prefect-dbt
is a collection of Prefect integrations for working with dbt with your Prefect flows.
Requires an installation of Python 3.7+.
We recommend using a Python virtual environment manager such as pipenv, conda or virtualenv.
These tasks are designed to work with Prefect 2.0. For more information about how to use Prefect, please refer to the Prefect documentation.
Install prefect-dbt
with pip
:
pip install prefect-dbt
Some dbt CLI profiles require additional installation; for example Databricks:
pip install dbt-databricks
Then, register to view the blocks on Prefect Cloud:
prefect block register -m prefect_dbt
Note, to use the load
method on Blocks, you must already have a block document saved through code or saved through the UI.
from prefect import flow
from prefect_dbt.cloud import DbtCloudCredentials
from prefect_dbt.cloud.jobs import trigger_dbt_cloud_job_run_and_wait_for_completion
@flow
def run_dbt_job_flow():
run_result = trigger_dbt_cloud_job_run_and_wait_for_completion(
dbt_cloud_credentials=DbtCloudCredentials(
api_key="my_api_key",
account_id=123456789
),
job_id=1
)
run_dbt_job_flow()
from prefect import flow
from prefect_dbt.cli.commands import trigger_dbt_cli_command
@flow
def trigger_dbt_cli_command_flow() -> str:
result = trigger_dbt_cli_command("dbt debug")
return result # Returns the last line the in CLI output
trigger_dbt_cli_command_flow()
from prefect import flow
from prefect_snowflake.credentials import SnowflakeCredentials
from prefect_snowflake.database import SnowflakeConnector
from prefect_dbt.cli.credentials import DbtCliProfile
from prefect_dbt.cli.commands import trigger_dbt_cli_command
from prefect_dbt.cli.configs import SnowflakeTargetConfigs
@flow
def trigger_dbt_cli_command_flow():
connector = SnowflakeConnector(
schema="public",
database="database",
warehouse="warehouse",
credentials=SnowflakeCredentials(
user="user",
password="password",
account="account.region.aws",
role="role",
),
)
target_configs = SnowflakeTargetConfigs(
connector=connector
)
dbt_cli_profile = DbtCliProfile(
name="jaffle_shop",
target="dev",
target_configs=target_configs,
)
result = trigger_dbt_cli_command(
"dbt debug",
overwrite_profiles=True,
dbt_cli_profile=dbt_cli_profile
)
return result
trigger_dbt_cli_command_flow()
from prefect import flow
from prefect_dbt.cli.credentials import DbtCliProfile
from prefect_dbt.cli.commands import trigger_dbt_cli_command
@flow
def trigger_dbt_cli_commands_flow():
dbt_cli_profile = DbtCliProfile.load("MY_BLOCK_NAME")
trigger_kwargs = dict(
profiles_dir=".",
overwrite_profiles=True,
dbt_cli_profile=dbt_cli_profile,
)
trigger_dbt_cli_command(
"dbt deps",
**trigger_kwargs
)
result = trigger_dbt_cli_command(
"dbt debug",
**trigger_kwargs
)
return result
trigger_dbt_cli_commands_flow()
If you encounter any bugs while using prefect-dbt
, feel free to open an issue in the prefect-dbt repository.
If you have any questions or issues while using prefect-dbt
, you can find help in either the Prefect Discourse forum or the Prefect Slack community.
If you need help getting started with or using dbt, please consult the dbt documentation.
Feel free to ⭐️ or watch prefect-dbt
for updates too!
If you'd like to install a version of prefect-dbt
for development, clone the repository and perform an editable install with pip
:
git clone https://github.com/PrefectHQ/prefect-dbt.git
cd prefect-dbt/
pip install -e ".[dev]"
# Install linting pre-commit hooks
pre-commit install