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Integrations
dbt

dbt

The DBT integration updates metadata from your DBT manifest into the data lineage graph.

Web App

dbt integration

Fields

FieldValueExample
NamespaceNamespace for the connection, see namespacesdefault

Python Library

Installation

Install dbt Grai package with pip

pip install grai-source-dbt

This installs the Grai dbt integration, which is now ready to run in python

Connecting & Syncing

The integration comes equipped with the client library already but we will need a python terminal or Jupyter Notebook to execute a few commands to establish a connection and begin querying the server.

Spin up your favorite python terminal then:

import os
from grai_source_dbt.base import update_server

For now we will use the default user credentials though you are free to create a new user / api keys from the server admin interface at http://localhost:8000/admin (opens in a new tab).

client = ClientV1("localhost", "8000", username="null@grai.io", password="super_secret")

Now we can update the server with data from any dbt source. In order to do so you will need to pass credentials and namespace into the update_server function. Namespace is used to uniquely identify the nodes and when used consistently will allow you to add to the node from any source.

Using example variables, in order to update the server with your metadata, simply run:

update_server(client, manifest_file=[path_to_your_manifest_file], namespace=[your_namespace])

DBT Manifest Version Support

Manifest VersionStatus
v1
v2
v3
v4
v5
v6
v7
v8