diff --git a/examples/flask_api_client.py b/examples/flask_api_client.py
new file mode 100644
index 0000000..1dc2ce2
--- /dev/null
+++ b/examples/flask_api_client.py
@@ -0,0 +1,298 @@
+"""
+Flask API 客户端示例
+====================
+演示如何调用 Universal Data Fetcher API
+"""
+
+import requests
+import json
+from typing import Dict, List, Optional
+
+
+class DataFetcherClient:
+    """
+    Universal Data Fetcher API 客户端
+    
+    使用示例:
+        client = DataFetcherClient("http://localhost:5000")
+        
+        # 获取单只标的
+        data = client.get_ohlcv("000300.SH", "2024-01-01", "2024-03-31")
+        
+        # 批量获取
+        results = client.batch_ohlcv(
+            ["000300.SH", "NDX", "HSI"],
+            "2024-01-01",
+            "2024-03-31"
+        )
+    """
+    
+    def __init__(self, base_url: str = "http://localhost:5000"):
+        self.base_url = base_url.rstrip('/')
+    
+    def health_check(self) -> Dict:
+        """健康检查"""
+        response = requests.get(f"{self.base_url}/health")
+        return response.json()
+    
+    def detect_asset_type(self, code: str) -> Dict:
+        """检测资产类型"""
+        response = requests.get(
+            f"{self.base_url}/api/v1/asset-type",
+            params={"code": code}
+        )
+        return response.json()
+    
+    def get_ohlcv(
+        self,
+        code: str,
+        start: Optional[str] = None,
+        end: Optional[str] = None,
+        retry: int = 3
+    ) -> Dict:
+        """
+        获取单只标的的 OHLCV 数据
+        
+        Args:
+            code: 标的代码
+            start: 开始日期 (YYYY-MM-DD)
+            end: 结束日期 (YYYY-MM-DD)
+            retry: 重试次数
+            
+        Returns:
+            {
+                "code": "000300.SH",
+                "asset_type": "china_index",
+                "data": [...],
+                "count": 58,
+                "date_range": {...}
+            }
+        """
+        params = {"code": code, "retry": retry}
+        if start:
+            params["start"] = start
+        if end:
+            params["end"] = end
+        
+        response = requests.get(
+            f"{self.base_url}/api/v1/ohlcv",
+            params=params
+        )
+        return response.json()
+    
+    def batch_ohlcv(
+        self,
+        codes: List[str],
+        start: Optional[str] = None,
+        end: Optional[str] = None,
+        retry: int = 3
+    ) -> Dict:
+        """
+        批量获取多只标的的 OHLCV 数据
+        
+        Args:
+            codes: 标的代码列表
+            start: 开始日期
+            end: 结束日期
+            retry: 重试次数
+            
+        Returns:
+            {
+                "results": {...},
+                "success_count": 2,
+                "failed_count": 1,
+                "total": 3
+            }
+        """
+        payload = {
+            "codes": codes,
+            "retry": retry
+        }
+        if start:
+            payload["start"] = start
+        if end:
+            payload["end"] = end
+        
+        response = requests.post(
+            f"{self.base_url}/api/v1/ohlcv/batch",
+            json=payload
+        )
+        return response.json()
+    
+    def get_supported_codes(self) -> Dict:
+        """获取支持的代码示例"""
+        response = requests.get(f"{self.base_url}/api/v1/supported-codes")
+        return response.json()
+
+
+# ============================================================
+# 使用示例
+# ============================================================
+
+def example_basic():
+    """基础使用示例"""
+    print("\n" + "="*60)
+    print("示例1: 基础使用")
+    print("="*60)
+    
+    client = DataFetcherClient("http://localhost:5000")
+    
+    # 健康检查
+    print("\n1. 健康检查:")
+    health = client.health_check()
+    print(f"   状态: {health.get('status')}")
+    print(f"   SSH配置: {health.get('ssh_configured')}")
+    
+    # 检测资产类型
+    print("\n2. 检测资产类型:")
+    for code in ["000300.SH", "NDX", "BTC", "AAPL"]:
+        result = client.detect_asset_type(code)
+        print(f"   {code:15s} -> {result.get('asset_type'):15s} ({result.get('description')})")
+
+
+def example_single_fetch():
+    """获取单只标的"""
+    print("\n" + "="*60)
+    print("示例2: 获取单只标的")
+    print("="*60)
+    
+    client = DataFetcherClient("http://localhost:5000")
+    
+    # 获取A股指数
+    print("\n1. 沪深300指数 (000300.SH):")
+    result = client.get_ohlcv("000300.SH", "2024-01-01", "2024-03-31")
+    
+    if "error" in result:
+        print(f"   ✗ 错误: {result['error']}")
+    else:
+        print(f"   ✓ 获取成功: {result['count']} 条")
+        print(f"   资产类型: {result['asset_type']}")
+        print(f"   日期范围: {result['date_range']['start']} ~ {result['date_range']['end']}")
+        if result['data']:
+            latest = result['data'][-1]
+            print(f"   最新数据: {latest['date']} 收盘 {latest['close']}")
+
+
+def example_batch_fetch():
+    """批量获取"""
+    print("\n" + "="*60)
+    print("示例3: 批量获取")
+    print("="*60)
+    
+    client = DataFetcherClient("http://localhost:5000")
+    
+    codes = [
+        "000300.SH",   # A股指数
+        "510300.SH",   # A股ETF
+        "NDX",         # 美股指数
+        "HSI",         # 港股指数
+    ]
+    
+    print(f"\n批量获取 {len(codes)} 只标的...")
