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ashare-data-lite

轻量、免费的 Python 行情工具,提供沪深股票、ETF、指数、基金净值及海外市场数据。Python 3.10+,运行代码使用标准库,采用 MIT 许可证。

安装与使用

从 PyPI 安装:

pip install ashare-data-lite
from ashare_data import get_etf_quote, get_etf_history, get_fund_nav_history

quote = get_etf_quote("159941")
print(quote.name, quote.last, quote.iopv)

bars = get_etf_history("159941", "2026-09-01", "2026-10-23")
print(bars[-1].timestamp, bars[-1].close, bars[-1].volume)

nav = get_fund_nav_history("159941", "2026-09-01", "2026-10-23")
print(nav[-1].date, nav[-1].nav)

ETF 指交易所交易基金,IOPV 指基金份额参考净值。查询结果采用 dataclass,支持属性访问和 to_dict()。股票数量以股计,ETF 数量以份计;百分率 2.5 表示 2.5%。

支持的数据

数据 入口
股票、ETF、指数实时行情及五档买卖报价 get_stock_quote、get_etf_quote、get_index_quote,批量方法以 _quotes 结尾
日线与 5 / 15 / 30 分钟 K 线 get_stock_history、get_etf_history、get_index_history
基金历史单位净值 get_fund_nav_history
ETF 目录、上交所 ETF 份额 get_etf_catalog、get_sse_etf_shares
FRED 经济序列及 VIX get_fred_series、get_vix_history
Twelve Data 海外 K 线 get_twelve_bars、get_twelve_daily_history

沪深行情、基金净值、目录和份额可直接查询。FRED 和 Twelve Data 使用服务商账户密钥,支持环境变量 FRED_API_KEY、TWELVE_DATA_API_KEY。

自动降级

日线默认原始价格,依次尝试腾讯、新浪;基金单位净值依次尝试东方财富移动端、网页。使用默认配置即可查询,也可设置来源优先级:

bars = get_etf_history(
    "159941", "2026-10-01", "2026-10-23",
    sources=["sina", "tencent"],
)

降级过程保持周期与复权方式一致。分钟线由新浪提供;前复权、后复权日线由腾讯提供。来源的覆盖日期与账户权限决定实际可用数据范围。

批量、序列化与异步

import json
from ashare_data import get_etf_quotes

quotes = get_etf_quotes(["159941", "513100"])
for quote in quotes:
    print(quote.symbol, quote.last, quote.error)

print(json.dumps(quotes[0].to_dict(), ensure_ascii=False))
import asyncio
from ashare_data import AsyncMarketClient

async def main():
    client = AsyncMarketClient(timeout=10)
    quotes = await client.get_etf_quotes(["159941", "513100"])
    print(quotes[0].last)

asyncio.run(main())

同步客户端 MarketClient 与异步客户端 AsyncMarketClient 提供相同的方法和返回类型。完整参数、返回字段、单位及异常见 API 文档。

数据来源与使用范围

实时行情来自腾讯;历史 K 线来自腾讯、新浪;基金净值来自东方财富;基金份额来自上交所;经济序列与海外行情来自 FRED、Twelve Data。数据源的覆盖范围、延迟、接口格式及访问额度可能变化,使用方应做好超时处理并校验关键数据。账户接口遵循对应服务商的套餐和调用限制。

本项目的 MIT 许可证适用于程序代码。行情数据的使用、存储和再分发遵循各来源的使用条款;交易分析需要结合其他信息校验,并自行承担决策风险。

开发

python -m pip install -e ".[dev]"
python -m unittest discover -s tests -v

使用案例位于 examples/。在线样本检查运行 python examples/smoke_check.py,记录保存在 docs/live-check.json。GitHub Actions 在 Python 3.10~3.13 执行自动测试。

发布新版本

在 main 分支审阅并提交功能改动后执行:

python scripts/release.py 0.1.1

脚本检查 PyPI 与 Git 标签、更新版本、构建并安装测试,然后推送提交与 v0.1.1 标签。GitHub Actions 使用 pypi Environment 和 OIDC(开放身份连接)可信发布到 PyPI。工作流运行记录见 Publish to PyPI。

仅执行发布前验证:python scripts/release.py 0.1.1 --check-only。项目内的发布指导位于 .agents/skills/publish-pypi/SKILL.md。

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