feat: 添加前端界面和市场分析模块
- 新增 Vue 3 + Vuetify 前端界面 - 新增市场分析模块 (market/) - 更新主服务器和路由 - 更新 MT5 EA 文件 - 添加 .gitignore 排除临时文件
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guaiwoluo2020
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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行情API调用示例
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演示EA端如何推送K线数据到Python服务
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"""
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import requests
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import json
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from datetime import datetime, timedelta
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import random
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# 服务地址
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BASE_URL = "http://localhost:8000"
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def generate_mock_klines(count: int, base_price: float, period_minutes: int) -> list:
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"""
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生成模拟K线数据
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"""
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klines = []
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now = datetime.now()
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for i in range(count):
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# 计算时间戳
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ts = now - timedelta(minutes=period_minutes * (count - i - 1))
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# 生成随机价格波动
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change = random.uniform(-0.01, 0.01) * base_price
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open_price = base_price + change
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high = open_price + random.uniform(0, 0.005) * base_price
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low = open_price - random.uniform(0, 0.005) * base_price
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close = open_price + random.uniform(-0.003, 0.003) * base_price
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klines.append({
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"timestamp": ts.strftime("%Y-%m-%d %H:%M:%S"),
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"open": round(open_price, 2),
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"high": round(high, 2),
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"low": round(low, 2),
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"close": round(close, 2),
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"volume": random.randint(100, 1000)
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})
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# 更新基准价格
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base_price = close
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return klines
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def push_kline_single_period(symbol: str, period: str, klines: list, is_full: bool = False):
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"""
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推送单个周期的K线数据
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"""
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url = f"{BASE_URL}/ea/kline/{period}"
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payload = {
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"symbol": symbol,
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"is_full": is_full,
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"klines": klines
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}
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print(f"\n推送 {symbol} {period} K线数据 ({len(klines)} 条, {'全量' if is_full else '增量'})")
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try:
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response = requests.post(url, json=payload)
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print(f"状态码: {response.status_code}")
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print(f"响应: {response.json()}")
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# 检查是否需要全量数据
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if response.status_code == 400:
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data = response.json()
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if data.get('code') == 8888:
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print(">>> 服务需要全量数据，请重新发送历史数据")
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return 8888
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return response.status_code
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except Exception as e:
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print(f"请求失败: {e}")
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return None
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def push_kline_batch(symbol: str, kline_data: dict, is_full: bool = False):
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"""
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批量推送多个周期的K线数据
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"""
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url = f"{BASE_URL}/ea/kline_batch"
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payload = {
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"symbol": symbol,
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"is_full": is_full,
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"data": kline_data
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}
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print(f"\n批量推送 {symbol} K线数据 ({'全量' if is_full else '增量'})")
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try:
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response = requests.post(url, json=payload)
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print(f"状态码: {response.status_code}")
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print(f"响应: {json.dumps(response.json(), indent=2, ensure_ascii=False)}")
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return response.status_code
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except Exception as e:
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print(f"请求失败: {e}")
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return None
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def get_trades_with_price(symbol: str, price: float):
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"""
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获取交易指令（携带价格，用于转折点检测）
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"""
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url = f"{BASE_URL}/get_trades"
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params = {
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"symbol": symbol,
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"price": price
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}
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try:
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response = requests.get(url, params=params)
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data = response.json()
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print(f"\n获取 {symbol} 交易指令 (价格: {price})")
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print(f"交易指令: {data.get('trades', [])}")
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# 检查转折点提醒
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alerts = data.get('pivot_alerts', [])
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if alerts:
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print(f"\n⚠️ 转折点提醒 ({len(alerts)} 条):")
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for alert in alerts:
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print(f" - {alert['period']} {alert['direction'] == 'high' and '高点' or '低点'}")
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print(f" 转折点价格: {alert['pivot_price']}")
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print(f" 当前价格: {alert['current_price']}")
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print(f" 距离: {alert['distance_pct']}%")
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else:
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print("无转折点提醒")
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return data
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except Exception as e:
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print(f"请求失败: {e}")
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return None
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def get_klines(symbol: str, period: str, count: int = 100):
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"""查询K线数据"""
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url = f"{BASE_URL}/market/kline/{symbol}"
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params = {"period": period, "count": count}
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try:
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response = requests.get(url, params=params)
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data = response.json()
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print(f"\n{symbol} {period} K线数据 ({data['count']} 条):")
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for k in data['data'][-3:]:
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print(f" {k['timestamp']}: O={k['open']} H={k['high']} L={k['low']} C={k['close']}")
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return data
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except Exception as e:
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print(f"请求失败: {e}")
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return None
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def get_pivots(symbol: str):
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"""查询转折点"""
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url = f"{BASE_URL}/market/pivots/{symbol}"
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try:
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response = requests.get(url)
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data = response.json()
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print(f"\n{symbol} 转折点数据:")
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for period, pivots in data.get('data', {}).items():
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if pivots:
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print(f" {period}: {len(pivots)} 个转折点")
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for p in pivots[:3]:
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print(f" - {p['direction'] == 'high' and '高点' or '低点'} @ {p['price']} ({p['timestamp']})")
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return data
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except Exception as e:
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print(f"请求失败: {e}")
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return None
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def main():
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"""
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演示完整的EA启动流程
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"""
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print("=" * 60)
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print("EA 行情数据推送示例")
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print("=" * 60)
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symbol = "GOLD"
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base_price = 2030.0
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# ==================== 1. EA启动时推送全量K线数据 ====================
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print("\n[步骤1] EA启动，推送全量K线数据...")
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# 各周期历史数据条数（根据实际需求）
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history_counts = {
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'H4': 1100, # 6个月约1100根4小时K线
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'H1': 720, # 1个月约720根1小时K线
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'M15': 288, # 3天约288根15分钟K线
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'M5': 288, # 24小时288根5分钟K线
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'M1': 60 # 1小时60根1分钟K线
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}
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kline_data = {}
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period_minutes = {'H4': 240, 'H1': 60, 'M15': 15, 'M5': 5, 'M1': 1}
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for period, count in history_counts.items():
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kline_data[period] = generate_mock_klines(count, base_price, period_minutes[period])
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push_kline_batch(symbol, kline_data, is_full=True)
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# ==================== 2. 查询K线和转折点 ====================
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print("\n[步骤2] 查询K线数据和转折点...")
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get_klines(symbol, 'H4', 10)
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get_pivots(symbol)
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# ==================== 3. 模拟EA轮询获取交易指令 ====================
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print("\n[步骤3] EA轮询获取交易指令（携带当前价格）...")
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# 模拟当前价格
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current_price = base_price + random.uniform(-5, 5)
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get_trades_with_price(symbol, current_price)
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# ==================== 4. 模拟增量数据推送 ====================
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print("\n[步骤4] 推送增量K线数据...")
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# 生成一根新的K线
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for period in ['H4', 'H1', 'M15', 'M5', 'M1']:
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new_klines = generate_mock_klines(1, base_price, period_minutes[period])
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push_kline_single_period(symbol, period, new_klines, is_full=False)
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# ==================== 5. 查看服务状态 ====================
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print("\n[步骤5] 查看服务状态...")
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try:
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response = requests.get(f"{BASE_URL}/market/status")
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data = response.json()
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print(json.dumps(data, indent=2, ensure_ascii=False))
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except Exception as e:
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print(f"请求失败: {e}")
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print("\n" + "=" * 60)
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print("示例完成")
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print("=" * 60)
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if __name__ == "__main__":
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main()
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