feat(tests): 添加多个数据获取脚本测试示例
- 新增获取3033.HK复权与不复权价格对比脚本，支持代理配置 - 新增使用Tushare获取AU9999黄金现货数据脚本，支持日期范围查询和CSV保存 - 新增从OKX通过CCXT库获取BTC/USDT日线数据脚本，支持HTTP代理和时间范围过滤 - 所有脚本均包含打印数据显示的格式化输出 - 各脚本提供主函数入口，易于独立运行和调试
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100
tests/fetch_3033.py
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100
tests/fetch_3033.py
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"""
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获取 3033.HK 最新10条数据
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对比复权和不复权价格
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"""
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import yfinance as yf
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import pandas as pd
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from typing import Optional
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import os
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def fetch_3033(period: str = "10d", proxy: Optional[str] = None) -> None:
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"""
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获取 3033.HK 数据，对比复权和不复权价格
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Args:
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period: 获取周期，默认10天
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proxy: 代理地址，如 "socks5://127.0.0.1:1080"
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"""
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# 设置代理
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if proxy:
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os.environ['HTTP_PROXY'] = proxy
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os.environ['HTTPS_PROXY'] = proxy
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print(f"使用代理: {proxy}")
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code = "3033.HK"
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ticker = yf.Ticker(code)
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print(f"\n{'='*80}")
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print(f"获取 {code} 最新数据")
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print(f"{'='*80}\n")
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# 1. 不复权价格 (auto_adjust=False)
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print("【1. 不复权价格】(auto_adjust=False)")
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print("-" * 80)
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data_raw = ticker.history(period=period, auto_adjust=False)
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if not data_raw.empty:
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print(f"{'日期':<12} {'开盘':>10} {'收盘':>10} {'最高':>10} {'最低':>10} {'成交量':>12}")
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print("-" * 80)
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for date, row in data_raw.tail(10).iterrows():
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date_str = date.strftime('%Y-%m-%d')
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print(f"{date_str:<12} {row['Open']:>10.3f} {row['Close']:>10.3f} {row['High']:>10.3f} {row['Low']:>10.3f} {row['Volume']:>12.0f}")
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print(f"\n最新收盘价: {data_raw['Close'].iloc[-1]:.3f}")
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else:
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print("无数据")
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# 2. 前复权价格 (auto_adjust=True，默认)
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print(f"\n{'='*80}")
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print("【2. 前复权价格】(auto_adjust=True，默认)")
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print("-" * 80)
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data_adj = ticker.history(period=period, auto_adjust=True)
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if not data_adj.empty:
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print(f"{'日期':<12} {'开盘':>10} {'收盘':>10} {'最高':>10} {'最低':>10} {'成交量':>12}")
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print("-" * 80)
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for date, row in data_adj.tail(10).iterrows():
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date_str = date.strftime('%Y-%m-%d')
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print(f"{date_str:<12} {row['Open']:>10.3f} {row['Close']:>10.3f} {row['High']:>10.3f} {row['Low']:>10.3f} {row['Volume']:>12.0f}")
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print(f"\n最新收盘价: {data_adj['Close'].iloc[-1]:.3f}")
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else:
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print("无数据")
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# 3. 对比
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if not data_raw.empty and not data_adj.empty:
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print(f"\n{'='*80}")
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print("【3. 价格对比】")
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print("-" * 80)
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latest_raw = data_raw['Close'].iloc[-1]
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latest_adj = data_adj['Close'].iloc[-1]
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print(f"不复权最新价: {latest_raw:.3f}")
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print(f"前复权最新价: {latest_adj:.3f}")
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print(f"差异: {abs(latest_raw - latest_adj):.3f} ({abs(latest_raw - latest_adj)/latest_raw*100:.2f}%)")
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print(f"\n{'='*80}")
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def main():
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"""主函数"""
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# 检查是否需要使用代理
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# 如果 Clash 开启，使用 Clash HTTP 代理
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# 如果 SSH 隧道开启，使用 SOCKS5 代理
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# 使用 Clash HTTP 代理
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proxy = "http://127.0.0.1:7890"
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# 如果 Clash 不可用，尝试 SOCKS5 代理（SSH 隧道）
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# proxy = "socks5://127.0.0.1:1080"
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try:
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fetch_3033(period="10d", proxy=proxy)
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except Exception as e:
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print(f"使用代理 {proxy} 失败: {e}")
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print("\n尝试不使用代理...")
