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Pass data between tasks | Astronomer Documentation

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Sharing data between tasks is a very common use case in Airflow. If you've been writing DAGs, you probably know that breaking them up into smaller tasks is a best practice for debugging and recovering quickly from failures. What do you do when one of your downstream tasks requires metadata about an upstream task, or processes the results of the task immediately before it? There are a few methods you can use to implement data sharing between your Airflow tasks. In this guide, you'll walk through the two most commonly used methods, learn when to use them, and use some example DAGs to understand how they can be implemented. There are multiple resources for learning about this topic. See also: To get the most out of this guide, you should have an understanding of: Before you dive into the specifics, there are a couple of important concepts to understand before you write DAGs that pass data between tasks. An important concept for any data pipeline, including an Airflow DAG, is idempotency.

> 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. # Pass data between tasks > Learn more about the most common methods to implement data sharing between your Airflow tasks, including an in-depth explanation of XCom. > **Info** > > This page has not yet been updated for Airflow 3. The concepts shown are relevant, but some code may need to be updated. If you run any examples

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