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https://github.com/succ985/openclaw-akshare-skill.git
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OpenClaw
318 lines
8.5 KiB
Python
Executable File
318 lines
8.5 KiB
Python
Executable File
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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AkShare Tool 使用示例
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演示如何使用 akshare_tool.py 中的功能
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"""
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from akshare_tool import AkShareTool
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import pandas as pd
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def example_stock_realtime():
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"""示例1: 获取A股实时行情"""
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print("\n" + "="*80)
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print("示例1: 获取A股实时行情")
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print("="*80)
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tool = AkShareTool()
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# 获取单只股票实时行情
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df = tool.get_stock_realtime(symbol="000001", use_cache=False)
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print(f"\n平安银行(000001)实时行情:")
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print(df)
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# 获取银行业股票
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df_banks = tool.get_stock_realtime(filter_field="行业", filter_value="银行", use_cache=False)
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print(f"\n银行板块股票数量: {len(df_banks)}")
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print(df_banks.head(10))
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def example_stock_history():
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"""示例2: 获取股票历史数据"""
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print("\n" + "="*80)
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print("示例2: 获取股票历史数据")
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print("="*80)
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tool = AkShareTool()
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# 获取平安银行日线数据
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df = tool.get_stock_history(
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symbol="000001",
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period="daily",
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start_date="20240101",
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end_date="20241231",
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adjust="qfq",
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use_cache=True
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)
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print(f"\n平安银行历史数据 (最近10天):")
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print(df.tail(10))
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# 计算技术指标
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df['MA5'] = df['收盘'].rolling(window=5).mean()
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df['MA20'] = df['收盘'].rolling(window=20).mean()
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print(f"\n包含移动平均线的数据 (最近5天):")
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print(df[['日期', '收盘', 'MA5', 'MA20']].tail(5))
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def example_hk_stock():
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"""示例3: 获取港股数据"""
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print("\n" + "="*80)
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print("示例3: 获取港股数据")
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print("="*80)
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tool = AkShareTool()
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# 获取腾讯控股实时行情
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df = tool.get_hk_stock_realtime(use_cache=False)
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print(f"\n港股实时行情数量: {len(df)}")
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print(df.head(10))
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# 获取腾讯控股历史数据
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df_history = tool.get_hk_stock_history(
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symbol="00700",
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period="daily",
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start_date="20240101",
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end_date="20241231",
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use_cache=True
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)
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print(f"\n腾讯控股历史数据 (最近5天):")
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print(df_history.tail(5))
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def example_futures():
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"""示例4: 获取期货数据"""
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print("\n" + "="*80)
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print("示例4: 获取期货数据")
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print("="*80)
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tool = AkShareTool()
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# 获取期货实时行情
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df = tool.get_futures_realtime(use_cache=False)
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print(f"\n期货实时行情数量: {len(df)}")
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print(df.head(10))
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# 获取沪深300期货历史数据
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df_history = tool.get_futures_history(
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symbol="IF0",
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start_date="20240101",
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end_date="202401231",
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use_cache=True
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)
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if not df_history.empty:
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print(f"\n沪深300期货历史数据 (最近5天):")
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print(df_history.tail(5))
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def example_fund():
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"""示例5: 获取基金数据"""
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print("\n" + "="*80)
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print("示例5: 获取基金数据")
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print("="*80)
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tool = AkShareTool()
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# 获取基金列表
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df = tool.get_fund_list(use_cache=True)
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print(f"\n基金总数: {len(df)}")
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print(df.head(10))
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# 获取特定基金的历史净值
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df_history = tool.get_fund_history(
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fund_code="000001",
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indicator="单位净值走势",
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use_cache=True
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)
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if not df_history.empty:
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print(f"\n华夏成长基金历史净值 (最近10天):")
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print(df_history.tail(10))
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def example_macro():
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"""示例6: 获取宏观经济数据"""
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print("\n" + "="*80)
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print("示例6: 获取宏观经济数据")
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print("="*80)
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tool = AkShareTool()
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# 获取GDP数据
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df_gdp = tool.get_macro_gdp(use_cache=True)
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print(f"\nGDP数据:")
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print(df_gdp)
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# 获取CPI数据
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df_cpi = tool.get_macro_cpi(use_cache=True)
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print(f"\nCPI数据 (最近10期):")
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print(df_cpi.tail(10))
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# 获取PMI数据
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df_pmi = tool.get_macro_pmi(use_cache=True)
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print(f"\nPMI数据 (最近10期):")
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print(df_pmi.tail(10))
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def example_index():
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"""示例7: 获取指数数据"""
