Introduction

Dagster is a system for building modern data applications.

Combining an elegant programming model and beautiful tools, Dagster allows infrastructure engineers, data engineers, and data scientists to seamlessly collaborate to process and produce the trusted, reliable data needed in today's world.

Install

To get started:

pip install dagster dagit

This installs two modules:

dagster | The core programming model and abstraction stack; stateless, single-node, single-process and multi-process execution engines; and a CLI tool for driving those engines.
dagit | A UI and rich development environment for Dagster, including a DAG browser, a type-aware config editor, and a streaming execution interface.

Learn

Next, jump right into our tutorial, or read our complete documentation. If you're actively using Dagster or have questions on getting started, we'd love to hear from you; come join our slack!

Contributing

For details on contributing or running the project for development, check out our contributing guide.

Integrations

Dagster works with the tools and systems that you're already using with your data, including:

Integration		Dagster Library
	Apache Airflow	dagster-airflow Allows Dagster pipelines to be scheduled and executed, either containerized or uncontainerized, as Apache Airflow DAGs.
	Apache Spark	dagster-spark · dagster-pyspark Libraries for interacting with Apache Spark and Pyspark.
	Dask	dagster-dask Provides a Dagster integration with Dask / Dask.Distributed.
	DataDog	dagster-datadog Provides a Dagster resource for publishing metrics to DataDog.
/	Jupyter / Papermill	dagstermill Built on the papermill library, dagstermill is meant for integrating productionized Jupyter notebooks into dagster pipelines.
	PagerDuty	dagster-pagerduty A library for creating PagerDuty alerts from Dagster workflows.
	Snowflake	dagster-snowflake A library for interacting with the Snowflake Data Warehouse.
Cloud Providers
	AWS	dagster-aws A library for interacting with Amazon Web Services. Provides integrations with S3, EMR, and (coming soon!) Redshift.
	GCP	dagster-gcp A library for interacting with Google Cloud Platform. Provides integrations with BigQuery and Cloud Dataproc.

This list is growing as we are actively building more integrations, and we welcome contributions!

Example Projects

Several example projects are provided under the examples folder demonstrating how to use Dagster, including: