content: #  Copyright (c) ZenML GmbH 2022. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
  #  or implied. See the License for the specific language governing
  #  permissions and limitations under the License.
  """Airflow orchestrator flavor."""
  
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Type
  
  from pydantic import field_validator
  
  from zenml.config.base_settings import BaseSettings
  from zenml.integrations.airflow import AIRFLOW_ORCHESTRATOR_FLAVOR
  from zenml.orchestrators import BaseOrchestratorConfig, BaseOrchestratorFlavor
  
  if TYPE_CHECKING:
      from zenml.integrations.airflow.orchestrators import AirflowOrchestrator
  
  from enum import Enum
  
  
  class OperatorType(Enum):
      """Airflow operator types."""
  
      DOCKER = "docker"
      KUBERNETES_POD = "kubernetes_pod"
      GKE_START_POD = "gke_start_pod"
  
      @property
      def source(self) -> str:
          """Operator source.
  
          Returns:
              The operator source.
          """
          return {
              OperatorType.DOCKER: "airflow.providers.docker.operators.docker.DockerOperator",
              OperatorType.KUBERNETES_POD: "airflow.providers.cncf.kubernetes.operators.kubernetes_pod.KubernetesPodOperator",
              OperatorType.GKE_START_POD: "airflow.providers.google.cloud.operators.kubernetes_engine.GKEStartPodOperator",
          }[self]
  
  
  class AirflowOrchestratorSettings(BaseSettings):
      """Settings for the Airflow orchestrator.
  
      Attributes:
          dag_output_dir: Output directory in which to write the Airflow DAG.
          dag_id: Optional ID of the Airflow DAG to create. This value is only
              applied if the settings are defined on a ZenML pipeline and
              ignored if defined on a step.
          dag_tags: Tags to add to the Airflow DAG. This value is only
              applied if the settings are defined on a ZenML pipeline and
              ignored if defined on a step.
          dag_args: Arguments for initializing the Airflow DAG. This
              value is only applied if the settings are defined on a ZenML
              pipeline and ignored if defined on a step.
          operator: The operator to use for one or all steps. This can either be
              a `zenml.integrations.airflow.flavors.airflow_orchestrator_flavor.OperatorType`
              or a string representing the source of the operator class to use
              (e.g. `airflow.providers.docker.operators.docker.DockerOperator`)
          operator_args: Arguments for initializing the Airflow
              operator.
          custom_dag_generator: Source string of a module to use for generating
              Airflow DAGs. This module must contain the same classes and
              constants as the
              `zenml.integrations.airflow.orchestrators.dag_generator` module.
              This value is only applied if the settings are defined on a ZenML
              pipeline and ignored if defined on a step.
      """
  
      dag_output_dir: Optional[str] = None
  
      dag_id: Optional[str] = None
      dag_tags: List[str] = []
      dag_args: Dict[str, Any] = {}
  
      operator: str = OperatorType.DOCKER.source
      operator_args: Dict[str, Any] = {}
  
      custom_dag_generator: Optional[str] = None
  
      @field_validator("operator", mode="before")
      @classmethod
      def _convert_operator(cls, value: Any) -> Any:
          """Converts operator types to source strings.
  
          Args:
              value: The operator type value.
  
          Returns:
              The operator source.
          """
          if isinstance(value, OperatorType):
              return value.source
  
          try:
              return OperatorType(value).source
          except ValueError:
              return value
  
  
  class AirflowOrchestratorConfig(
      BaseOrchestratorConfig, AirflowOrchestratorSettings
  ):
      """Configuration for the Airflow orchestrator.
  
      Attributes:
          local: If the orchestrator is local or not. If this is True, will spin
              up a local Airflow server to run pipelines.
      """
  
      local: bool = True
  
      @property
      def is_local(self) -> bool:
          """Checks if this stack component is running locally.
  
          Returns:
              True if this config is for a local component, False otherwise.
          """
          return self.local
  
      @property
      def is_schedulable(self) -> bool:
          """Whether the orchestrator is schedulable or not.
  
          Returns:
              Whether the orchestrator is schedulable or not.
          """
          return True
  
  
  class AirflowOrchestratorFlavor(BaseOrchestratorFlavor):
      """Flavor for the Airflow orchestrator."""
  
      @property
      def name(self) -> str:
          """Name of the flavor.
  
          Returns:
              The name of the flavor.
          """
          return AIRFLOW_ORCHESTRATOR_FLAVOR
  
      @property
      def docs_url(self) -> Optional[str]:
          """A url to point at docs explaining this flavor.
  
          Returns:
              A flavor docs url.
          """
          return self.generate_default_docs_url()
  
      @property
      def sdk_docs_url(self) -> Optional[str]:
          """A url to point at SDK docs explaining this flavor.
  
          Returns:
              A flavor SDK docs url.
          """
          return self.generate_default_sdk_docs_url()
  
      @property
      def logo_url(self) -> str:
          """A url to represent the flavor in the dashboard.
  
          Returns:
              The flavor logo.
          """
          return "https://public-flavor-logos.s3.eu-central-1.amazonaws.com/orchestrator/airflow.png"
  
      @property
      def config_class(self) -> Type[AirflowOrchestratorConfig]:
          """Returns `AirflowOrchestratorConfig` config class.
  
          Returns:
              The config class.
          """
          return AirflowOrchestratorConfig
  
      @property
      def implementation_class(self) -> Type["AirflowOrchestrator"]:
          """Implementation class.
  
          Returns:
              The implementation class.
          """
          from zenml.integrations.airflow.orchestrators import (
              AirflowOrchestrator,
          )
  
          return AirflowOrchestrator
  