col": 2, "value": "15.1"},
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{"row": 15, "col": 3, "value": "15.2"},
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{"row": 15, "col": 4, "value": "15.1"},
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{"row": 15, "col": 5, "value": "15.0"},
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{"row": 15, "col": 6, "value": ""},
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{"row": 1, "col": 1, "value": "2025-12-05 14:00:00"},
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{"row": 1, "col": 3, "value": "2025-12-05 17:30:00"},
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{"row": 0, "col": 1, "value": "13.4"}
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]
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}]
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}
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work_order_no = "W2001150.001"
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print("=" * 80)
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print("完整数据转换流程测试")
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print("=" * 80)
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# 步骤1: 转换数据
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print("\n步骤1: 转换表格数据为 SQL Server 格式")
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print("-" * 80)
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converted_data = convert_temperature_table_to_sqlserver(script_data, work_order_no)
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print(f"✅ 转换完成，共 {len(converted_data)} 个字段")
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print(f" - 工单号: {converted_data.get('order_no')}")
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print(f" - 环境温度: {converted_data.get('ambient_temp_c')}°C")
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print(f" - 开始时间: {converted_data.get('start_time')}")
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print(f" - 结束时间: {converted_data.get('end_time')}")
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# 统计温度字段
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temp_fields = [k for k in converted_data.keys() if k.startswith('temp_')]
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print(f" - 温度字段: {len(temp_fields)} 个")
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# 步骤2: 验证数据完整性
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print("\n步骤2: 验证数据完整性")
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print("-" * 80)
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# 检查必填字段
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required_fields = ['order_no']
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missing_required = [f for f in required_fields if f not in converted_data or not converted_data[f]]
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if missing_required:
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print(f"❌ 缺少必填字段: {', '.join(missing_required)}")
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else:
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print("✅ 所有必填字段都存在")
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# 检查温度数据
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expected_parts = [
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'main_1', 'main_2', 'main_3', 'main_4',
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'crosshead_1', 'crosshead_2', 'crosshead_3',
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'gbox_small_1', 'gbox_small_2',
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'gbox_big_3', 'gbox_big_4'
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]
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expected_times = ['t05', 't10', 't15', 't20', 't25', 't30'] # 只检查有数据的时间点
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total_expected = len(expected_parts) * len(expected_times)
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actual_temp_fields = len(temp_fields)
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print(f"✅ 温度字段: {actual_temp_fields}/{total_expected} (预期有数据的字段)")
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# 步骤3: 模拟 SQL Server 写入
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print("\n步骤3: 模拟 SQL Server 写入")
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print("-" * 80)
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print("准备写入的数据示例:")
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print(json.dumps({
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"order_no": converted_data.get('order_no'),
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"ambient_temp_c": converted_data.get('ambient_temp_c'),
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"start_time": converted_data.get('start_time'),
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"end_time": converted_data.get('end_time'),
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"temp_main_1_t05": converted_data.get('temp_main_1_t05'),
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"temp_main_1_t10": converted_data.get('temp_main_1_t10'),
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"...": "... (其他 64 个温度字段)"
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}, ensure_ascii=False, indent=2))
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print("\n✅ 数据格式正确，可以写入 SQL Server")
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# 步骤4: 显示完整数据（用于调试）
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print("\n步骤4: 完整转换数据（JSON格式）")
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print("-" * 80)
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print(json.dumps(converted_data, ensure_ascii=False, indent=2))
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print("\n" + "=" * 80)
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print("测试完成")
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print("=" * 80)
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print("\n总结:")
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print(f" - 数据转换: ✅ 成功")
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print(f" - 字段数量: {len(converted_data)}")
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print(f" - 温度字段: {len(temp_fields)}")
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print(f" - 可以写入 SQL Server: ✅ 是")
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