Implement Airflow dynamic task mapping with expand() and partial() to fan out over a runtime-determined parameter list
domain: airflow.apache.org · 6 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗
Steps
Define a base operator or @task function that accepts a single element of the mapped parameter
Call .expand(param=list_of_values) on the operator or task to generate one mapped task instance per list element at parse time or dynamically at runtime
Use .partial(static_param=value).expand(dynamic_param=values) to fix shared arguments while varying only the fan-out parameter
Chain mapped tasks to downstream operators; Airflow automatically collects the list of XCom outputs and passes it to the downstream task
Control concurrency of mapped instances using max_active_tis_per_dag or pool slots to avoid overwhelming downstream systems
Inspect mapped task instances in the Grid view of the Airflow UI, which shows each expand index as a separate row
Known gotchas
Dynamic task mapping requires Airflow 2.3+; the expand() list is resolved either at parse time (static list) or at start of the task group (dynamic via XCom), not both simultaneously in all versions
Mapping over a very large list creates a mapped task instance for every element in the same scheduler cycle — use chunking or limit list size to avoid scheduler overload
If an upstream @task returns a list, that list is automatically mapped when passed to expand(); wrapping it in a list literal creates a nested structure instead of mapping, which is a common mistake
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