chdb-sql
Use when the user wants to run SQL — especially analytical SQL — on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL…
Skill by chdb-ioOfficial
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: spreadsheets, backend, cloud, data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/chdb-sql
What's inside
- Skill name
chdb-sql- Description
- Use when the user wants to run SQL — especially analytical SQL — on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB — embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server administration.
- License
- Apache-2.0
- Compatibility
- Requires Python 3.9+, macOS or Linux. pip install chdb.
- Metadata
- author: chdb-io · version: 4.1 · homepage: https://clickhouse.com/docs/chdb
- Instructions
- 93 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (8)
- README.md
- SKILL.md
- examples.md · examples/
- metadata.json
- api-reference.md · references/
- sql-functions.md · references/
- table-functions.md · references/
- verify_install.py · scripts/
SKILL.md (first lines)
# chdb SQL — ClickHouse in Your Python Process
Run ClickHouse SQL directly in Python — no server needed. Query local files, remote databases, and cloud storage with full ClickHouse SQL power.
```bash
pip install chdb
```
## Decision Tree: Pick the Right API
```
1. One-off query on files or databases → chdb.query()
2. Multi-step analysis with tables → Session
3. DB-API 2.0 connection → chdb.connect()
4. Pandas-style DataFrame operations → Use chdb-datastore skill instead
```
## chdb.query() — One Line, Any Data
```python
import chdb
chdb.query("SELECT * FROM file('data.parquet', Parquet) WHERE price > 100 LIMIT 10") # local files
chdb.query("SELECT * FROM mysql('db:3306', 'shop', 'orders', 'root', 'pass')") # databases
chdb.query("SELECT * FROM s3('s3://bucket/data.parquet', NOSIGN) LIMIT 10") # cloud storage
chdb.query("SELECT * FROM deltaLake('s3://bucket/delta/table', NOSIGN) LIMIT 10") # data lakes
# Cross-source join
chdb.query("""
SELECT u.name, o.amount FROM mysql('db:3306', 'crm', 'users', 'root', 'pass') AS u
JOIN file('orders.parquet', Parquet) AS o ON u.id = o.user_id ORDER BY o.amount DESC
""")
data = {"name": ["Alice", "Bob"], "score": [95, 87]}
chdb.query("SELECT * FROM Python(data) ORDER BY score DESC") # Python data
df = chdb.query("SELECT * FROM numbers(10)", "DataFrame") # output formats
chdb.query("SELECT toDate({d:String}) + number FROM numbers({n:UInt64})",
"DataFrame", params={"d": "2025-01-01", "n": 30}) # parametrized
```
Table functions → [table-functions.md](references/table-functions.md) | SQL functions → [sql-functions.md](references/sql-functions.md) | Full API → [api-reference.md](references/api-reference.md)
## Session — Stateful Analysis Pipelines
```python
from chdb import session as chs
sess = chs.Session("./analytics_db") # persistent; Session() for in-memory
sess.query("CREATE TABLE users ENGINE=MergeTree() ORDER BY id AS SELECT * FROM mysql('db:3306','crm','users','root','pass')")
sess.query("CREATE TABLE events ENGINE=MergeTree() ORDER BY (ts,user_id) AS SELECT * FROM s3('s3://logs/events/*.parquet',NOSIGN)")
sess.query("""
SELECT u.country, count() AS cnt, uniqExact(e.user_id) AS users
FROM events e JOIN users u ON e.user_id = u.id
WHERE e.ts >= today() - 7 GROUP BY u.country ORDER BY cnt DESC
""", "Pretty").show()
sess.close()
```
## Connection API (DB-API 2.0)
```python
from chdb import dbapi
conn = dbapi.connect()
cur = conn.cursor()
cur.execute("SELECT * FROM file('data.parquet', Parquet) WHERE value > 100")
print(cur.fetchall())
cur.close()
conn.close()
```
## Troubleshooting
| Problem | Fix |
|---------|-----|
| `ImportError: No module named 'chdb'` | `pip install chdb` |
| `DB::Exception: FILE_NOT_FOUND` | Check file path; use absolute path or verify cwd |
| `DB::Exception: Unknown table function` | Check function name spelling (e.g., `deltaLake` not `deltalake`) |
| Connection refused to remote DB | Check host:port format; ensure remote DB allows connections |
| Environment check | Run `python scripts/verify_install.py` (from skill directory) |
## References
- [API Reference](references/api-reference.md) — query/Session/connect signatures
- [Table Functions](references/table-functions.md) — All ClickHouse table functions
- [SQL Functions](references/sql-functions.md) — Commonly used SQL functions
- [Examples](examples/examples.md) — 9 runnable examples with expected output
- [Official Docs](https://clickhouse.com/docs/chdb)
> Note: This skill teaches how to *use* chdb SQL.
> For pandas-style operations, use the `chdb-datastore` skill.
> For contributing to chdb source code, see CLAUDE.md in the project root.From ClickHouse/agent-skills, Apache-2.0.
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AGENTS.md · ClickHouse/agent-skills
ClickHouse
AGENTS.md from ClickHouse/agent-skills: 212 lines covering Repository Overview, Repository Structure, Creating a New Skill, Contributing Guidelines and more.
TemplateDFreshness: D★ 560Codex +5
Signals
- Stars
- 560
- Forks
- 38
- Open issues
- 1
- Last commit (this folder)
- May 26, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 4.1
- License
- Apache-2.0
- Repository
- github.com/ClickHouse/agent-skills
- Website
- clickhouse.ai
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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chdb-sql skill. Agent Mart. https://agentmart.dev/skills/clickhouse-chdb-sql (last updated 2026-10-24)