Use the Airflow TaskFlow API with XCom to pass structured data between decorated tasks in a complex DAG
domain: airflow.apache.org · 6 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗
Steps
Decorate Python functions with @task to create TaskFlow-compatible operators; each return value is automatically pushed as an XCom
Call decorated task functions directly inside a @dag-decorated function to establish dependencies via return-value wiring rather than set_upstream/set_downstream
Use typed return annotations and pass complex objects (dicts, lists) that Airflow serializes to XCom storage automatically
Configure a custom XCom backend by subclassing BaseXCom and setting xcom_backend in airflow.cfg when default database-backed XCom is insufficient for large payloads
Pull XCom values explicitly with ti.xcom_pull when mixing TaskFlow tasks with classic operators in the same DAG
Verify XCom values in the Airflow UI under Admin > XComs or via the REST API GET /xcom/list endpoint
Known gotchas
Returning large objects (DataFrames, file blobs) from @task pushes them to the metadata DB by default — always use a custom S3/GCS XCom backend for payloads above a few kilobytes
Mixing @task and classic BaseOperator in the same DAG requires explicit xcom_pull calls; the return-value wiring only works between @task-decorated functions
XCom values are serialized with JSON by default; returning non-JSON-serializable objects silently fails or raises at runtime — use dataclasses or register a custom serializer
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