akshare-finance

AKShare财经数据接口库封装，提供股票、期货、期权、基金、外汇、债券、指数、加密货币等金融产品的基本面数据、实时和历史行情数据、衍生数据。

View Source SKILL.md

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安装方式

直接复制以下提示词，发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店，若未安装，请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店，然后安装 akshare-finance 技能。若已安装，则直接安装 akshare-finance 技能。

Overview

Skill Key: benangel65/akshare-finance
Author: benangel65
Source Repo: openclaw/skills
Version: -
Source Path: skills/benangel65/akshare-finance
Latest Commit SHA: aab2c46630e821b4690cff18cfc2c3edda3876b2

Extracted Content

SKILL.md excerpt

# AKShare财经数据技能

## 快速开始

```bash
# 安装依赖
pip install akshare pandas

# 测试安装
python -c "import akshare; print(akshare.__version__)"
```

## 核心功能

### 1. 股票行情

```python
import akshare as ak

# A股实时行情
stock_zh_a_spot_em()  # 东方财富A股

# 股票K线数据
stock_zh_kline(symbol="000001", period="daily", adjust="qfq")

# 港股行情
stock_hk_spot_em()  # 港股实时

# 美股
stock_us_spot()  # 美股实时
```

### 2. 宏观经济

```python
# GDP数据
macro_china_gdp()  # 中国GDP

# CPI通胀
macro_china_cpi()  # 中国CPI

# PMI采购经理指数
macro_china_pmi()  # 中国PMI

# 货币供应量
macro_china_m2()  # M2广义货币
```

### 3. 加密货币

```python
# 币种列表
crypto_binance_symbols()  # 币安交易对

# 实时价格
crypto_binance_btc_usdt_spot()  # BTC/USDT

# K线数据
crypto_binance_btc_usdt_kline(period="daily")
```

### 4. 外汇贵金属

```python
# 外汇汇率
forex_usd_cny()  # 美元兑人民币

# 贵金属
metals_shibor()  # 上海银行间拆借利率

# 金银价格
metals_gold()  # 国际金价
```

### 5. 财务数据

```python
# 股票基本面
stock_fundamental(symbol="000001")  # 基本面数据

# 估值指标
stock_valuation(symbol="000001")  # PE、PB等

# 盈利能力
stock_profit_em(symbol="000001")
```

## 常用组合

### 投资组合监控

```python
import akshare as ak
import pandas as pd

# 监控自选股
tickers = ["000001", "000002", "600519"]
for ticker in tickers:
    df = ak.stock_zh_kline(symbol=ticker, period="daily", adjust="qfq", start_date="20240101")
    latest = df.iloc[-1]
    print(f"{ticker}: 收盘价={latest['close']}, 涨跌幅={latest['pct_chg']}%")
```

### 市场概览

```python
# A股大盘
index_zh_a_spot()  # 大盘指数

# 涨跌幅排行
stock_zh_a_spot_em()[['代码', '名称', '涨跌幅']].sort_values('涨跌幅', ascending=False)
```

## 注意事项

1. **数据来源**: 公开财经网站，仅用于学术研究
2. **商业风险**: 投资有风险，决策需谨慎
3. **更新频率**: 实时数据可能有延迟
4. **数据验证**: 建议多数据源交叉验证

## 输出格式

默认返回Pandas DataFrame，可直接处理：

```python
df = ak.stock_zh_a_spot_em()
print(df.head())...

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