Tags: Integration, Data, SQL, Intermediate

dbt is one of the widely-used data transformation tools for working with data directly in a data warehouse. It’s optimized for analytics use cases and can be used for business intelligence, operational analytics, and even machine learning.

The Flytekit dbt plugin is a Python module that provides an easy way to invoke basic dbt CLI commands from within a Flyte task. The plugin supports the commands dbt run, dbt test, and dbt source freshness.


To use the dbt plugin you’ll need to install the flytekitplugins-dbt plugin.


See the PyPi page here.

pip install flytekitplugins-dbt

Then install dbt itself. You will have to install dbt-core as well as the correct adapter for the database that you are accessing.

For example, if you are using a Postgres database you would do:

pip install dbt-postgres

This will install dbt-core and dbt-postgres, but not any of the other adapters, dbt-redshift, dbt-snowflake, or dbt-bigquery. See the official installation page for details.

Running the Example

We use a Postgres database installed on the cluster and an example project from dbt, called jaffle-shop. To run the example on your local machine, do the following.


The example below is not designed to run directly in your local python environment. It must be run in a Kubernetes cluster, either locally on your machine using the flytectl demo start command or on a cloud cluster.

Start up the demo cluster on your local machine:

flytectl demo start

Pull the pre-built image for this example:

docker pull ghcr.io/flyteorg/flytecookbook:dbt_example-latest

This image is built using the following Dockerfile and contains:

  • The flytekitplugins-dbt and dbt-postgres Python dependencies.

  • The jaffle-shop example.

  • A postgres database.

See Dockerfile

This Dockerfile can be found in the flytesnacks/examples directory under the filepath listed in the code block title below.

FROM python:3.8-slim-buster

ENV VENV /opt/venv

RUN apt-get update && apt-get install -y build-essential git postgresql-client libpq-dev

# Install the AWS cli separately to prevent issues with boto being written over
RUN pip3 install awscli

ENV VENV /opt/venv
# Virtual environment
RUN python3 -m venv ${VENV}

# Install Python dependencies
COPY requirements.in /root/
RUN pip install -r /root/requirements.in
# psycopg2-binary is a dependency of the dbt-postgres adapter, but that doesn't work on mac M1s.
# As per https://github.com/psycopg/psycopg2/issues/1360, we install psycopg to circumvent this.
RUN pip uninstall -y psycopg2-binary && pip install psycopg2

# Copy the actual code
COPY . /root/

# Copy dbt-specific files
COPY profiles.yml /root/dbt-profiles/
RUN git clone https://github.com/dbt-labs/jaffle_shop.git

# This tag is supplied by the build script and will be used to determine the version
# when registering tasks, workflows, and launch plans
ARG tag


To run this example, copy the code in the dbt example below into a file called dbt_example.py, then run it on your local container using the provided image:

pyflyte run --remote \
    --image ghcr.io/flyteorg/flytecookbook:dbt_example-latest \
    dbt_plugin/dbt_example.py wf

Alternatively, you can clone the flytesnacks repo and run the example directly:

git clone https://github.com/flyteorg/flytesnacks
cd flytesnacks/examples/dbt_example
pyflyte run --remote \
    --image ghcr.io/flyteorg/flytecookbook:dbt_example-latest \
    dbt_plugin/dbt_example.py wf