![]() execute ( self, context : Dict ) ¶ class. The condition is determined by the result of python_callable. True, downstream tasks proceed as normal. Anyĭownstream tasks are marked with a state of "skipped". It evaluates aĬondition and short-circuits the workflow if the condition is False. The ShortCircuitOperator is derived from the PythonOperator. Workflow "short-circuits" and downstream tasks are skipped. ShortCircuitOperator ¶Īllows a workflow to continue only if a condition is met. The skipped states are propagatedĭownstream to allow for the DAG state to fill up and the DAG run's state This means you can define multiple DAGs per Python file, or even spread one very complex DAG across multiple Python files using imports. It will take each file, execute it, and then load any DAG objects from that file. Or directly downstream tasks are marked with a state of skipped so that Airflow loads DAGs from Python source files, which it looks for inside its configured DAGFOLDER. Should point to a task directly downstream from. It derives the PythonOperator and expects a Python function that returnsĪ single task_id or list of task_ids to follow. BranchPythonOperator ¶īases:, Īllows a workflow to "branch" or follow a path following the execution Template_fields = ¶ template_fields_renderers ¶ BLUE = #ffefeb ¶ ui_color ¶ shallow_copy_attrs = ¶ execute ( self, context : Dict ) ¶ execute_callable ( self ) ¶Ĭalls the python callable with the given arguments. Processing templated fields, for examples Templates_exts ( list ) - a list of file extensions to resolve while In your callable's context after the template has been applied. _init_ and execute takes place and are made available Will get templated by the Airflow engine sometime between Templates_dict ( dict ) - a dictionary where the values are templates that Op_args ( list ( templated )) - a list of positional arguments that will get unpacked when Op_kwargs ( dict ( templated )) - a dictionary of keyword arguments that will get unpacked PythonOperator ( *, python_callable : Callable, op_args : Optional = None, op_kwargs : Optional = None, templates_dict : Optional = None, templates_exts : Optional ] = None, ** kwargs ) ¶įor more information on how to use this operator, take a look at the guide: Dict will unroll to xcom values with keys as keys.Ĭlass. Multiple_outputs ( bool) - if set, function return value will be Op_args ( list) - a list of positional arguments that will get unpacked when Op_kwargs ( dict) - a dictionary of keyword arguments that will get unpacked Python_callable ( python callable) - A reference to an object that is callable Please use the following instead:įrom corators import my_task() Parameters task ( python_callable : Optional = None, multiple_outputs : Optional = None, ** kwargs ) ¶ Deprecated function that calls and allows users to turn a python function into an Airflow task.
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