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
See the Getting started guide.
A minimal profiles.yml for local development is:
my_project:
target: dev
outputs:
dev:
type: polars
schema: dev
catalog_type: local
root: ./data
Documentation
1 maintainer
Metadata
1 maintainer
Release files for dbt-polars 0.1.1
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| dbt_polars-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 93.9 kB
Release files / dbt_polars-0.1.1.tar.gz
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