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Manage task and task group dependencies in Airflow | Astronomer Documentation

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Dependencies are a powerful and popular Airflow feature. In Airflow, your pipelines are defined as Directed Acyclic Graphs (DAGs). Each task is a node in the graph and dependencies are the directed edges that determine how to move through the graph. Because of this, dependencies are key to following data engineering best practices because they help you define flexible pipelines with atomic tasks. Throughout this guide, the following terms are used to describe task dependencies: In this guide you'll learn about the many ways you can implement dependencies in Airflow, including: To view a video presentation of these concepts, see Manage Dependencies Between Airflow Deployments, DAGs, and Tasks. The focus of this guide is dependencies between tasks in the same DAG. If you need to implement dependencies between DAGs, see Cross-DAG dependencies. To get the most out of this guide, you should have an understanding of: Basic dependencies between Airflow tasks can be set in the following ways:

> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://www.astronomer.io/docs/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://www.astronomer.io/docs/_mcp/server. # Manage task and task group dependencies in Airflow > Learn how to manage dependencies between tasks and TaskGroups in Apache Airflow, including how to set dynamic dependencies. [Dependencies](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html#relationships) are a powerful and popular Airflow fe

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