Dagster University: Dagster + dbt

This is the starter version of the Dagster project made to accompany Dagster University's Dagster + dbt course.

Looking for the finished project for the Dagster + dbt course? Use the module/dagster-and-dbt branch.

Getting started

First, install your Dagster code location as a Python package. By using the --editable flag, pip will install your Python package in "editable mode" so that as you develop, local code changes will automatically apply.

pip install -e ".[dev]"

Duplicate the .env.example file and rename it to .env. Then, fill in the values for the environment variables in the file.

Then, start the Dagster UI web server:

dagster dev

Open http://localhost:3000 with your browser to see the project.

Development

Adding new Python dependencies

You can specify new Python dependencies in setup.py.

Unit testing

Tests are in the dagster_university_tests directory and you can run tests using pytest:

pytest dagster_university_tests

Schedules and sensors

If you want to enable Dagster Schedules or Sensors for your jobs, the Dagster Daemon process must be running. This is done automatically when you run dagster dev.

Once your Dagster Daemon is running, you can start turning on schedules and sensors for your jobs.

Deploy on Dagster Cloud

The easiest way to deploy your Dagster project is to use Dagster Cloud.

Successful Deployment

dbt assets in the Asset graph

Check out the Dagster Cloud Documentation to learn more.

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