Python SDK

Overview

Define ClickHouse tables once in Python, then query them by semantic name with tenant isolation and caching.

Datasets are semantic analytics definitions. A dataset models a source table or view with dimensions, measures, relationships, a tenant key, and a time key.

Use datasets when query logic has started to matter beyond one file:

  • define table semantics once
  • query by semantic names instead of hand-written SQL
  • apply tenant and time context consistently
  • cache results under tenant-safe keys
  • share the same definitions with TypeScript services through the language-neutral protocol

The Python SDK splits responsibilities across modules: hypequery.datasets owns definitions, planning, and the client; hypequery.execution owns ClickHouse execution; hypequery.serve owns HTTP delivery.

The fastest way in is the quick start. Then read:

Feature status

What the Python SDK supports today compared with TypeScript.

Definition

Create dataset definitions over ClickHouse tables and views in Python.

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