Axiolune Python SDK
用领域函数读取股票、基金、指数、债券、期货、期权、外汇与宏观数据,返回可以直接组合研究的 pandas 表格。常规数据读取不需要初始化数据目录或创建客户端。
中文使用手册 · English documentation · 完整 API 与参数
第一次读取
import axiolune as ax
matches = ax.stock.search(query="茅台", market="CN")
print(matches)
prices = ax.stock.history(
symbols="600519.SH",
start="2026-09-01",
end="2026-09-30",
adjustment="none",
)
print(prices[["symbol", "date", "close", "currency"]].head())
symbols 使用带市场后缀的代码;start、end 是包含边界的日期。adjustment="none" 表示不复权。调用会访问真实数据来源;返回值和空表取决于来源及所选范围。每列含义、单位、可选值与默认值见 stock.history。
不知道填什么时
print(ax.search("净值"))
print(ax.help("fund.history", language="zh"))
contract = ax.describe("stock.history")
print(contract["parameters"])
print(contract["output"])
发现与帮助操作不取网络数据。每个操作有独立参数页,列出必填项、格式、默认值、枚举、参数依赖、输出字段与实际留存结果。证券和指标示例不代表动态全集;先查相应目录再选值。
从表格组合研究
安装研究功能 pip install "axiolune[research]" 后,复用上一步的价格表:
close = ax.research.prices(prices, field="close")
average = ax.research.sma(close, window=5)
returns = ax.research.returns(close, periods=1)
print(average.tail())
print(returns.tail())
矩阵以日期为行、证券为列;收益率为小数比例,缺失值保持缺失。继续使用 完整组合教程、指标、模型、回测、组合风险和报告手册。研究结果取决于实际输入与明确的交易、费用和时间假设。
安装与功能选择
当前产品版本 / Product version: 0.6.0 · 待发布到 PyPI / Awaiting PyPI publication。
以下为发布后的标准索引安装方式,公共索引目前尚不能取得本版本。 These are the standard commands after publication; this version is not yet available from the public index.
pip install axiolune
uv pip install axiolune
uv add axiolune
基础安装包含常规取数、Arrow/pandas 与 Excel;Python >=3.12,<3.14。不同安装器择一使用,pip/uv pip 面向环境,uv add 面向项目。首次解析选择所用索引与 Python/平台/依赖约束允许的最新正常版本;已有环境和 uv.lock 不会自动追新。
Core installation includes routine data retrieval, Arrow/pandas and Excel. Choose one workflow: pip/uv pip manages an environment; uv add manages a project. Initial resolution chooses the latest normal release permitted by the index and environment constraints, without automatically upgrading existing environments or lockfiles.
按需组合 / Combine capabilities
pip install "axiolune[local]"
uv pip install "axiolune[research,plot,team]"
uv add "axiolune[documents,ocr]"
可同时选择多个 extras;其下层依赖自动包含。data 和 team 的依赖已含基础安装,保留兼容别名;all 仅用于需要全部可选依赖的环境。 Select multiple extras; their dependencies are included automatically. data and team retain compatibility aliases with dependencies already in the core. Choose all only when every optional dependency is needed.