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print("\n" + "="*80)
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print("示例7: 获取指数数据")
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print("="*80)
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tool = AkShareTool()
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# 获取指数实时行情
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df = tool.get_index_realtime(index_type="all", use_cache=False)
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print(f"\n指数实时行情:")
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print(df)
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# 获取上证指数历史数据
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df_history = tool.get_index_history(
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symbol="000001",
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period="daily",
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start_date="20240101",
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end_date="20241231",
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use_cache=True
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)
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print(f"\n上证指数历史数据 (最近10天):")
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print(df_history.tail(10))
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def example_cache():
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"""示例8: 缓存管理"""
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print("\n" + "="*80)
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print("示例8: 缓存管理")
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print("="*80)
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tool = AkShareTool(use_cache=True, cache_expiry_hours=24)
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# 第一次请求（从网络获取）
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print("\n第一次请求（从网络获取）:")
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df1 = tool.get_stock_realtime(symbol="000001", use_cache=True)
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# 第二次请求（从缓存获取）
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print("\n第二次请求（从缓存获取）:")
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df2 = tool.get_stock_realtime(symbol="000001", use_cache=True)
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# 清除缓存
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print("\n清除缓存:")
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count = tool.clear_cache()
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print(f"已清除 {count} 个缓存文件")
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# 再次请求（从网络获取）
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print("\n清除后再次请求:")
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df3 = tool.get_stock_realtime(symbol="000001", use_cache=True)
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def example_error_handling():
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"""示例9: 错误处理"""
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print("\n" + "="*80)
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print("示例9: 错误处理")
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print("="*80)
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tool = AkShareTool()
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try:
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# 尝试获取不存在的股票
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df = tool.get_stock_realtime(symbol="999999")
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if df.empty:
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print("股票代码不存在，返回空数据")
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except Exception as e:
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print(f"发生错误: {e}")
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def example_data_analysis():
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"""示例10: 数据分析"""
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print("\n" + "="*80)
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print("示例10: 数据分析")
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print("="*80)
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tool = AkShareTool()
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# 获取股票历史数据
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df = tool.get_stock_history(
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symbol="000001",
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period="daily",
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start_date="20240101",
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end_date="20241231",
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adjust="qfq"
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)
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if df.empty:
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print("没有数据")
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return
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# 计算收益率
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df['涨跌幅'] = df['收盘'].pct_change() * 100
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# 计算移动平均线
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df['MA5'] = df['收盘'].rolling(window=5).mean()
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df['MA10'] = df['收盘'].rolling(window=10).mean()
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df['MA20'] = df['收盘'].rolling(window=20).mean()
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# 计算波动率
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df['波动率'] = df['涨跌幅'].rolling(window=20).std()
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# 统计信息
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print("\n统计信息:")
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print(f"交易天数: {len(df)}")
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print(f"平均涨跌幅: {df['涨跌幅'].mean():.2f}%")
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print(f"最大涨幅: {df['涨跌幅'].max():.2f}%")
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print(f"最大跌幅: {df['涨跌幅'].min():.2f}%")
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print(f"平均波动率: {df['波动率'].mean():.2f}%")
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print("\n最近10天数据:")
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print(df[['日期', '收盘', '涨跌幅', 'MA5', 'MA10', 'MA20', '波动率']].tail(10))
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def main():
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"""运行所有示例"""
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print("\n" + "="*80)
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print("AkShare Tool 使用示例")
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print("="*80)
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examples = [
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("A股实时行情", example_stock_realtime),
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("股票历史数据", example_stock_history),
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("港股数据", example_hk_stock),
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("期货数据", example_futures),
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("基金数据", example_fund),
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("宏观经济数据", example_macro),
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("指数数据", example_index),
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("缓存管理", example_cache),
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("错误处理", example_error_handling),
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("数据分析", example_data_analysis),
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]
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print("\n可用示例:")
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for i, (name, _) in enumerate(examples, 1):
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print(f" {i}. {name}")
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print("\n运行所有示例可能需要较长时间，请耐心等待...")
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input("\n按Enter键开始运行所有示例，或Ctrl+C取消...")
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try:
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for name, func in examples:
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try:
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func()
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except Exception as e:
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print(f"\n示例 '{name}' 运行出错: {e}")
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import traceback
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traceback.print_exc()
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print("\n" + "="*80)
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print("所有示例运行完成！")
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print("="*80)
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except KeyboardInterrupt:
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print("\n\n用户中断执行")
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except Exception as e:
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print(f"\n发生错误: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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main() |