ccflow_celery

Submodules

• ccflow_celery.app
• ccflow_celery.config
• ccflow_celery.evaluators
• ccflow_celery.examples
• ccflow_celery.tasks

Attributes

__version__

Classes

CeleryConfig	Configuration for a Celery application.
CeleryApp	Wrapper around a Celery application instance.
CeleryEvaluator	Evaluator that dispatches model execution to Celery workers.
CeleryGraphEvaluator	Evaluator that parallelizes DAG execution via Celery.

Package Contents

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

Bases: 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.

broker_url: str = None

result_backend: str | None = None

task_serializer: str = 'json'

result_serializer: str = 'json'

accept_content: list = None

task_track_started: bool = True

task_default_queue: str = 'default'

task_routes: Dict[str, str] | None = None

worker_concurrency: int | None = None

task_always_eager: bool = None

task_eager_propagates: bool = None

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

Bases: 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.

name: str = None

config: CeleryConfig = None

_app: Any = None

get_app()

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

Bases: 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.

app: ccflow_celery.app.CeleryApp = None

timeout: float | None = None

task_name: str = None

_celery_app: Any = None

_get_celery_app()

__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.

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

Bases: 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.

app: ccflow_celery.app.CeleryApp = None

timeout: float | None = None

task_name: str = None

_celery_app: Any = None

_is_evaluating: bool = None

_get_celery_app()

__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.

ccflow_celery.__version__ = '0.1.0'