:py:mod:`airflow.models.mappedoperator`
=======================================

.. py:module:: airflow.models.mappedoperator


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   airflow.models.mappedoperator.OperatorPartial
   airflow.models.mappedoperator.MappedOperator


Functions
~~~~~~~~~

.. autoapisummary::

   airflow.models.mappedoperator.get_mappable_types
   airflow.models.mappedoperator.validate_mapping_kwargs
   airflow.models.mappedoperator.prevent_duplicates
   airflow.models.mappedoperator.ensure_xcomarg_return_value


Attributes
~~~~~~~~~~

.. autoapisummary::

   airflow.models.mappedoperator.Mappable
   airflow.models.mappedoperator.ValidationSource
   airflow.models.mappedoperator.MAPPABLE_LITERAL_TYPES


.. py:data:: Mappable
   

.. py:data:: ValidationSource
   

.. py:data:: MAPPABLE_LITERAL_TYPES
   

.. py:function:: get_mappable_types()


.. py:function:: validate_mapping_kwargs(op, func, value)


.. py:function:: prevent_duplicates(kwargs1, kwargs2, *, fail_reason)


.. py:function:: ensure_xcomarg_return_value(arg)


.. py:class:: OperatorPartial

   An "intermediate state" returned by ``BaseOperator.partial()``.

   This only exists at DAG-parsing time; the only intended usage is for the
   user to call ``.expand()`` on it at some point (usually in a method chain) to
   create a ``MappedOperator`` to add into the DAG.

   .. py:attribute:: operator_class
      :annotation: :Type[airflow.models.baseoperator.BaseOperator]

      
   .. py:attribute:: kwargs
      :annotation: :Dict[str, Any]

      
   .. py:method:: __attrs_post_init__(self)


   .. py:method:: __repr__(self)

      Return repr(self).


   .. py:method:: __del__(self)


   .. py:method:: expand(self, **mapped_kwargs)


.. py:class:: MappedOperator(context=None)

   Bases: :py:obj:`airflow.models.abstractoperator.AbstractOperator`

   Object representing a mapped operator in a DAG.

   .. py:attribute:: operator_class
      :annotation: :Union[Type[airflow.models.baseoperator.BaseOperator], Dict[str, Any]]

      
   .. py:attribute:: mapped_kwargs
      :annotation: :Dict[str, Mappable]

      
   .. py:attribute:: partial_kwargs
      :annotation: :Dict[str, Any]

      
   .. py:attribute:: task_id
      :annotation: :str

      
   .. py:attribute:: params
      :annotation: :Optional[dict]

      
   .. py:attribute:: deps
      :annotation: :FrozenSet[airflow.ti_deps.deps.base_ti_dep.BaseTIDep]

      
   .. py:attribute:: operator_extra_links
      :annotation: :Collection[airflow.models.baseoperator.BaseOperatorLink]

      
   .. py:attribute:: template_ext
      :annotation: :Sequence[str]

      
   .. py:attribute:: template_fields
      :annotation: :Collection[str]

      
   .. py:attribute:: template_fields_renderers
      :annotation: :Dict[str, str]

      
   .. py:attribute:: ui_color
      :annotation: :str

      
   .. py:attribute:: ui_fgcolor
      :annotation: :str

      
   .. py:attribute:: dag
      :annotation: :Optional[airflow.models.dag.DAG]

      
   .. py:attribute:: task_group
      :annotation: :Optional[airflow.utils.task_group.TaskGroup]

      
   .. py:attribute:: start_date
      :annotation: :Optional[pendulum.DateTime]

      
   .. py:attribute:: end_date
      :annotation: :Optional[pendulum.DateTime]

      
   .. py:attribute:: upstream_task_ids
      :annotation: :Set[str]

      
   .. py:attribute:: downstream_task_ids
      :annotation: :Set[str]

      
   .. py:attribute:: is_mapped
      :annotation: :ClassVar[bool] = True

      
   .. py:attribute:: subdag
      :annotation: :None

      
   .. py:attribute:: HIDE_ATTRS_FROM_UI
      :annotation: :ClassVar[FrozenSet[str]]

      
   .. py:method:: __hash__(self)

      Return hash(self).


