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 ( *, python_callable, op_args = None, op_kwargs = None, templates_dict = None, templates_exts = None, show_return_value_in_logs = True, ** kwargs ) ¶īases: PythonOperator, Ī workflow can “branch” or follow a path after the execution of this task. determine_kwargs ( context ) ¶ execute_callable ( ) ¶Ĭalls the python callable with the given arguments. Refer to get_template_context for more context. This is the main method to derive when creating an operator.Ĭontext is the same dictionary used as when rendering jinja templates. Template_fields : Sequence = ('templates_dict', 'op_args', 'op_kwargs') ¶ template_fields_renderers ¶ BLUE = '#ffefeb' ¶ ui_color ¶ shallow_copy_attrs : Sequence = ('python_callable', 'op_kwargs') ¶ execute ( context ) ¶ Such as transmission a large amount of XCom to TaskAPI. It can be set to False to prevent log output of return value when you return huge data Defaults to True, which allows return value log output. Show_return_value_in_logs ( bool) – a bool value whether to show return_value Processing templated fields, for examples Templates_exts ( Sequence | None) – 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 | None) – a dictionary where the values are templates that Op_args ( Collection | None) – a list of positional arguments that will get unpacked when Op_kwargs ( Mapping | None) – a dictionary of keyword arguments that will get unpacked Python_callable ( Callable) – A reference to an object that is callable PythonOperator ( *, python_callable, op_args = None, op_kwargs = None, templates_dict = None, templates_exts = None, show_return_value_in_logs = True, ** kwargs ) ¶īases: ĭef my_python_callable ( ** kwargs ): ti = kwargs next_ds = kwargs Parameters Dict will unroll to xcom values with keys as keys.Ĭlass. Multiple_outputs ( bool | None) – if set, function return value will be Op_args – a list of positional arguments that will get unpacked when Op_kwargs – a dictionary of keyword arguments that will get unpacked Python_callable ( Callable | None) – A reference to an object that is callable Please use the following instead:įrom corators import my_task() Parameters task ( python_callable = None, multiple_outputs = None, ** kwargs ) ¶Ĭalls and allows users to turn a python function intoĪn Airflow task. Retrieve the execution context dictionary without altering user method's signature.Ī. What is not part of the Public Interface of Apache Airflow?.Using Public Interface to integrate with external services and applications.Using Public Interface to extend Airflow capabilities.ExternalPythonOperator.execute_callable().PythonVirtualenvOperator.execute_callable().PythonVirtualenvOperator.template_fields.PythonOperator.template_fields_renderers.Using the Public Interface for DAG Authors.

Airflow operator