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try:
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fetch_3033(period="10d", proxy=None)
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except Exception as e2:
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print(f"无代理也失败: {e2}")
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if __name__ == "__main__":
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main()
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119
tests/fetch_au9999.py
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119
tests/fetch_au9999.py
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"""
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使用 Tushare 获取 AU9999 黄金数据
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"""
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import os
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import pandas as pd
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import tushare as ts
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from datetime import datetime, timedelta
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from typing import Optional
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from dotenv import load_dotenv
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def get_tushare_token() -> str:
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"""从环境变量获取 Tushare token"""
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load_dotenv()
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token = os.environ.get('TUSHARE_TOKEN')
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if not token:
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raise ValueError("未设置 TUSHARE_TOKEN 环境变量")
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return token
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def fetch_au9999(start_date: str, end_date: str) -> Optional[pd.DataFrame]:
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"""
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获取 AU9999 黄金现货数据（使用上期所黄金主力合约 AU.SHF）
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Args:
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start_date: 开始日期 (YYYY-MM-DD)
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end_date: 结束日期 (YYYY-MM-DD)
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Returns:
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DataFrame with columns: date, open, high, low, close, vol
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"""
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try:
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# 初始化 Tushare
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pro = ts.pro_api(get_tushare_token())
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# 转换日期格式
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start_str = start_date.replace('-', '')
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end_str = end_date.replace('-', '')
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print(f"从 Tushare 获取 AU9999 数据...")
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print(f"时间范围: {start_date} ~ {end_date}")
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# 获取黄金期货主力合约数据
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# ts_code: AU.SHF 表示上海期货交易所黄金主力合约
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df = pro.fut_daily(ts_code='AU.SHF', start_date=start_str, end_date=end_str)
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if df is None or df.empty:
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print("未获取到数据")
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return None
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# 标准化列名
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df = df.rename(columns={
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'trade_date': 'date',
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'open': 'open',
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'high': 'high',
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'low': 'low',
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'close': 'close',
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'vol': 'volume',
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})
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# 转换日期格式
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df['date'] = pd.to_datetime(df['date'])
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df = df.set_index('date')
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df = df.sort_index()
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# 选择需要的列
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df = df[['open', 'high', 'low', 'close', 'volume']]
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print(f"✓ 获取成功: {len(df)} 条数据")
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print(f"时间范围: {df.index[0].strftime('%Y-%m-%d')} ~ {df.index[-1].strftime('%Y-%m-%d')}")
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return df
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except Exception as e:
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print(f"获取数据失败: {e}")
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return None
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def print_au9999_data(df: pd.DataFrame):
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"""打印 AU9999 数据"""
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print("\n" + "="*80)
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print("AU9999 黄金数据 (上期所主力合约 AU.SHF)")
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print("="*80)
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print(f"{'日期':<15} {'开盘价':>12} {'最高价':>12} {'最低价':>12} {'收盘价':>12} {'成交量':>12}")
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print("-"*80)
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for date, row in df.iterrows():
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date_str = date.strftime('%Y-%m-%d')
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print(f"{date_str:<15} {row['open']:>12.2f} {row['high']:>12.2f} {row['low']:>12.2f} {row['close']:>12.2f} {row['volume']:>12.2f}")
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print("="*80)
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def main():
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"""主函数"""
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# 计算最近30天的日期范围
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end_date = datetime.now()
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start_date = end_date - timedelta(days=30)
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start_str = start_date.strftime('%Y-%m-%d')
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end_str = end_date.strftime('%Y-%m-%d')
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# 获取数据
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df = fetch_au9999(start_str, end_str)
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if df is not None:
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print_au9999_data(df)
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# 保存到CSV
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output_file = "au9999_data.csv"