| 能力 | 用途 | 自动包含的能力 |
|---|---|---|
data |
常规取数、Arrow/pandas 和 Excel;当前已包含在基础安装,保留此兼容选项。 | — |
source-crypto |
需要加密能力的数据来源适配。 | data |
local |
本地快照、DuckDB SQL 与 Polars 表格计算。 | data |
research |
指标、筛选、回测、风险和组合研究。 | local, financial |
plot |
交互图表与可导出的 HTML 报告。 | data |
team |
连接现有团队服务的远程客户端;依赖已含基础安装,保留此兼容选项。 | — |
sql |
连接外部 SQL 数据库与读取查询结果。 | data |
server |
团队 HTTP 服务、PostgreSQL 接入与工作进程;数据库服务另行配置。 | local, financial |
ingest |
数据连接器与财务导入适配。 | financial |
ml |
基于 scikit-learn 的常规模型研究。 | research |
ml-advanced |
CatBoost、LightGBM、XGBoost 树模型后端。 | ml |
ta |
独立进程中的 TA-Lib 指标计算。 | research |
semantic |
语义映射、RDF 与 SHACL 校验。 | financial |
documents |
PDF 文本解析与文档证据。 | — |
ocr |
PDF 渲染与 OCR;模型权重不随安装命令下载。 | documents |
stream |
WebSocket 流式数据来源。 | data |
financial |
财报合同、财务计算与公司研究。 | data |
all |
安装所有可选依赖;适合确实使用全部能力的环境。 | data, source-crypto, local, research, plot, team, sql, server, ingest, ml, ml-advanced, ta, semantic, documents, ocr, stream, financial |
升级 / Upgrade
pip install -U axiolune
uv pip install --upgrade axiolune
升级时保留所需 extras,例如 pip install -U "axiolune[research,plot]"。普通重复 install 不等于升级。uv 项目更新锁文件后再同步:
Retain required extras during upgrades. An ordinary repeated install is not an upgrade request. For uv projects:
uv lock --upgrade-package axiolune
uv sync
uv.lock 保留已解析版本;升级仍遵守 pyproject.toml 的版本范围。 uv.lock retains resolved versions; upgrades remain subject to pyproject.toml constraints.
使用独立虚拟环境。Windows 用 py -3.13 -m venv .venv,Linux/macOS 用 python3.13 -m venv .venv;或统一使用 uv venv --python 3.13。不激活时用 .venv/Scripts/python -m pip(Windows)、.venv/bin/python -m pip(Linux/macOS),或 uv pip install --python .venv axiolune。uv 项目同时声明完整 Python 范围:uv init --python ">=3.12,<3.14" my-research 后 uv add axiolune。
Use an isolated environment and its own interpreter. Python 3.12 is also supported. uv projects manage their environment automatically.
可选系统依赖:Linux OCR 需要 OpenGL/GLib(Debian/Ubuntu:libgl1 libglib2.0-0);macOS 的 ml-advanced/all 需要 brew install libomp。server 不自动部署 PostgreSQL;OCR 模型权重另行准备。Windows x64、Linux x86_64/glibc ≥ 2.28、macOS Intel ≥ 13 / Apple Silicon ≥ 14 是完整依赖目标;实际平台执行记录须分别查看,历史 a34 结果仍属于 a34。
Optional system libraries: OpenGL/GLib for Linux OCR and libomp for macOS advanced tree models. server does not provision PostgreSQL; OCR weights are separate. Historical a34 execution records remain a34 evidence.
依赖与版本唯一来源为 SDK pyproject.toml 和根 VERSION;安装/升级命令不固定版本号。需要精确复现时才显式使用 ==。
The SDK pyproject.toml and root VERSION are authoritative. Version pins are reserved for explicit reproduction.
本地输入与持久研究
需要导入文件、快照、本地 SQL 或研究声明时使用 Client;一般数据读取仍直接使用领域函数。
import axiolune as ax
with ax.Client(data_root="./research-data") as client:
result = client.inputs.import_file("prices.csv")
print(result.to_pandas().head())
prices.csv 是调用者已有的本地文件。快照与 SQL 使用 axiolune[local]。offline=True 禁止新网络采集;默认允许读取。客户端的全部参数、预算与生命周期见 本地客户端。团队通过 ax.team.connect(endpoint, credential) 接入已有服务。
原始来源与升级
发布者特有字段使用 ax.source.search/describe/fetch/frame。先读来源合同,再传来源参数;普通行情优先使用股票、基金等领域函数。
0.7 为不兼容重构,旧顶层 Session、fetch/frame、Ticker/download、init/data/catalog/universe/sim 入口已撤下。迁移说明列出对应的新入口。历史观测记录保留其原始日期与 SDK 版本,不当作本版本重新执行的证据。
项目与贡献
由 Moonweave AI 维护,文档与公共操作合同随 SDK 一起生成。缺陷与改进请提交到 项目仓库,提供版本、最小复现、参数和脱敏后的来源错误。不要提交凭据、个人数据或未经允许分发的数据。
包使用 Apache-2.0,见 LICENSE。数据来源权利独立于代码许可证,见 THIRD_PARTY_NOTICES.md。
Metadata
Release files for axiolune 0.7.0
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Total release size: 74.1 MB
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