Module core.backends.processing.processing_base_backend

Definition of the data Processing Backend

Classes

ProcessingBaseBackend(**kwargs) : Use this class to run a ZenML pipeline locally.

Every ZenML pipeline runs in backends.

A dedicated processing backend can be used to efficiently process large
amounts of incoming data in parallel, potentially distributed across
multiple machines. This can happen on local processing backends as well
as cloud-based variants like Google Cloud Dataflow. More powerful machines
with higher core counts and clock speeds can be leveraged to increase
processing throughput significantly.

### Ancestors (in MRO)

* zenml.core.backends.base_backend.BaseBackend

### Class variables

`BACKEND_TYPE`
:

### Methods

`get_beam_args(self, pipeline_name: str = None, pipeline_root: str = None) ‑> Union[List[str], NoneType]`
:   Returns a list of beam args for the pipeline.
    
    Args:
        pipeline_name: Name of the pipeline.
        pipeline_root: Root dir of pipeline.