+    result = client.batch_ohlcv(codes, "2024-01-01", "2024-03-31")
+    
+    print(f"\n结果统计:")
+    print(f"   成功: {result['success_count']}/{result['total']}")
+    print(f"   失败: {result['failed_count']}/{result['total']}")
+    
+    print(f"\n详细结果:")
+    for code, data in result['results'].items():
+        if 'error' in data:
+            print(f"   ✗ {code:15s} 错误: {data['error']}")
+        else:
+            print(f"   ✓ {code:15s} {data['count']:4d} 条 "
+                  f"({data['date_range']['start']} ~ {data['date_range']['end']})")
+
+
+def example_cli():
+    """命令行接口示例"""
+    print("\n" + "="*60)
+    print("示例4: 命令行调用")
+    print("="*60)
+    
+    import subprocess
+    
+    # 使用 curl 调用 API
+    commands = [
+        ("健康检查", "curl -s http://localhost:5000/health | python -m json.tool"),
+        ("检测资产类型", "curl -s 'http://localhost:5000/api/v1/asset-type?code=000300.SH' | python -m json.tool"),
+        ("获取K线数据", "curl -s 'http://localhost:5000/api/v1/ohlcv?code=000300.SH&start=2024-01-01&end=2024-01-31' | python -m json.tool"),
+    ]
+    
+    for name, cmd in commands:
+        print(f"\n{name}:")
+        print(f"   命令: {cmd}")
+        print("   输出:")
+        try:
+            result = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=10)
+            if result.returncode == 0:
+                print(result.stdout[:500] + "..." if len(result.stdout) > 500 else result.stdout)
+            else:
+                print(f"   错误: {result.stderr}")
+        except Exception as e:
+            print(f"   执行失败: {e}")
+
+
+def example_dataframe():
+    """转换为 DataFrame"""
+    print("\n" + "="*60)
+    print("示例5: 转换为 DataFrame")
+    print("="*60)
+    
+    import pandas as pd
+    
+    client = DataFetcherClient("http://localhost:5000")
+    
+    # 获取数据
+    result = client.get_ohlcv("000300.SH", "2024-01-01", "2024-01-31")
+    
+    if "error" not in result and result['data']:
+        # 转换为 DataFrame
+        df = pd.DataFrame(result['data'])
+        df['date'] = pd.to_datetime(df['date'])
+        df = df.set_index('date')
+        
+        print(f"\n转换为 DataFrame:")
+        print(f"   形状: {df.shape}")
+        print(f"   列: {list(df.columns)}")
+        print(f"\n数据预览:")
+        print(df.head())
+        
+        # 计算收益率
+        df['return'] = df['close'].pct_change()
+        print(f"\n收益率统计:")
+        print(df['return'].describe())
+
+
+# ============================================================
+# 运行示例
+# ============================================================
+
+if __name__ == "__main__":
+    print("\n" + "="*60)
+    print("Universal Data Fetcher API 客户端示例")
+    print("="*60)
+    print("\n确保 API 服务器已启动:")
+    print("   python core/datasource/flask_server.py")
+    print("\n")
+    
+    # 运行示例
+    examples = [
+        ("基础使用", example_basic),
+        ("单只标的", example_single_fetch),
+        ("批量获取", example_batch_fetch),
+        ("命令行调用", example_cli),
+        ("DataFrame转换", example_dataframe),
+    ]
+    
+    for name, func in examples:
+        try:
+            func()
+        except Exception as e:
+            print(f"\n示例 '{name}' 失败: {e}")
+            import traceback
+            traceback.print_exc()
+    
+    print("\n" + "="*60)
+    print("示例完成")
+    print("="*60)
diff --git a/examples/universal_fetcher_examples.py b/examples/universal_fetcher_examples.py
new file mode 100644
index 0000000..a8127e8
--- /dev/null
+++ b/examples/universal_fetcher_examples.py
@@ -0,0 +1,299 @@
+"""
+统一数据获取接口使用示例
+========================
+展示如何使用 UniversalDataFetcher 获取各种资产的K线数据
+"""
+
+import sys
+from pathlib import Path
+
+# 添加项目根目录到路径
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from dotenv import load_dotenv
+load_dotenv()
+
+from core.datasource.universal_fetcher import (
+    UniversalDataFetcher,
+    detect_asset_type,
+    fetch_kline
+)
+import pandas as pd
+
+
+# ============================================================
+# 示例1: 快速上手 - 获取单只标的
