MLflow Experiment

laktory.models.resources.databricks.MLflowExperiment

Bases: BaseModel, PulumiResource, TerraformResource

MLflow Experiment

Examples:

from laktory import models

exp = models.resources.databricks.MLflowExperiment(
    name="/.laktory/Sample",
    artifact_location="dbfs:/tmp/my-experiment",
    description="My MLflow experiment description",
    access_controls=[
        {
            "group_name": "account users",
            "permission_level": "CAN_MANAGE",
        }
    ],
)

PARAMETER	DESCRIPTION
access_controls	Access controls list TYPE: list[AccessControl | VariableType] | VariableType DEFAULT: []
artifact_location	Path to dbfs:/ or s3:// artifact location of the MLflow experiment. TYPE: str | VariableType DEFAULT: None
creation_time	TYPE: int | VariableType DEFAULT: None
description	The description of the MLflow experiment. TYPE: str | VariableType DEFAULT: None
experiment_id	TYPE: str | VariableType DEFAULT: None
last_update_time	TYPE: int | VariableType DEFAULT: None
lifecycle_stage	TYPE: str | VariableType DEFAULT: None
name	Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. /Users/<some-username>/my-experiment. For more information about changes to experiment naming conventions, see mlflow docs. TYPE: str | VariableType

ATTRIBUTE	DESCRIPTION
additional_core_resources	permissions TYPE: list[PulumiResource]

additional_core_resources property

• permissions