chdb-sql

Run ClickHouse SQL queries in-process on local files, databases, and cloud storage.

1.6k|107|Updated Feb 15, 2026
One-click install
npx skills add https://github.com/Makisuo/maple --skill chdb-sql-makisuo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: chdb-sql
Source: https://github.com/Makisuo/maple/tree/main/.agents/skills/chdb-sql
Command: npx skills add https://github.com/Makisuo/maple --skill chdb-sql-makisuo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

In-process ClickHouse SQL engine for Python — run powerful queries directly against local files, remote databases, and cloud storage without starting a server.

Core Features & Use Cases

  • In-process SQL execution across file sources (Parquet/CSV/JSON), databases, and cloud data lakes.
  • Stateful analytics via Session, parametrized queries, and window functions.
  • Table functions and DB-API support enable cross-source joins and flexible data workflows.

Quick Start

Install the chdb package and run a simple query to verify basic operation.

Frequently Asked Questions about chdb-sql

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run ClickHouse SQL in Python without starting a server?▼

An in-process SQL engine allows you to run ClickHouse SQL in Python without a server by executing queries directly against local files, remote databases, and cloud storage.

Can I join data from Parquet files and remote databases in a single SQL query?▼

Yes, you can join data from Parquet, CSV, JSON files, and remote databases in a single query using table functions to access cross-source data.

Does Python support parametrized queries and session-based state for ClickHouse?▼

Python supports parametrized queries and stateful analytics via the Session API, allowing you to maintain session-based state across multiple SQL executions.

What is the best way to query cloud storage and local files using SQL in Python?▼

The best way to query cloud storage and local files is using an in-process ClickHouse SQL engine, which provides DB-API 2.0 support and table functions for flexible data workflows.

Do I need a dedicated ClickHouse server to use window functions on local CSV files?▼

No, you do not need a dedicated server to use window functions on local CSV files because the in-process engine executes advanced SQL features directly within the Python process.