dbt-polars

A dbt adapter that runs models locally using Polars. Instead of connecting to a database, dbt-polars reads and writes files — on your local filesystem, Azure Blob Storage, AWS S3, or an Iceberg catalog.

Installation

pip install dbt-polars

Extra dependencies are required for cloud and Iceberg backends:

pip install 'dbt-polars[azure]'    # Azure Blob Storage
pip install 'dbt-polars[s3]'       # AWS S3
pip install 'dbt-polars[iceberg]'  # Apache Iceberg (SQLite, REST, Databricks, …)

Catalogs

dbt-polars uses catalogs to define where data is stored. Each catalog maps to a storage backend. You can configure multiple catalogs in a single profile and reference them from your models.

Catalog	Backend	Status
`local`	Local filesystem	Usable
`iceberg` with SQLite	Iceberg + SQLite metastore	Usable
`iceberg` with REST + Databricks	Iceberg REST API (Unity Catalog)	Experimental
`iceberg` with other backends	Any pyiceberg-supported backend	Experimental
`azure`	Azure Blob Storage / ADLS Gen2	Experimental

Quick start

A minimal profiles.yml for local development:

my_project:
  target: dev
  outputs:
    dev:
      type: polars
      schema: dev
      catalogs:
        - name: my_catalog
          type: local
          root: ./data

Documentation

Metadata

Release files for dbt-polars 0.1.0

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Source distribution for dbt-polars 0.1.0
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