chDB DataStore — ClickHouse-backed pandas, one-line speedup
Swap import pandas for chdb.datastore to get a lazy ClickHouse-backed DataFrame API with S3/database connectors and cross-source joins
- What
- Swap import pandas for chdb.datastore to get a lazy ClickHouse-backed DataFrame API with S3/database connectors and cross-source joins
- Cost
- Free
- Needs
- Python 3.9+ on macOS or Linux; pip install chdb in your environment (no Windows support)
- Install
- Copy the installer prompt below into your Muse — your agent does the rest.
Curated by Skill Harbor — @clickhouse's skill for teaching agents the chDB DataStore: a lazy, ClickHouse-backed pandas replacement where changing one import line (`import pandas as pd` → `import chdb.datastore as pd`) keeps existing pandas code working unchanged while operations compile to optimized SQL and execute only when results are needed. The skill covers the decision tree (file analysis, cross-source joins, "pandas too slow", raw SQL → use the chdb-sql skill instead), one-pattern connectors for 16+ sources (local files, MySQL, Postgres, S3, ClickHouse Cloud, Iceberg, Delta Lake), the full pandas API (209 supported methods, with `.to_sql()` to inspect generated SQL), the killer feature of joining DataFrames across different sources, and troubleshooting for common setup issues. Apache-2.0 licensed. Honest caveats: requires Python 3.9+ on macOS or Linux (`pip install chdb`) — no Windows; this skill teaches using DataStore, not ClickHouse server administration or raw SQL authoring; example code in the wild embeds plaintext DB credentials, so prefer the secure vault for connection strings. Skill Harbor never reviews the code, review it yourself before use. Discovered via skills.sh.
Version:
Install
Prerequisites: Python 3.9+ on macOS or Linux; pip install chdb in your environment (no Windows support) Install "chDB DataStore — ClickHouse-backed pandas, one-line speedup" for me. It teaches my agent @clickhouse's chDB DataStore: a lazy ClickHouse-backed pandas replacement where one import-line change keeps existing pandas code working while operations compile to optimized SQL; plus connectors for 16+ data sources (files, MySQL, Postgres, S3, ClickHouse Cloud, Iceberg, Delta Lake), 209 supported DataFrame methods, cross-source joins, .to_sql() inspection, and troubleshooting. Apache-2.0 licensed. Repository: https://github.com/clickhouse/agent-skills/blob/main/skills/chdb-datastore/SKILL.md 1. Fetch the SKILL.md file (and any helper files) from the repository path into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via the secure vault, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "chdb-datastore". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. run pip install chdb, and save my database credentials in the vault — never paste them into chat). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. If anything looks off, stop and ask me.
Questions
How do I install a build?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you — no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.
What does the ✓ next to a creator’s name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a build before installing it.