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Kubeflow

Initialization of the Kubeflow integration for ZenML.

The Kubeflow integration sub-module powers an alternative to the local orchestrator. You can enable it by registering the Kubeflow orchestrator with the CLI tool.

KubeflowIntegration

Bases: Integration

Definition of Kubeflow Integration for ZenML.

Source code in src/zenml/integrations/kubeflow/__init__.py 
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class KubeflowIntegration(Integration):
    """Definition of Kubeflow Integration for ZenML."""

    NAME = KUBEFLOW
    REQUIREMENTS = ["kfp>=2.6.0", "kfp-kubernetes>=1.1.0"]  # Only 1.x version that supports pyyaml 6
    REQUIREMENTS_IGNORED_ON_UNINSTALL = [
        "kfp", # it is used by GCP as well
    ]

    @classmethod
    def flavors(cls) -> List[Type[Flavor]]:
        """Declare the stack component flavors for the Kubeflow integration.

        Returns:
            List of stack component flavors for this integration.
        """
        from zenml.integrations.kubeflow.flavors import (
            KubeflowOrchestratorFlavor,
        )

        return [KubeflowOrchestratorFlavor]

flavors() classmethod

Declare the stack component flavors for the Kubeflow integration.

Returns:

Type Description
List[Type[Flavor]]

List of stack component flavors for this integration.
Source code in src/zenml/integrations/kubeflow/__init__.py 
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@classmethod
def flavors(cls) -> List[Type[Flavor]]:
    """Declare the stack component flavors for the Kubeflow integration.

    Returns:
        List of stack component flavors for this integration.
    """
    from zenml.integrations.kubeflow.flavors import (
        KubeflowOrchestratorFlavor,
    )

    return [KubeflowOrchestratorFlavor]