DagsterDocs

Getting Started with Dagster #

Dagster is a data orchestrator for machine learning, analytics, and ETL

New to Dagster? Learn all about it in a short tutorial.

Take the Tutorial

Or read about:

Quick Start #

Installing Dagster #

To install Dagster and Dagit into an existing Python environment, run:

pip install dagster

This will install the latest stable version of the core Dagster packages in your current Python environment.

Writing a Job #

Let's get your first job up and running.

from dagster import job, op


@op
def get_name():
    return "dagster"


@op
def hello(context, name: str):
    context.log.info(f"Hello, {name}!")


@job
def hello_dagster():
    hello(get_name())

Save the code above in a file named hello_world.py.

You can execute the job in three different ways: Dagit, Dagster Python API, or Dagster CLI.

Running the Job in Dagit #

It's highly recommended to use Dagit with Dagster. Dagit is a web-based interface for viewing and interacting with Dagster objects.

pip install dagit

To visualize your job in Dagit, run the following command:

dagit -f hello_world.py

Then navigate to http://localhost:3000 to start using Dagit:

dagit-def

Click on the "Launchpad" tab, then press the "Launch Execution" button to execute the job. You will then see Dagit launches a job run:

dagit-run

Other Options to Run Dagster Jobs #

You can also execute the job without the UI in the following methods:

Dagster Python API

if __name__ == "__main__":
    result = hello_dagster.execute_in_process()

Dagster CLI

dagster job execute -f hello_world.py

If You Get Stuck #

If you have questions on getting started, we'd love to hear from you:

join-us-on-slack