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wherobots-dbt

The Wherobots adapter for dbt. Write spatial models as SQL, run them on Wherobots Cloud, and keep them version-controlled, tested, and documented like the rest of your dbt project.

Install

pip install wherobots-dbt

Requires Python 3.10 or later and dbt Core 1.9 or later (below 2.0).

Configure

Add a Wherobots target to ~/.dbt/profiles.yml. Read the API key from an environment variable so no secret is written to disk.

my_project:
  target: dev
  outputs:
    dev:
      type: wherobots
      host: api.cloud.wherobots.com
      catalog: my_catalog          # a catalog you can write to (dbt's `database`)
      schema: my_namespace
      api_token: "{{ env_var('WHEROBOTS_API_KEY') }}"
      runtime: micro               # optional
      region: aws-us-west-2        # optional
      threads: 1
export WHEROBOTS_API_KEY="<your-api-key>"
dbt debug

What works

  • dbt debug, seed, run, test, snapshot, docs generate, show, and source freshness.
  • Materializations: view, table, ephemeral, incremental (append, merge, delete+insert, insert_overwrite), and snapshot. Persisted models are Havasu (Apache Iceberg) tables.
  • Spatial columns: geometry seeds load from WKT, EWKT, GeoJSON, or WKB with a real SRID, and models can materialize geometry, geography, and raster columns.

Documentation

See Wherobots dbt Adapter for the profile reference, materializations, and working with spatial data.

License

Apache-2.0

Metadata

Release files for wherobots-dbt 0.1.2

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