+# ============================================================
+def example_basic():
+    """基础用法：获取单只标的的K线数据"""
+    print("\n" + "="*60)
+    print("示例1: 基础用法")
+    print("="*60)
+    
+    # 获取A股指数
+    df = fetch_kline("000300.SH", "2024-01-01", "2024-03-31")
+    
+    if df is not None:
+        print(f"\n沪深300指数数据:")
+        print(f"  数据量: {len(df)} 条")
+        print(f"  日期范围: {df.index.min()} ~ {df.index.max()}")
+        print(f"  列: {list(df.columns)}")
+        print(f"\n最新5条数据:")
+        print(df.tail())
+
+
+# ============================================================
+# 示例2: 检测资产类型
+# ============================================================
+def example_detect_type():
+    """自动检测资产类型"""
+    print("\n" + "="*60)
+    print("示例2: 资产类型检测")
+    print("="*60)
+    
+    codes = [
+        "000300.SH",   # A股指数
+        "510300.SH",   # A股ETF
+        "600000.SH",   # A股股票
+        "NDX",         # 美股指数
+        "AAPL",        # 美股股票
+        "HSI",         # 港股指数
+        "AU.SHF",      # 期货
+        "BTC",         # 加密货币
+    ]
+    
+    print("\n资产类型检测结果:")
+    for code in codes:
+        asset_type = detect_asset_type(code)
+        print(f"  {code:15s} -> {asset_type}")
+
+
+# ============================================================
+# 示例3: 批量获取多只标的
+# ============================================================
+def example_batch_fetch():
+    """批量获取多只标的"""
+    print("\n" + "="*60)
+    print("示例3: 批量获取")
+    print("="*60)
+    
+    # 定义要获取的标的列表
+    codes = [
+        "000300.SH",   # 沪深300
+        "399006.SZ",   # 创业板指
+        "510300.SH",   # 沪深300ETF
+        "NDX",         # 纳斯达克100
+        "HSTECH.HK",   # 恒生科技
+    ]
+    
+    # 使用上下文管理器（推荐）
+    fetcher = UniversalDataFetcher()
+    with fetcher:
+        results = fetcher.fetch_multiple(codes, "2024-01-01", "2024-03-31")
+    
+    # 处理结果
+    print("\n获取结果汇总:")
+    for code, df in results.items():
+        if df is not None:
+            print(f"  ✓ {code:15s} {len(df):4d} 条, "
+                  f"收盘价: {df['close'].iloc[-1]:.3f}")
+        else:
+            print(f"  ✗ {code:15s} 无数据")
+
+
+# ============================================================
+# 示例4: 跨市场组合分析
+# ============================================================
+def example_cross_market():
+    """跨市场数据分析示例"""
+    print("\n" + "="*60)
+    print("示例4: 跨市场组合分析")
+    print("="*60)
+    
+    # 定义全球资产组合
+    portfolio = {
+        "000300.SH": "沪深300",
+        "NDX": "纳斯达克100",
+        "HSI": "恒生指数",
+        "N225": "日经225",
+        "GDAXI": "德国DAX",
+    }
+    
+    # 获取数据
+    fetcher = UniversalDataFetcher()
+    with fetcher:
+        results = fetcher.fetch_multiple(
+            list(portfolio.keys()),
+            "2024-01-01",
+            "2024-12-31"
+        )
+    
+    # 合并收盘价
+    close_prices = pd.DataFrame()
+    for code, name in portfolio.items():
+        if results[code] is not None:
+            close_prices[name] = results[code]['close']
+    
+    # 计算收益率
+    if len(close_prices) > 0:
+        returns = close_prices.pct_change().dropna()
+        
+        print("\n各市场收益率统计:")
+        print((returns.mean() * 252 * 100).round(2).to_string())
+        
+        print("\n相关系数矩阵:")
+        print(returns.corr().round(3).to_string())
+
+
+# ============================================================
+# 示例5: 结合技术指标计算
+# ============================================================
+def example_with_indicators():
+    """结合技术指标计算"""
+    print("\n" + "="*60)
+    print("示例5: 技术指标计算")
+    print("="*60)
+    
+    # 获取数据
+    df = fetch_kline("000300.SH", "2024-01-01", "2024-06-30")
+    
+    if df is None:
+        print("数据获取失败")
+        return
+    
+    # 计算移动平均线
+    df['MA5'] = df['close'].rolling(window=5).mean()
+    df['MA20'] = df['close'].rolling(window=20).mean()
+    df['MA60'] = df['close'].rolling(window=60).mean()
+    
+    # 计算RSI
+    delta = df['close'].diff()
+    gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
