ccflow_celery
=============

.. py:module:: ccflow_celery


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/ccflow_celery/app/index
   /autoapi/ccflow_celery/config/index
   /autoapi/ccflow_celery/evaluators/index
   /autoapi/ccflow_celery/examples/index
   /autoapi/ccflow_celery/tasks/index


Attributes
----------

.. autoapisummary::

   ccflow_celery.__version__


Classes
-------

.. autoapisummary::

   ccflow_celery.CeleryConfig
   ccflow_celery.CeleryApp
   ccflow_celery.CeleryEvaluator
   ccflow_celery.CeleryGraphEvaluator


Package Contents
----------------

.. py:class:: CeleryConfig(/, **data: Any)

   Bases: :py:obj:`ccflow.BaseModel`


   Configuration for a Celery application.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: broker_url
      :type:  str
      :value: None



   .. py:attribute:: result_backend
      :type:  Optional[str]
      :value: None



   .. py:attribute:: task_serializer
      :type:  str
      :value: 'json'



   .. py:attribute:: result_serializer
      :type:  str
      :value: 'json'



   .. py:attribute:: accept_content
      :type:  list
      :value: None



   .. py:attribute:: task_track_started
      :type:  bool
      :value: True



   .. py:attribute:: task_default_queue
      :type:  str
      :value: 'default'



   .. py:attribute:: task_routes
      :type:  Optional[Dict[str, str]]
      :value: None



   .. py:attribute:: worker_concurrency
      :type:  Optional[int]
      :value: None



   .. py:attribute:: task_always_eager
      :type:  bool
      :value: None



   .. py:attribute:: task_eager_propagates
      :type:  bool
      :value: None



.. py:class:: CeleryApp(/, **data: Any)

   Bases: :py:obj:`ccflow.BaseModel`


   Wrapper around a Celery application instance.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: name
      :type:  str
      :value: None



   .. py:attribute:: config
      :type:  CeleryConfig
      :value: None



   .. py:attribute:: _app
      :type:  Any
      :value: None



   .. py:method:: get_app()


.. py:class:: CeleryEvaluator(/, **data: Any)

   Bases: :py:obj:`ccflow.EvaluatorBase`


   Evaluator that dispatches model execution to Celery workers.

   Serializes the model and context, submits as a Celery task,
   and waits for the result. The model must be reconstructable from its
   Pydantic config dump.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: app
      :type:  ccflow_celery.app.CeleryApp
      :value: None



   .. py:attribute:: timeout
      :type:  Optional[float]
      :value: None



   .. py:attribute:: task_name
      :type:  str
      :value: None



   .. py:attribute:: _celery_app
      :type:  Any
      :value: None



   .. py:method:: _get_celery_app()


   .. py:method:: __call__(context: ccflow.callable.ModelEvaluationContext) -> Any

      This method produces the result for the given context.

      Instead of passing the context, one can pass an object that pydantic will try to validate as the context.
      Additionally, if kwargs are passed instead of the context, it will use these to construct the context.



.. py:class:: CeleryGraphEvaluator(/, **data: Any)

   Bases: :py:obj:`ccflow.EvaluatorBase`


   Evaluator that parallelizes DAG execution via Celery.

   Builds the dependency graph (like GraphEvaluator), then submits
   independent nodes as parallel Celery tasks using Celery groups.
   Nodes that depend on other nodes wait for their dependencies first.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: app
      :type:  ccflow_celery.app.CeleryApp
      :value: None



   .. py:attribute:: timeout
      :type:  Optional[float]
      :value: None



   .. py:attribute:: task_name
      :type:  str
      :value: None



   .. py:attribute:: _celery_app
      :type:  Any
      :value: None



   .. py:attribute:: _is_evaluating
      :type:  bool
      :value: None



   .. py:method:: _get_celery_app()


   .. py:method:: __call__(context: ccflow.callable.ModelEvaluationContext) -> Any

      This method produces the result for the given context.

      Instead of passing the context, one can pass an object that pydantic will try to validate as the context.
      Additionally, if kwargs are passed instead of the context, it will use these to construct the context.



.. py:data:: __version__
   :value: '0.1.0'