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LiteQuant Python SDK

LiteQuant Python SDK 用于在本地下载和读取 LiteQuant 数据。SDK 会自动处理连接、同步、本地 Parquet 缓存和常见错误提示。

支持 Python 3.8 及以上版本。

Installation

pip install litequant

Quick Start

from litequant import LiteQuantClient

client = LiteQuantClient(
    api_token="your_api_token",
    save_path="./litequant_data",
)

client.UpdateAllCategory(update_method="incremental")
df = client.GetCategory("cn_stock_pivot#open")
print(df.tail())

client.close()

推荐使用上下文管理器自动关闭连接:

from litequant import LiteQuantClient

with LiteQuantClient(api_token="your_api_token", save_path="./litequant_data") as client:
    categories = client.ListCategories()
    df = client.GetCategory(categories[0])

默认 API 地址为 https://www.litequant.pro。如需连接测试环境,可以传入 api_url 或设置环境变量 LITEQUANT_API_URL

Transport Security

  • API Token 只会发送到 HTTPS 地址;仅允许 localhost127.0.0.1::1 使用 HTTP 本地调试。
  • SDK 不跟随 API 重定向,避免临时连接凭证被转发到其他地址。
  • 第三方 API 返回的外部明文 Redis/Tair 连接会被拒绝;官方生产 API 仅可在服务端明确声明受限传输策略、目标地址和端口均匹配时使用短期连接凭证。
  • 远端数据写入本地前必须通过 SHA-256 校验;不完整或异常元数据会被拒绝。
  • 数据类别名称会经过严格校验,不能越过 save_path 读写或删除文件。

Windows wheel 会将连接与同步核心编译为 .pyd,不随包分发对应的 Python 源文件。这可以提高查看和修改内部实现的门槛,但不应被视为不可逆向的安全边界;长期密钥和权限判断始终保留在服务端。

Error Handling

SDK 默认会在 Python 终端输出功能面错误提示,同时抛出类型化异常。错误信息不会展示后端细节。

from litequant import LiteQuantClient, LiteQuantError

try:
    with LiteQuantClient(api_token="your_api_token", save_path="./litequant_data") as client:
        df = client.GetCategory("cn_stock_pivot#open")
except LiteQuantError as exc:
    print(exc.code)
    print(exc.user_message)
    print(exc.retryable)

如果你希望完全自己处理错误提示,可以关闭终端输出:

client = LiteQuantClient(
    api_token="your_api_token",
    save_path="./litequant_data",
    display_errors=False,
)

常见公开错误码:

  • AUTH_INVALID:API 凭证无效或已过期
  • ACCOUNT_UNAVAILABLE:账号不可用
  • SUBSCRIPTION_UNAVAILABLE:套餐不可用或已过期
  • PERMISSION_DENIED:权限不足
  • CONNECTION_LIMIT:连接数已达上限
  • CONNECTION_INTERRUPTED:连接已中断,请重新连接
  • REQUEST_INVALID:请求参数无效
  • SERVICE_UNAVAILABLE:服务暂时不可用
  • DATA_UNAVAILABLE:数据暂时不可用
  • DATA_VERIFY_FAILED:数据校验失败

Data Cache

SDK 会把数据保存为本地 Parquet 缓存。再次读取同一数据类别时,会优先使用本地缓存;如果本地没有该数据类别,SDK 会自动同步。

当前 pivot 数据支持 monthlydaily 两种分区模式。后续可以在服务端元信息和客户端缓存层一起扩展更多分区模式。

Metadata Contract

数据服务会提供客户端可识别的类别列表、类别元信息和分区元信息。客户端会自动读取这些元信息并完成数据同步。

公开稳定字段包括:

  • partition_mode:pivot 分区模式,目前支持 monthlydaily
  • partition_keys:数据分区标识列表
  • hash:数据校验值
  • key_columns / dedupe_keys:unstack 数据去重键

普通用户通常不需要直接使用这些字段。

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