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234 lines
9.7 KiB
234 lines
9.7 KiB
#!/usr/bin/env python3
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"""
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前端集成示例
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演示前端如何调用API接口展示中间处理过程
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"""
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import requests
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import json
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from datetime import datetime
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API_BASE = "http://127.0.0.1:8080/api"
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class FrontendIntegrationExample:
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"""模拟前端调用后端API的示例"""
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def __init__(self):
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self.processing_steps = [
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{
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'name': '原始数据',
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'api': 'original-data',
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'description': '文件上传后的原始ATC对话',
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'icon': '📤'
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},
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{
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'name': '数据预处理',
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'api': 'preprocessed-data',
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'description': '清理格式、去除多余空格',
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'icon': '🧹'
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},
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{
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'name': '格式合并',
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'api': 'merged-data',
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'description': '统一航空术语格式',
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'icon': '📋'
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},
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{
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'name': '单词纠错',
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'api': 'corrected-data',
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'description': '修正拼写、语音字母转换',
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'icon': '✏️'
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},
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{
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'name': 'AI信息提取',
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'api': 'processed-data',
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'description': 'AI提取结构化飞行信息',
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'icon': '🤖'
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},
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{
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'name': '最终验证',
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'api': 'final-data',
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'description': '验证通过的有效数据',
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'icon': '✅'
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}
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]
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def simulate_step_by_step_processing(self):
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"""模拟前端分步处理模式"""
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print("🎯 前端集成示例 - 分步处理模式")
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print("="*70)
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print("📝 模拟前端界面展示中间处理过程的数据")
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print()
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# 模拟处理步骤
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processing_apis = [
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('preprocess', '数据预处理'),
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('merge', '格式合并'),
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('correct', '单词纠错'),
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('analyze', 'AI分析')
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]
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print("🔄 执行处理步骤:")
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for api, name in processing_apis:
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print(f" 🔧 执行{name}...")
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try:
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response = requests.post(f"{API_BASE}/{api}/", json={}, timeout=30)
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if response.status_code == 200:
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result = response.json()
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print(f" ✅ {name}完成: {result['message']}")
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else:
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print(f" ❌ {name}失败: {response.status_code}")
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except Exception as e:
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print(f" ❌ {name}异常: {e}")
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print()
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# 模拟前端展示各步骤数据
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print("📊 前端界面展示 - 中间处理过程数据:")
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print("="*70)
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for i, step in enumerate(self.processing_steps, 1):
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print(f"\\n{step['icon']} 步骤{i}: {step['name']}")
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print(f" 📝 {step['description']}")
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try:
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response = requests.get(f"{API_BASE}/{step['api']}/", timeout=10)
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if response.status_code == 200:
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data = response.json()
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count = data['count']
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records = data.get('data', [])
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print(f" 📊 数据量: {count} 条记录")
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# 显示数据样例（模拟前端表格展示）
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if records and len(records) > 0:
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print(f" 📋 数据样例:")
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# 根据不同步骤显示不同的关键字段
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if step['api'] == 'original-data':
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for j, record in enumerate(records[:2], 1):
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print(f" {j}. ID: {record.get('id', 'N/A')} | 原文: {record.get('text', 'N/A')[:50]}...")
