The DBT integration updates metadata from your DBT manifest into the data lineage graph.
|Namespace||Namespace for the connection, see namespaces||default|
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="email@example.com", 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