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Core concepts#

Learn about Dagster's core concepts and how to use them in your data platform.

Asset definition#

An asset is an object in persistent storage, such as a table, file, or persisted machine learning model. An asset definition is a Dagster object that couples an asset to the function and upstream assets used to produce its contents.


Dagster offers several ways to run data pipelines without manual intervention, including traditional scheduling and event-based triggers.

Partitions and backfills#

An asset defininition or job can represent a collection of partitions that can be tracked and executed independently.

Resources & configuration#

Resources enable you to separate logic from external dependencies, making developing and testing possible in multiple environments.

Learn more about resources.

Additionally, Dagster provides a configuration system that allows you to document, schematize, and error-check your configuration.

Code locations#

A code location is a collection of Dagster definitions, including assets, jobs, schedules, sensors, and resources. Dagster tools like the Dagster webserver/UI and CLI use code locations to load your code.

Dagster UI#

The Dagster UI is a web-based interface for viewing and interacting with Dagster objects.

Learn more about the Dagster UI.


Dagster enables you to build testable and maintainable data applications. It provides ways to allow you unit-test your data applications, separate business logic from environments, and set explicit expectations on uncontrollable inputs.

Learn more about testing.

Advanced concepts#

Ops and jobs#

Ops typically perform relatively simple tasks, such as executing a database query or sending a Slack message.

An op graph is a set of interconnected ops or sub-graphs. While individual ops typically perform simple tasks, ops can be assembled into a graph or job to accomplish complex tasks.

Metadata & tags#

Apply tags and metadata to organize your project and provide useful context to other members of your team.

Dagster Pipes (Experimental)#

Dagster Pipes is a toolkit for building integrations between Dagster and external execution environments.

I/O management#

I/O managers are user-provided objects that store asset and op outputs and load them as inputs to downstream assets and ops.

Dagster Types#

The Dagster Type system provides gradual, opt-in typing for the inputs and outputs of assets and ops.

Learn more about Dagster types.


A rich, extensible logging system, Dagster's built-in logger tracks all execution events. Loggers can also be customized to fit your infrastructure.

GraphQL API#

The GraphQL API allows you to interact programmatically with Dagster.