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#!/usr/bin/env python
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"""
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测试版本的AI处理脚本 - 添加超时和错误处理
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"""
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import os
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import sys
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import django
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import time
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from concurrent.futures import ThreadPoolExecutor, TimeoutError
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# 设置Django环境
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sys.path.append('/home/hzk/项目/moxun-1/信息抽取+数据检验/Django123/atc_extractor/backend')
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os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'backend.settings')
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django.setup()
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from extractor.infoextractor_czhwjq import CallSignExtractor, read_from_table, write_to_table, parse_input
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def process_single_record(extractor, data_item, idx):
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"""处理单条记录，带超时控制"""
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try:
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raw_id, raw_text = data_item[0], data_item[1]
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print(f"处理第 {idx+1} 条记录: {raw_id}")
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# 调用AI模型
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result = extractor.extract_call_signs(raw_id, raw_text)
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if not result:
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print(f" ❌ AI返回空结果")
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return []
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# 解析结果
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result_list = parse_input(result)
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print(f" ✅ 解析出 {len(result_list)} 条记录")
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return result_list
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except Exception as e:
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print(f" ❌ 处理失败: {e}")
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return []
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def test_ai_processing():
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"""测试AI处理流程"""
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print("开始测试AI处理流程...")
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# 读取原始数据
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print("1. 读取原始数据...")
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id_data = read_from_table("prewashed_table", "id")
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text_data = read_from_table("prewashed_table", "text")
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data = [[id_data[i], text_data[i]] for i in range(len(id_data))]
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if len(data) == 0:
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print("❌ 没有原始数据")
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return
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print(f"📊 原始数据: {len(data)} 条")
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# 只处理前10条作为测试
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test_data = data[:10]
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print(f"🧪 测试处理前 {len(test_data)} 条")
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# 初始化提取器
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extractor = CallSignExtractor()
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all_result = []
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idx = 0
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print("2. 开始AI处理...")
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start_time = time.time()
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for i, data_item in enumerate(test_data):
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try:
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# 设置单条记录处理超时（30秒）
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with ThreadPoolExecutor(max_workers=1) as executor:
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future = executor.submit(process_single_record, extractor, data_item, i)
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result_list = future.result(timeout=30) # 30秒超时
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# 添加结果
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for row in result_list:
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if row and len(row) >= 5: # 确保数据完整
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idx += 1
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all_result.append([idx] + row)
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except TimeoutError:
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print(f" ⏰ 第 {i+1} 条记录处理超时，跳过")
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continue
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except Exception as e:
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print(f" ❌ 第 {i+1} 条记录处理失败: {e}")
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continue
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end_time = time.time()
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processing_time = end_time - start_time
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print(f"3. 处理完成:")
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print(f" ⏱️ 处理时间: {processing_time:.2f} 秒")
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print(f" 📈 原始记录: {len(test_data)} 条")
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print(f" 📊 提取结果: {len(all_result)} 条")
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print(f" 🎯 提取率: {len(all_result)/len(test_data)*100:.1f}%")
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# 显示前几条结果
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if all_result:
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print(f"4. 提取结果示例:")
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for i, result in enumerate(all_result[:3]):
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print(f" 记录{i+1}: {result}")
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# 写入测试表
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if all_result:
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try:
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headers = ["num", "id", "Call Sign", "Behavior", "Flight Level", "Location", "Time"]
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write_to_table(all_result, headers, "test_precessed_table")
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print(f"✅ 结果已写入 test_precessed_table 表")
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except Exception as e:
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print(f"❌ 写入数据库失败: {e}")
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return {
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"processed_records": len(test_data),
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"extracted_records": len(all_result),
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"extraction_rate": len(all_result)/len(test_data)*100 if test_data else 0,
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"processing_time": processing_time
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}
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if __name__ == "__main__":
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result = test_ai_processing()
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print(f"\n🎉 测试完成: {result}") |
