gus_dagster_project

Copied From Pete's Crash Course)

This is a Dagster project scaffolded with dagster project scaffold.

Getting started

First, create a base Python 3.9 environment. I prefer to use conda, but the choice is yours

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

pip install -e ".[dev]"

Then, start the Dagit web server:

dagit

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

You can start writing assets in gus_dagster_project/assets/. The assets are automatically loaded into the Dagster repository as you define them.

Development

Adding new Python dependencies

You can specify new Python dependencies in setup.py.

Unit testing

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

pytest gus_dagster_project_tests

Schedules and sensors

If you want to enable Dagster Schedules or Sensors for your jobs, start the Dagster Daemon process in the same folder as your workspace.yaml file, but in a different shell or terminal.

The $DAGSTER_HOME environment variable must be set to a directory for the daemon to work. Note: using directories within /tmp may cause issues. See Dagster Instance default local behavior for more details.

dagster-daemon run

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.

Check out the Dagster Cloud Documentation to learn more.