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df.to_csv(output_file)
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print(f"\n数据已保存: {output_file}")
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else:
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print("获取数据失败")
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if __name__ == "__main__":
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main()
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109
tests/fetch_btc_okx.py
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tests/fetch_btc_okx.py
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"""
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从 OKX 获取 BTC 日线数据
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使用 CCXT 库，支持本地 Clash HTTP 代理
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"""
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import ccxt
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import pandas as pd
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from datetime import datetime, timedelta
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from typing import Optional
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import os
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def fetch_btc_okx(days: int = 10, http_proxy: str = "http://127.0.0.1:7890") -> Optional[pd.DataFrame]:
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"""
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从 OKX 获取 BTC/USDT 日线数据
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Args:
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days: 获取最近多少天的数据，默认10天
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http_proxy: HTTP 代理地址，默认使用本地 Clash 代理 http://127.0.0.1:7890
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Returns:
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DataFrame with columns: date, open, high, low, close, volume
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"""
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try:
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# 配置 CCXT
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config = {'enableRateLimit': True}
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# 设置 HTTP 代理
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if http_proxy:
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config['proxies'] = {'http': http_proxy, 'https': http_proxy}
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print(f"使用 HTTP 代理: {http_proxy}")
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# 创建 OKX 交易所实例
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exchange = ccxt.okx(config)
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# 计算时间范围
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end_date = datetime.now()
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start_date = end_date - timedelta(days=days + 5) # 多取几天确保有足够数据
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since = int(start_date.timestamp() * 1000)
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print(f"从 OKX 获取 BTC/USDT 最近{days}天数据...")
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print(f"时间范围: {start_date.strftime('%Y-%m-%d')} ~ {end_date.strftime('%Y-%m-%d')}")
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# 获取日线数据
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ohlcv = exchange.fetch_ohlcv('ETH/USDT', '1d', since, limit=100)
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if not ohlcv:
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print("未获取到数据")
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return None
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# 转换为 DataFrame
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df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
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# 转换时间戳为日期索引（UTC -> 北京时间）
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df['date'] = pd.to_datetime(df['timestamp'], unit='ms', utc=True).dt.tz_convert('Asia/Shanghai')
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df = df.set_index('date')
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df = df[['open', 'high', 'low', 'close', 'volume']]
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# 过滤最近N天
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df = df.tail(days)
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print(f"✓ 获取成功: {len(df)} 条数据")
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print(f"时间范围: {df.index[0].strftime('%Y-%m-%d %H:%M')} ~ {df.index[-1].strftime('%Y-%m-%d %H:%M')}")
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return df
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except Exception as e:
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print(f"获取数据失败: {e}")
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return None
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def print_btc_data(df: pd.DataFrame):
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"""打印 BTC 数据"""
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print("\n" + "="*80)
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print("BTC/USDT 日线数据 (OKX)")
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print("="*80)
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print(f"{'日期':<20} {'开盘价':>12} {'最高价':>12} {'最低价':>12} {'收盘价':>12} {'成交量':>12}")
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print("-"*80)
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for date, row in df.iterrows():
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date_str = date.strftime('%Y-%m-%d %H:%M')
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print(f"{date_str:<20} {row['open']:>12.2f} {row['high']:>12.2f} {row['low']:>12.2f} {row['close']:>12.2f} {row['volume']:>12.4f}")
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print("="*80)
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def main():
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"""主函数"""
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# 使用本地 Clash HTTP 代理（默认端口 7890）
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# 如果 Clash 使用其他端口，请修改此处
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http_proxy = "http://127.0.0.1:7890"
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# 获取数据
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df = fetch_btc_okx(days=10, http_proxy=http_proxy)
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if df is not None:
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print_btc_data(df)
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# 保存到CSV
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output_file = "btc_okx_1d.csv"
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df.to_csv(output_file)
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print(f"\n数据已保存: {output_file}")
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else:
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print("获取数据失败")
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if __name__ == "__main__":
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main()
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