   .. py:method:: __repr__(self)

      Return repr(self).


   .. py:method:: __attrs_post_init__(self)


   .. py:method:: get_serialized_fields(cls)
      :classmethod:


   .. py:method:: deps_for(operator_class)
      :staticmethod:


   .. py:method:: task_type(self)
      :property:

      Implementing Operator.


   .. py:method:: inherits_from_empty_operator(self)
      :property:

      Implementing Operator.


   .. py:method:: roots(self)
      :property:

      Implementing DAGNode.


   .. py:method:: leaves(self)
      :property:

      Implementing DAGNode.


   .. py:method:: owner(self)
      :property:


   .. py:method:: email(self)
      :property:


   .. py:method:: trigger_rule(self)
      :property:


   .. py:method:: depends_on_past(self)
      :property:


   .. py:method:: wait_for_downstream(self)
      :property:


   .. py:method:: retries(self)
      :property:


   .. py:method:: queue(self)
      :property:


   .. py:method:: pool(self)
      :property:


   .. py:method:: pool_slots(self)
      :property:


   .. py:method:: execution_timeout(self)
      :property:


   .. py:method:: retry_delay(self)
      :property:


   .. py:method:: retry_exponential_backoff(self)
      :property:


   .. py:method:: priority_weight(self)
      :property:


   .. py:method:: weight_rule(self)
      :property:


   .. py:method:: sla(self)
      :property:


   .. py:method:: max_active_tis_per_dag(self)
      :property:


   .. py:method:: resources(self)
      :property:


   .. py:method:: on_execute_callback(self)
      :property:


   .. py:method:: on_failure_callback(self)
      :property:


   .. py:method:: on_retry_callback(self)
      :property:


   .. py:method:: on_success_callback(self)
      :property:


   .. py:method:: run_as_user(self)
      :property:


   .. py:method:: executor_config(self)
      :property:


   .. py:method:: inlets(self)
      :property:


   .. py:method:: outlets(self)
      :property:


   .. py:method:: get_dag(self)

      Implementing Operator.


   .. py:method:: serialize_for_task_group(self)

      Implementing DAGNode.


   .. py:method:: unmap(self, unmap_kwargs = None)

      Get the "normal" Operator after applying the current mapping.

      If ``operator_class`` is not a class (i.e. this DAG has been deserialized) then this will return a
      SerializedBaseOperator that aims to "look like" the real operator.

      :param unmap_kwargs: Override the args to pass to the Operator constructor. Only used when
          ``operator_class`` is still an actual class.

      :meta private:


   .. py:method:: expand_mapped_task(self, run_id, *, session)

      Create the mapped task instances for mapped task.

      :return: The newly created mapped TaskInstances (if any) in ascending order by map index, and the
          maximum map_index.


   .. py:method:: prepare_for_execution(self)


   .. py:method:: render_template_fields(self, context, jinja_env = None)

      Template all attributes listed in template_fields.

      Different from the BaseOperator implementation, this renders the
      template fields on the *unmapped* BaseOperator.

      :param context: Dict with values to apply on content
      :param jinja_env: Jinja environment
      :return: The unmapped, populated BaseOperator


   .. py:method:: iter_mapped_dependencies(self)

      Upstream dependencies that provide XComs used by this task for task mapping.


   .. py:method:: parse_time_mapped_ti_count(self)

      Number of mapped TaskInstances that can be created at DagRun create time.

      :return: None if non-literal mapped arg encountered, or else total number of mapped TIs this task
          should have


   .. py:method:: run_time_mapped_ti_count(self, run_id, *, session)

      Number of mapped TaskInstances that can be created at run time, or None if upstream tasks are not
      complete yet.

      :return: None if upstream tasks are not complete yet, or else total number of mapped TIs this task
          should have