+    loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
+    rs = gain / loss
+    df['RSI'] = 100 - (100 / (1 + rs))
+    
+    print("\n技术指标计算结果（最新10条）:")
+    print(df[['close', 'MA5', 'MA20', 'MA60', 'RSI']].tail(10).round(2))
+
+
+# ============================================================
+# 示例6: 错误处理与重试
+# ============================================================
+def example_error_handling():
+    """错误处理示例"""
+    print("\n" + "="*60)
+    print("示例6: 错误处理")
+    print("="*60)
+    
+    # 测试无效代码
+    invalid_codes = ["INVALID", "999999.SH", ""]
+    
+    for code in invalid_codes:
+        print(f"\n尝试获取: {code}")
+        df = fetch_kline(code, "2024-01-01", "2024-01-31")
+        if df is None:
+            print(f"  ✓ 正确返回 None")
+        else:
+            print(f"  ✗ 意外获取到数据")
+    
+    # 测试重试机制
+    print("\n测试重试机制（网络错误）:")
+    fetcher = UniversalDataFetcher()
+    df = fetcher.fetch("NDX", "2024-01-01", "2024-01-31", retry=3)
+    if df is not None:
+        print(f"  ✓ 重试成功: {len(df)} 条")
+    else:
+        print(f"  ✗ 重试后仍失败")
+
+
+# ============================================================
+# 示例7: 与现有轮动策略集成
+# ============================================================
+def example_integration_with_rotation():
+    """与现有轮动策略集成示例"""
+    print("\n" + "="*60)
+    print("示例7: 与轮动策略集成")
+    print("="*60)
+    
+    # 模拟轮动策略的代码配置
+    code_config = {
+        "399006.SZ": {"name": "创业板指", "etf": "159915.SZ", "market": "A"},
+        "NDX": {"name": "纳指100", "etf": "513100.SH", "market": "US"},
+        "HSI": {"name": "恒生指数", "etf": "159920.SZ", "market": "HK"},
+    }
+    
+    # 使用 UniversalDataFetcher 获取数据
+    all_codes = list(code_config.keys())
+    etf_codes = [cfg['etf'] for cfg in code_config.values() if cfg.get('etf')]
+    
+    fetcher = UniversalDataFetcher()
+    with fetcher:
+        # 获取指数数据（用于因子计算）
+        index_data = fetcher.fetch_multiple(
+            all_codes, "2024-01-01", "2024-03-31"
+        )
+        
+        # 获取ETF数据（用于收益计算）
+        etf_data = fetcher.fetch_multiple(
+            etf_codes, "2024-01-01", "2024-03-31"
+        )
+    
+    # 验证数据完整性
+    print("\n数据完整性检查:")
+    for code in all_codes:
+        idx_df = index_data.get(code)
+        etf_code = code_config[code].get('etf')
+        etf_df = etf_data.get(etf_code) if etf_code else None
+        
+        print(f"  {code}:")
+        print(f"    指数数据: {'✓' if idx_df is not None else '✗'} "
+              f"({len(idx_df) if idx_df is not None else 0} 条)")
+        if etf_code:
+            print(f"    ETF数据 ({etf_code}): {'✓' if etf_df is not None else '✗'} "
+                  f"({len(etf_df) if etf_df is not None else 0} 条)")
+
+
+# ============================================================
+# 运行所有示例
+# ============================================================
+if __name__ == "__main__":
+    print("\n" + "="*60)
+    print("统一数据获取接口 - 使用示例")
+    print("="*60)
+    
+    # 选择要运行的示例
+    examples = [
+        ("基础用法", example_basic),
+        ("资产类型检测", example_detect_type),
+        ("批量获取", example_batch_fetch),
+        ("跨市场组合分析", example_cross_market),
+        ("技术指标计算", example_with_indicators),
+        ("错误处理", example_error_handling),
+        ("与轮动策略集成", example_integration_with_rotation),
+    ]
+    
+    print("\n可用示例:")
+    for i, (name, _) in enumerate(examples, 1):
+        print(f"  {i}. {name}")
+    
+    # 运行特定示例或全部
+    run_all = True  # 改为 False 可以选择性运行
+    
+    if run_all:
+        for name, func in examples:
+            try:
+                func()
+            except Exception as e:
+                print(f"\n示例 '{name}' 运行失败: {e}")
+                import traceback
+                traceback.print_exc()
+    else:
+        # 运行单个示例
+        example_index = 0  # 修改为 1-7 运行特定示例
+        if 0 <= example_index < len(examples):
+            examples[example_index][1]()
+    
+    print("\n" + "="*60)
+    print("示例运行完成")
+    print("="*60)