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Execute_complete method

As explained in Data Pipelines with Apache Airflow, Second Edition

The execute_complete method is an Airflow operator callback that handles completion after a deferred task's trigger signals success.

The execute_complete method is the callback for a deferred Airflow task. After a trigger detects success, Airflow returns execution to a worker, which runs this method before the scheduler marks the task successful. section 9.5.2

A deferrable sensor connects the callback to the rest of the task lifecycle:

  • The callback performs the remaining completion work; a timeout raises an exception and fails the task. section 9.5.2

MovieLens ratings sensor

A custom sensor defers to MovielensTrigger while waiting for ratings, then execute_complete logs "Movie Ratings are Available!". A downstream fetch_ratings task can proceed after the sensor succeeds.

How Data Pipelines with Apache Airflow, Second Edition covers it

How deep it goes
Explains callback placement and worker resumption, but does not detail callback event handling beyond logging.
Examples
Uses a MovieLens ratings sensor whose callback logs availability before a ratings-fetch task runs.
What it assumes
Assumes familiarity with Airflow operators and tasks while demonstrating triggers, deferred execution, and timeout configuration.
What you can do after
Build it from scratch by connecting a deferrable sensor's defer call to an execute_complete callback.
How it connects
Connects execute_complete with deferrable operators, triggers, triggerers, workers, timeouts, and downstream tasks.
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This explainer was generated by Manning's knowledge graph from the text of Data Pipelines with Apache Airflow, Second Edition. The section links point to the parts of the book it draws on.