Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
skills.volces.com avatar

Akshare Finance

  • 159 installs
  • skills.volces.com

Use akshare-finance for development tasks

About

akshare-finance: A skill for development. This provides functionality for development workflows.

  • akshare-finance

Akshare Finance by the numbers

  • 159 all-time installs (skills.sh)
  • Ranked #2,395 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/skills.volces.com --skill akshare-finance

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs159
Repositoryskills.volces.com

What it does

Use akshare-finance for development tasks

Files

SKILL.mdMarkdownGitHub ↗

AKShare财经数据技能

快速开始

# 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

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

# 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

# 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

# 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

# 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

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

# 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:

df = ak.stock_zh_a_spot_em()
print(df.head())  # 查看前5行
print(df.columns)  # 查看列名
df.to_csv("data.csv")  # 保存CSV

参考文档

  • AKShare文档: https://akshare.akfamily.xyz/
  • GitHub: https://github.com/akfamily/akshare

Related skills

Backend & APIsbackendintegrations

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.