Some core functionality may be limited. If you're interested in contributing, check out the source code for each repository listed below.
- Maintained by: fal.ai
- Authors: Features & Labels
- GitHub repo: fal-ai/fal
- PyPI package:
- Slack channel: #tools-fal
- Supported dbt Core version: v1.3.0 and newer
- dbt Cloud support: Not Supported
- Minimum data platform version: n/a
pip to install the adapter. Before 1.8, installing the adapter would automatically install
dbt-core and any additional dependencies. Beginning in 1.8, installing an adapter does not automatically install
dbt-core. This is because adapters and dbt Core versions have been decoupled from each other so we no longer want to overwrite existing dbt-core installations.
Use the following command for installation:
For fal-specific configuration, please refer to fal configs.
Setting up fal with other adapter
fal offers a Python runtime independent from what database you are using and integrates seamlessly with dbt. It works by downloading the data as a Pandas DataFrame, transforming it in a local Python runtime and uploading it to the database. The only configuration change you need to do is adding it to the
profiles.yml and setting the
db_profile property as the database profile you are already using.
It will run all the SQL dbt models with the main adapter you specified in your
profiles.yml and all the Python models are executed by the fal adapter.
db_profile: dev_pg # This points to your main adapter