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#ask-ai
Title
# ask-ai
b

Brendan Jackson

02/16/2024, 6:30 PM
How do I add a dbt source asset to an asset group in dagster?
s

Scout

02/16/2024, 6:30 PM
To add a dbt source asset to an asset group in Dagster, you can define the dbt source as a Dagster asset and specify the
group_name
property. Here's a step-by-step guide based on the documentation: 1. Create a file called
sources.yml
inside the
models/
directory of your dbt project. 2. Define your dbt source in the
sources.yml
file and include metadata that specifies the corresponding Dagster asset key. For example:
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yaml version: 2  sources:   - name: jaffle_shop     tables:       - name: raw_customers         meta:           dagster:             asset_key: ["raw_customers"] # This metadata specifies the corresponding Dagster asset for this dbt source.
3. In your Dagster code, define the dbt source as a Dagster asset and assign it to a group by using the
@asset
decorator with the
group_name
property:
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python @asset(group_name="your_asset_group_name") def dbt_source_asset():     # Your logic to load the dbt source data     pass
By following these steps, you can organize your dbt source assets into groups, which helps manage and visualize them in the Dagster UI. Remember to replace
"your_asset_group_name"
with the actual name of the asset group you want to use. Please note that the code example provided here is a general representation based on the documentation's guidance. You will need to adapt it to fit the specifics of your dbt project and Dagster assets.
b

Brendan Jackson

02/16/2024, 6:32 PM
Is there a way to do it without referencing dagster in dbt code (i.e. without the 'meta' step)
@Scout is there a way to do it without referencing dagster in dbt code (i.e. without the 'meta' step)?
s

Scout

02/16/2024, 6:32 PM
Yes, you can integrate dbt models into Dagster without referencing Dagster in your dbt code. You can achieve this by using the
dagster-dbt
library, which provides a set of abstractions to work with dbt within Dagster. Here's how you can do it: 1. Install the
dagster-dbt
library if you haven't already:
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shell pip install dagster-dbt
2. Use the
dbt_cli_resource
to configure your dbt project within Dagster. This resource allows you to run dbt commands within Dagster without modifying your dbt code. 3. Define a Dagster asset that represents the dbt model. You can use the
dbt_cli_resource
to run dbt commands such as
dbt run
or
dbt test
and specify the models you want to run. 4. Add the dbt asset to an asset group by specifying the
group_name
parameter in the
@asset
decorator. Here's an example of how you might define a dbt asset in Dagster and add it to an asset group:
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python from dagster import asset, AssetGroup from dagster_dbt import dbt_cli_resource  # Configure the dbt CLI resource dbt_cli = dbt_cli_resource.configured(     {         "project_dir": "path/to/your/dbt/project",         "profiles_dir": "path/to/your/dbt/profiles",     } )  # Define a Dagster asset for a dbt model @asset(required_resource_keys={"dbt"}, group_name="your_asset_group_name") def dbt_model(context):     # Run the dbt model     context.resources.dbt.run(models=["your_dbt_model_name"])  # Create an asset group with the dbt asset asset_group = AssetGroup([dbt_model], resource_defs={"dbt": dbt_cli})
In this example,
your_dbt_model_name
should be replaced with the actual name of your dbt model, and
your_asset_group_name
should be replaced with the name of the asset group you want to use. The
dbt_model
asset will be part of the specified asset group and can be managed within Dagster's asset catalog. By using the
dagster-dbt
library, you can integrate dbt with Dagster without having to add Dagster-specific metadata to your dbt project. This approach keeps your dbt codebase clean and focused on dbt-specific configurations.
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