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elif step['api'] == 'preprocessed-data':
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for j, record in enumerate(records[:2], 1):
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print(f" {j}. ID: {record.get('id', 'N/A')} | 清理操作: {record.get('cleaning_operations', 'N/A')}")
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elif step['api'] == 'merged-data':
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for j, record in enumerate(records[:2], 1):
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print(f" {j}. ID: {record.get('id', 'N/A')} | 格式操作: {record.get('format_operations', 'N/A')}")
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elif step['api'] == 'corrected-data':
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for j, record in enumerate(records[:2], 1):
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corrections = record.get('corrections_made', 'N/A')
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count_corr = record.get('correction_count', 0)
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print(f" {j}. ID: {record.get('id', 'N/A')} | 纠错: {corrections} ({count_corr}处)")
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elif step['api'] == 'processed-data':
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for j, record in enumerate(records[:2], 1):
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call_sign = record.get('call_sign', 'N/A')
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behavior = record.get('behavior', 'N/A')
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print(f" {j}. ID: {record.get('id', 'N/A')} | 呼号: {call_sign} | 行为: {behavior}")
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elif step['api'] == 'final-data':
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for j, record in enumerate(records[:2], 1):
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call_sign = record.get('Call Sign', 'N/A')
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behavior = record.get('Behavior', 'N/A')
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print(f" {j}. ID: {record.get('id', 'N/A')} | 呼号: {call_sign} | 行为: {behavior}")
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else:
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print(f" 📋 暂无数据")
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else:
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print(f" ❌ 数据获取失败: {response.status_code}")
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except Exception as e:
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print(f" ❌ 数据获取异常: {e}")
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# 显示统计信息
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print(f"\\n📈 处理统计信息:")
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print("="*30)
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try:
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response = requests.get(f"{API_BASE}/statistics/", timeout=10)
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if response.status_code == 200:
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data = response.json()
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stats = data['statistics']
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print(f" 📊 数据流向: {stats.get('original_count', 0)} → {stats.get('extracted_count', 0)} → {stats.get('valid_count', 0)}")
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print(f" 🎯 提取效率: {stats.get('extraction_rate', 0)}%")
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print(f" ✅ 验证通过率: {stats.get('validation_rate', 0)}%")
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print(f" ❌ 错误率: {stats.get('error_rate', 0)}%")
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except Exception as e:
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print(f" ❌ 统计信息获取失败: {e}")
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def generate_frontend_api_guide(self):
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"""生成前端API调用指南"""
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print(f"\\n📚 前端API调用指南")
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print("="*50)
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print(f"\\n🔄 分步处理模式 (推荐用于前端展示):")
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print(f"```javascript")
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print(f"// 1. 文件上传")
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print(f"const uploadResponse = await fetch('/api/upload/', {{")
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print(f" method: 'POST',")
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print(f" body: formData")
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print(f"}});")
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print(f"")
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print(f"// 2. 执行处理步骤并展示结果")
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print(f"const steps = ['preprocess', 'merge', 'correct', 'analyze'];")
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print(f"for (const step of steps) {{")
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print(f" // 执行处理")
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print(f" await fetch(`/api/${{step}}/`, {{ method: 'POST' }});")
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print(f" ")
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print(f" // 获取结果数据")
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print(f" const dataEndpoint = getDataEndpoint(step);")
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print(f" const result = await fetch(`/api/${{dataEndpoint}}/`);")
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print(f" const data = await result.json();")
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print(f" ")
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print(f" // 更新界面显示")
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print(f" updateUI(step, data);")
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print(f"}}")
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print(f"```")
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print(f"\\n📊 数据获取API映射:")
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for i, step in enumerate(self.processing_steps, 1):
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print(f" {i}. {step['name']}: GET /api/{step['api']}/")
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print(f"\\n🎯 前端界面建议:")
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print(f" 1. 设计进度条显示处理步骤")
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print(f" 2. 每个步骤完成后展示数据表格")
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print(f" 3. 支持切换查看不同步骤的数据")
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print(f" 4. 显示数据转换的统计信息")
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print(f" 5. 提供数据导出功能")
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print(f"\\n⚡ 性能优化建议:")
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print(f" 1. 使用分页加载大量数据")
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print(f" 2. 缓存中间步骤的结果")
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print(f" 3. 支持异步处理模式")
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print(f" 4. 添加处理进度指示器")
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def run_example(self):
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"""运行完整示例"""
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print(f"🚀 前端集成示例演示")
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print(f"📅 时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
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print()
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# 执行分步处理演示
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self.simulate_step_by_step_processing()
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# 生成API调用指南
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self.generate_frontend_api_guide()
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print(f"\\n🎉 前端集成示例演示完成！")
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print(f"💡 现在前端可以完整展示数据处理的中间过程")
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def main():
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"""主函数"""
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example = FrontendIntegrationExample()
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example.run_example()
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return 0
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if __name__ == "__main__":
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exit(main()) |