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    "name": "Akshare Finance",
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "快速开始",
        "body": "# 安装依赖\npip install akshare pandas\n\n# 测试安装\npython -c \"import akshare; print(akshare.__version__)\""
      },
      {
        "title": "1. 股票行情",
        "body": "import akshare as ak\n\n# A股实时行情\nstock_zh_a_spot_em()  # 东方财富A股\n\n# 股票K线数据\nstock_zh_kline(symbol=\"000001\", period=\"daily\", adjust=\"qfq\")\n\n# 港股行情\nstock_hk_spot_em()  # 港股实时\n\n# 美股\nstock_us_spot()  # 美股实时"
      },
      {
        "title": "2. 宏观经济",
        "body": "# GDP数据\nmacro_china_gdp()  # 中国GDP\n\n# CPI通胀\nmacro_china_cpi()  # 中国CPI\n\n# PMI采购经理指数\nmacro_china_pmi()  # 中国PMI\n\n# 货币供应量\nmacro_china_m2()  # M2广义货币"
      },
      {
        "title": "3. 加密货币",
        "body": "# 币种列表\ncrypto_binance_symbols()  # 币安交易对\n\n# 实时价格\ncrypto_binance_btc_usdt_spot()  # BTC/USDT\n\n# K线数据\ncrypto_binance_btc_usdt_kline(period=\"daily\")"
      },
      {
        "title": "4. 外汇贵金属",
        "body": "# 外汇汇率\nforex_usd_cny()  # 美元兑人民币\n\n# 贵金属\nmetals_shibor()  # 上海银行间拆借利率\n\n# 金银价格\nmetals_gold()  # 国际金价"
      },
      {
        "title": "5. 财务数据",
        "body": "# 股票基本面\nstock_fundamental(symbol=\"000001\")  # 基本面数据\n\n# 估值指标\nstock_valuation(symbol=\"000001\")  # PE、PB等\n\n# 盈利能力\nstock_profit_em(symbol=\"000001\")"
      },
      {
        "title": "投资组合监控",
        "body": "import akshare as ak\nimport pandas as pd\n\n# 监控自选股\ntickers = [\"000001\", \"000002\", \"600519\"]\nfor ticker in tickers:\n    df = ak.stock_zh_kline(symbol=ticker, period=\"daily\", adjust=\"qfq\", start_date=\"20240101\")\n    latest = df.iloc[-1]\n    print(f\"{ticker}: 收盘价={latest['close']}, 涨跌幅={latest['pct_chg']}%\")"
      },
      {
        "title": "市场概览",
        "body": "# A股大盘\nindex_zh_a_spot()  # 大盘指数\n\n# 涨跌幅排行\nstock_zh_a_spot_em()[['代码', '名称', '涨跌幅']].sort_values('涨跌幅', ascending=False)"
      },
      {
        "title": "注意事项",
        "body": "数据来源: 公开财经网站，仅用于学术研究\n商业风险: 投资有风险，决策需谨慎\n更新频率: 实时数据可能有延迟\n数据验证: 建议多数据源交叉验证"
      },
      {
        "title": "输出格式",
        "body": "默认返回Pandas DataFrame，可直接处理：\n\ndf = ak.stock_zh_a_spot_em()\nprint(df.head())  # 查看前5行\nprint(df.columns)  # 查看列名\ndf.to_csv(\"data.csv\")  # 保存CSV"
      },
      {
        "title": "参考文档",
        "body": "AKShare文档: https://akshare.akfamily.xyz/\nGitHub: https://github.com/akfamily/akshare"
      }
    ],
    "body": "AKShare财经数据技能\n快速开始\n# 安装依赖\npip install akshare pandas\n\n# 测试安装\npython -c \"import akshare; print(akshare.__version__)\"\n\n核心功能\n1. 股票行情\nimport akshare as ak\n\n# A股实时行情\nstock_zh_a_spot_em()  # 东方财富A股\n\n# 股票K线数据\nstock_zh_kline(symbol=\"000001\", period=\"daily\", adjust=\"qfq\")\n\n# 港股行情\nstock_hk_spot_em()  # 港股实时\n\n# 美股\nstock_us_spot()  # 美股实时\n\n2. 宏观经济\n# GDP数据\nmacro_china_gdp()  # 中国GDP\n\n# CPI通胀\nmacro_china_cpi()  # 中国CPI\n\n# PMI采购经理指数\nmacro_china_pmi()  # 中国PMI\n\n# 货币供应量\nmacro_china_m2()  # M2广义货币\n\n3. 加密货币\n# 币种列表\ncrypto_binance_symbols()  # 币安交易对\n\n# 实时价格\ncrypto_binance_btc_usdt_spot()  # BTC/USDT\n\n# K线数据\ncrypto_binance_btc_usdt_kline(period=\"daily\")\n\n4. 外汇贵金属\n# 外汇汇率\nforex_usd_cny()  # 美元兑人民币\n\n# 贵金属\nmetals_shibor()  # 上海银行间拆借利率\n\n# 金银价格\nmetals_gold()  # 国际金价\n\n5. 财务数据\n# 股票基本面\nstock_fundamental(symbol=\"000001\")  # 基本面数据\n\n# 估值指标\nstock_valuation(symbol=\"000001\")  # PE、PB等\n\n# 盈利能力\nstock_profit_em(symbol=\"000001\")\n\n常用组合\n投资组合监控\nimport akshare as ak\nimport pandas as pd\n\n# 监控自选股\ntickers = [\"000001\", \"000002\", \"600519\"]\nfor ticker in tickers:\n    df = ak.stock_zh_kline(symbol=ticker, period=\"daily\", adjust=\"qfq\", start_date=\"20240101\")\n    latest = df.iloc[-1]\n    print(f\"{ticker}: 收盘价={latest['close']}, 涨跌幅={latest['pct_chg']}%\")\n\n市场概览\n# A股大盘\nindex_zh_a_spot()  # 大盘指数\n\n# 涨跌幅排行\nstock_zh_a_spot_em()[['代码', '名称', '涨跌幅']].sort_values('涨跌幅', ascending=False)\n\n注意事项\n数据来源: 公开财经网站，仅用于学术研究\n商业风险: 投资有风险，决策需谨慎\n更新频率: 实时数据可能有延迟\n数据验证: 建议多数据源交叉验证\n输出格式\n\n默认返回Pandas DataFrame，可直接处理：\n\ndf = ak.stock_zh_a_spot_em()\nprint(df.head())  # 查看前5行\nprint(df.columns)  # 查看列名\ndf.to_csv(\"data.csv\")  # 保存CSV\n\n参考文档\nAKShare文档: https://akshare.akfamily.xyz/\nGitHub: https://github.com/akfamily/akshare"
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    "provenanceUrl": "https://clawhub.ai/BenAngel65/akshare-finance",
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    "owner": "BenAngel65",
    "version": "1.0.0",
    "license": null,
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