create-dql-app

The fastest way to start a DQL project.

npx create-dql-app@latest my-analytics
cd my-analytics
npm install
npm install --prefix .dql/connectors duckdb       # DuckDB/local files only
# npm install --prefix .dql/connectors snowflake-sdk  # Snowflake only
# Databricks does not need an extra package.
npm run notebook

Opens a running notebook at http://127.0.0.1:3474 in under 5 minutes on a clean machine. No global install required; the template installs @duckcodeailabs/dql-cli locally and exposes it through npm scripts.

The scaffolded project is a clean starter: dql.config.json, a welcome notebook, and npm scripts for notebook, compile, lineage, doctor, and validate. If a sibling dbt project is detected, it is wired into dql.config.json automatically so dql sync dbt works out of the box.

Database drivers are project-local so the base install stays fast:

| Database | Extra install | Notes | | --- | --- | --- | | Databricks SQL | none | Built into DQL through HTTPS | | DuckDB or local files | npm install --prefix .dql/connectors duckdb | Needed for DuckDB, CSV, Parquet, and JSON | | Snowflake | npm install --prefix .dql/connectors snowflake-sdk | Needed for Snowflake connections |

You can also install DuckDB or Snowflake from the notebook Connections page.

Want a ready-made dbt project to try DQL on? Clone the example repo and add DQL to it — the same steps you'd use on your own dbt repo: github.com/duckcode-ai/jaffle-shop-duckdb.

Already installed @duckcodeailabs/dql-cli globally? That only installs the command. From an existing dbt repo, run dql init ./dql before cd dql.

Flags

| Flag | Default | Meaning | | --- | --- | --- | | --template <name> | starter | Starter template |

Docs

• Quickstart
• Concepts
• Connect your own warehouse

License

MIT